Reviewerly/exHarmony huggingface dataset:
Педагогика партнерства и проектное обучение как способы развития субъектов современного образования

The modern educational system has no chance to avoid responding the challenges of the emerging digital civilization and multimedia culture. To authors’ opinion, such response is the actualization of subject-subjective nature of educational service production/consumption. Taking into account the contradiction between traditionally formed, essentially conservative paradigm of educational process and explosive improvement of life conditions in the modern society, the authors suggest to activate the partnership pedagogics as the meaningful response of university education to to the modern era challenges. The article discusses the experience of partnership pedagogics in the project leaning format in conditions of educational process at Plekhanov Russian University of Economics. The paper objective is to present the analysis results of cognitive abilities of a student as a partner in the project learning context. The research methodology and techniques predetermine consideraing the view of a student role in the project  learning process as an equal, motivated actor participating in the process of education and self-education, actively interacting with a scientific supervisor-tutor. Viewing the student as the partner in the project learning context supposes understanding the relevance of the student subjective position. Adjustment of educational paradigm  actually forming “soft skills” primarily enables shift of education processes from traditional subject-object “stuffing students up” with  information to subject-subjective student “self-education  management”; students have their research, organizational and creative tasks. The dilemma of many modern pedagogical practices is associated with the necessity to master “hard skills” (basic, programme skills), and “soft skills” (mobile skills, connected to  creativity, dialogue and openness to multiple ways of task-solutions). The essential solution of this contradiction and the possibility of its  “sublation” on the higher level is related to the partnership pedagogy, where the student is regarded as the equal, equipotent agent, active  and initiative participant in the educational process interaction. The  future research prospects are connected to the psychological analysis of humanistic oriented practices in the educational process.
FIRST ROUNDTABLE ON PRACTICES AND STANDARDS IN FORENSIC AUTHORSHIP ANALYSIS (OVERVIEW 2)

The article provides an overview of the reports of the 1st Roundtable on Practices and Standards in Forensic Authorship. The roundtable was held by the International Association of Forensic Linguistics and the Centre for Digital Humanities at the University of Manchester on May 15, 2019. The review presents a co-authored report by Krzysztof Kredens from the University of Aston and Piotr Rezik “Large-scale author classification — looking into the black box”, Jack Grieve, Professor of Linguistics at the University of Birmingham “Register variation and authorship analysis” and the report by Jack Grieve, Professor of Linguistics at the University of Birmingham, “Register variation and authorship analysis”. Each report is supplemented with questions to the speaker and their answers to them. The first report looks at the issue of authorship identification on the material of short messages from popular Internet forums («Musmnet» is one of them). Data processing involves the k-nearest neighbors algorithm and uses the following style markers: n-grams, POSlemmas with neutralized polysemanticity, collocations demonstrating typical lexical realizations of syntactic constructions (phrasal verbs, direct objects and subjects expressed by pronouns). In case there are no universally accepted markers, it is necessary each time to find optimal parameters and treat each case as unique. In his report on stylometry, Jack Grieve argues that the functional theory of language variation is more suitable as a foundation for it than sociolinguistics: language varies in different contexts because some linguistic forms suit these contexts better than others. To demonstrate the advantages of the functional approach, a stylometric analysis of the articles of two political columnists of “The Telegraph” is performed. The style of analytical columns of these authors differs depending on the communication strategy: the style of one author is more narrative, and that of the other is more analytical. The reporter concludes that the functional theory of authorship identification studies can become more reliable than the sociolinguistic theory of individual style and can be considered a foundation of forensic linguistics on the whole.
Optimizing Operating Points for High Performance Lesion Detection and Segmentation Using Lesion Size Reweighting.

