Reviewerly/exHarmony huggingface dataset:
Deep learning methods for Electrocorticographic data analyses

Electrocorticography (ECoG) records brain activity from the cortical surface. ECoG data analyses has led to significant advancements in neuroscientific research, particularly in two major domains: functional mapping to understand the cortical organization of human brain; and brain-machine interfaces (BMIs) that decode intent from neural data. Designing high performance BMIs is an active area of interest. A discrete BMI design primarily involves decoding specific targets from features extracted from ECoG data. Majority of ECoG based research studies use spectral features i.e. powers in specific frequency bands; which are based on empirical observations. However, given the non-stationarity and variability of neural signals, features extracted in a data driven way could lead to more robust BMIs. In addition to efficient feature extraction and decoder training, the choice of targets presented to BMI user can greatly affect the bit-rate or throughput of the BMI.The ability to record ECoG data in the order of days in epilepsy monitorig units (EMU); in synchrony with behavioral data through non-invasive sensors like Kinect; has resulted in deluge of large-scale, coarsely labelled datasets. Deep learning architectures are being explored to tackle this big-data problem and extract meaningful spatio-temporal patterns from these data. However, much of the existing research has been relying on architectures that found success in other domains such as computer vision and audio. A more systematic approach towards neural network architecture designs for analyzing large-scale ECoG datasets, that embeds domain knowledge from neuroscience and neurophysiology, is necessary.The contributions of this thesis are three-fold. Firstly, I show that we can increase the throughput of a speech-based BMI by using targets that generate maximal separation in neural space. Secondly, I show that data-driven features can be learnt in an unsupervised fashion using autoencoders and are more robust compared to linear dimensionality reductions methods like PCA. These features also aid in funcional mapping by identifying functionally similar electrodes in unsupervised fashion. Lastly, I show that cross-subject model can be learnt to decode finger flexions by learning common latent spaces that map activity from different subjects onto a single latent space. By learning temporal dynamics using a recurrent neural network, from this common space, we show that we can decode continuous behvaiors from ECoG.By analyzing the architectural design decisions on smaller, well-structured and labelled datasets, we can have a smarter approach towards developing deep learning toolkits for larger, coarsely labelled or unlabelled datasets. The methods described in this thesis will aid neuroscientists in ECoG data analysis, clinicians by providing data driven functional mapping methods, and neural engineers by providing more robust machine learning pipelines for BMI design.
Modern Mathematics Lesson for the 6th Grade Based on the TSIP Pedagogy

Modern society requires new demands on the personality: knowledge of key competencies, communicativeness, purposefulness, creativity, critical thinking, and autonomy in guidance of the information flow. The problem