There are many clinical contexts which require accurate detection and segmentation of all focal pathologies (e.g. lesions, tumours) in patient images. In cases where there are a mix of small and large lesions, standard binary cross entropy loss will result in better segmentation of large lesions at the expense of missing small ones. Adjusting the operating point to accurately detect all lesions generally leads to oversegmentation of large lesions. In this work, we propose a novel reweighing strategy to eliminate this performance gap, increasing small pathology detection performance while maintaining segmentation accuracy. We show that our reweighing strategy vastly outperforms competing strategies based on experiments on a large scale, multi-scanner, multi-center dataset of Multiple Sclerosis patient images.
Improving Students’ Reading Comprehension Of Narrative Text Through Think Aloud Technique At The Eleventh Grade Students Of MAS Al Washliyah 22 Tembung Academic Year 2019/2020

This research aimed to find out the improvement of students’ readingcomprehension of narrative text through Think Aloud Technique. The subject ofresearch were 28 students in grade XI IIS-B MAS Al-WasliyahTembung. Thisresearch was conducted by using Classroom Action Research by Kemmis and McTaggart, which consisted of two cycles. There were two kinds of approach inanalyzing the data, the first was qualitative approach to analyze the data that wereobtained from observation, interview, diary notes and documentation using Milesand Huberman technique namely data condentation, data display, and conclutionand verification. The second was the quantitative approach to analyze the dataobtained from reading test that was analyzed by using the mean and percentagescores formula. The result of this research showed that the students’ readingcomprehension of narrative text improved after the implementation of think aloudtechnique, which was indicated by the improvement of students’ scores in thereading test. The students’ mean score was higher after the implemention of thetechnique. It can be shown from the result of pre-test, post-test 1 and post-test 2.In the pre-test, the students ‘ mean score was 55,7with only three students or10,71% of 28 students who passed the minimum passing grade. In the post-test I,the mean of students’ score was 71 with 10 students or 37,5% passing theminimum of passing grade. At the post-test 2, the mean score of students scorewas 84,6 with 23 students or 82,14% who passed the minimum of passing grade.These results indicated that the think aloud technique can improve students’reading comprehension in narrative text. In addition to the improvement ofcomprehension, the students also showed more participation during the process ofteaching-learning in the class
Quantum Meets the Minimum Circuit Size Problem

In this work, we initiate the study of the Minimum Circuit Size Problem (MCSP) in the quantum setting. MCSP is a problem to compute the circuit complexity of Boolean functions. It is a fascinating problem in complexity theory---its hardness is mysterious, and a better understanding of its hardness can have surprising implications to many fields in computer science. We first define and investigate the basic complexity-theoretic properties of minimum quantum circuit size problems for three natural objects: Boolean functions, unitaries, and quantum states. We show that these problems are not trivially in NP but in QCMA (or have QCMA protocols). Next, we explore the relations between the three quantum MCSPs and their variants. We discover that some reductions that are not known for classical MCSP exist for quantum MCSPs for unitaries and states, e.g., search-to-decision reduction and self-reduction. Finally, we systematically generalize results known for classical MCSP to the quantum setting (including quantum cryptography, quantum learning theory, quantum circuit lower bounds, and quantum fine-grained complexity) and also find new connections to tomography and quantum gravity. Due to the fundamental differences between classical and quantum circuits, most of our results require extra care and reveal properties and phenomena unique to the quantum setting. Our findings could be of interest for future studies, and we post several open problems for further exploration along this direction.
Influence of entanglement on precision of parameter estimation in quantum weak measurement

An appropriate weak value can be used to amplify weak physical parameters and improve the precision of parameter estimation in the process of quantum weak measurement. The increase of the precision of such a parameter estimation may originate from the entanglement in the system. This paper uses Fisher information to study the influence of the entanglement in the system and the entanglement between the system and the pointer on the estimation precision of the coupling parameters between the system and the pointer in the process of weak measurement. The entanglement of the entangled pure state of the GHZ-like state and the entangled mixed state affected by the depolarization noise and the influence of the entanglement between the system and the pointer on the parameter estimation are analyzed. The results show that the Fisher information quantity increases with the increase of the initial state entanglement degree of the system when the initial state of the system is an entangled pure state or an entangled mixed state affected by depolarization noise, and both the Fisher information quantity and the post-selection probability reach their maximum values when the initial and final state of the system are both the maximum entangled states; but the weaker the entanglement between the system and the pointer, the more the Fisher information obtained in the measurement will be and the higher the accuracy of parameter estimation. These research results show that the entanglement in the system will improve the precision of parameter estimation, while the entanglement between the system and the pointer will reduce the precision of parameter estimation.
Machine Learning Uplink Power Control in Single Input Multiple Output Cell-free Networks

This thesis considers the uplink of cell-free single input multiple output systems, in which the access points employ matched-filter reception. In this setting, our objectiveis to develop a scalabl ...
Perancangan Sistem Pencatatan Akuntansi dan Pelaporan Keuangan Pada Rumah Makan Gorengan Kamput

Information technology has experienced very fast development at this time. Rumah Makan Gorengan Kamput is one of the SME’s in the city of Batam, during operation they still use manual accounting and financial reporting records. This community service (PkM) is expected to be able to provide support to SME Rumah Makan Gorengan Kamput. The author uses the PHP programming language and the waterfall method to complete the system with several stages such as requirements analysis, design, development, testing, implementation. The final result of this research is a website application that will be used by business owners to help their business activities.
High-Throughput and Predictable VM Scheduling for High-Density Workloads

In the increasingly competitive public-cloud marketplace, improving the efficiency of data centers is a major concern. One way to improve efficiency is to consolidate as many VMs onto as few physical cores as possible, provided that performance expectations are not violated. However, as a prerequisite for increased VM densities, the hypervisor’s VM scheduler must allocate processor time efficiently and in a timely fashion. As we show in this thesis, contemporary VM schedulers leave substantial room for improvements in both regards when facing challenging high-VM-density workloads that frequently trigger the VM scheduler. As root causes, we identify (i) high runtime overheads and (ii) unpredictable scheduling heuristics.To better support high VM densities, we propose Tableau, a VM scheduler that guarantees a minimum processor share and a maximum bound on scheduling delay for every VM in the system. Tableau combines a low-overhead, core-local, table-driven dispatcher with a fast on-demand table-generation procedure (triggered on VM creation/teardown) that employs scheduling techniques typically used in hard real-time systems. Further, we show that, owing to its focus on efficiency and scalability, Tableau provides comparable or better throughput than existing Xen schedulers in dedicated-core scenarios as are commonly employed in public clouds today.Tableau also extends this design by providing the ability to use idle cycles in the system to perform low-priority background work, without affecting the performance of primary VMs, a common requirement in public clouds.Finally, VM churn and workload variations in multi-tenant public clouds result in changing interference patterns at runtime, resulting in performance variation. In particular, variation in last-level cache (LLC) interference has been shown to have a significant impact on virtualized application performance in cloud environments. Tableau employs a novel technique for dealing with dynamically changing interference, which involves periodically regenerating tables with the same guarantees on utilization and scheduling latency for all VMs in the system, but having different LLC interference characteristics. We present two strategies to mitigate LLC interference: a randomized approach, and one that uses performance counters to detect VMs running cache-intensive workloads and selectively mitigate interference.
Reading, Writing, and Counting (Calistung) Application for Early Childhood

As it has been known here on earth, every era will usher in a new form of development. Evolution keeps on moving forward. Technology is one of the points which have developed at an unprecedented rate. The world of technology has lately seeped into the world of education in the form of digital education. This study sets its sites on how to use the Calistung application in learning, literacy, reading, writing, and arithmetics. The method which will be used in this study process will be a form of pretest-posttest with a quantitative approach. The results garnered from the study showed an increased average grade. This was after the subjects were given instructions through a video tutorial on how to use the Calistung application through YouTube and WhatsApp group chats. The result received from the study showed that the average score of the posttest was 86% whilst the pretest was 76%. A 10% increase due to a different format of learning. What can be concluded from this test is that the use.
Utilize Medical Text Data to Estimate Disease Types by Using Naïve Bayes and ANN Classifier

The primary concept of the hospital is the provision of health services to the community. In many cases, the utilization of information technology to record all hospital activity data can improve hospitals' quality services. However currently, the data is only stored in the database and used as history without further use. Many experiences show that optimizing data usage can greatly assist doctors in making decisions to minimize medical errors. For example, examination data that among others of anamnesis (medical abstract), blood pressure, temperature, and other patient’s symptom data can be used to classify the kind of disease. One of the challenges in medical data utilization is that these data consists of various formats, structured, and unstructured as well. In this study, we address the medical unstructured data format by using Natural Language Processing approach. The combination of its representation results with the structured format data is then used as the dataset to build the model for disease type prediction based on Naive Bayes and Artificial Neural Network classifier. By using these two algorithms, the results of the classification of the kind of disease. The performed experiments show that the ANN model performs better with the best accuracy average of 89.29% compared to Naive Bayes, which is 80.60 %.
House of Flower, House of Harmony

House of Flower, House of Harmony is a mixed media collage created by the Malaysian woman artist Mastura Abdul Rahman in 1999. It shows a Congkak board in the midst of a circle expressing the beauty and harmony of traditional Malay culture. The artwork, which measures 183 cm x 276 cm, is owned by the National Art Gallery of Malaysia in Kuala Lumpur.
The effect of airflow on (visually induced) motion sickness during a simulated driving task

Driving simulators are highly valuable tools for research, rehabilitation, and training purposes, but are also known for commonly causing simulator sickness, a special form of traditional motion sickness that is primarily driven by stimulation of the visual system. Simulator sickness can increase the users’ rate of terminating a simulated driving session dramatically and can be as high as 77%. Although the alleviation of simulator sickness is crucial for ensuring the users’ well-being and guaranteeing the quality of driving performance data, reliable methods that successfully reduce simulator sickness have not yet been identified. Thus, the goals of the present study were (1) to investigate the efficacy of airflow as a countermeasure against simulator sickness and (2) to explore the relationship between airflow and the participants’ subjective comfort. Twenty-four healthy young adults (14F, 10M) were engaged in a 25.5km long simulated driving task using The KITE Research Institute’s high-fidelity driving simulator. To study the effect of airflow on simulator sickness, car vents were directed to generate airflow that directly passed over the driver’s skin (direct airflow condition; n = 11) or towards the ceiling of the car (indirect airflow condition, n = 13). Simulator sickness was assessed using the Fast Motion Sickness scale and the Simulator Sickness Questionnaire. Results suggested that simulator sickness was reported to be mild on average (mean FMS score of 5.31) and did not differ between the two airflow conditions. However, participants in the direct airflow condition reported to feel colder (p = .019) and to be more uncomfortable (p = .044) than participants in the indirect airflow condition. Taken together, our findings indicated that both types of airflow had similar effects on simulator sickness, but that the use of indirect airflow may be preferred to direct airflow as it promotes greater subjective comfort while achieving similar results.
Recall of faces quantified through an avatar creation interface

A variety of methods have been used to study visual memory for images including recall tasks, recognition tasks, verbal description, and recently, drawing recall tasks. However, when it comes to recollection of faces, studies have largely failed to capture the precise details during free recall that allow for quantitative analysis. Here, we propose a new method utilizing an avatar creation tool to provide a numerical representation of face recollection. The interface contains a 3D character model, and sliders that range from -1 to 1 for each facial feature. Changes made to features such as nose width or prominence of laugh lines are updated in real-time, so participants can understand the effects of each slider on their representation of a face. Participants were first shown sample human faces that were constructed in the face tool for a period of time (20 seconds) and told to memorize as much as they could. After the face image was presented, they were then shown the character creation interface with instructions to recreate the face as best they could from memory. After this memory task, a perceptual task was conducted where participants had to recreate the faces again, this time with the image available as a reference. We identified key differences between face recall and perception, along with perception and the ground truth in participants’ abilities to reconstruct faces. Specifically, face reconstruction was improved when using a reference as opposed to relying on memory, demonstrating that this interface can be an effective method to capture representations of faces in perception and memory. Overall, the use of this interface allows for a new method to study the recollection of faces with precise quantification of specific features.
Parametric Study of Double Axes Tracking Heliostat to Optimize Heliostat Field Efficiency

The paper presents the research on optimization of heliostat field in terms of distance of heliostat relative to the receiver. The heliostat field consist of sun tracking mirror (heliostat) that reflects the sun radiation to the receiver at the top of the tower. Heliostat field efficiency is related to cosine loss and atmospheric attenuation loss. Increasing the distance of heliostat relative to the receiver, results in higher cosine loss and atmospheric loss. The heliostat field is located in Ipoh, Malaysia (latitudea4.340aN). The angle of incidence is calculated using sun position and heliostat position related equations that had been established in the mathematical model.
LibGuides: Early Childhood Reading Support: Year Five

Understanding how early literacy will empower your little one, with practice tools and resources to get you started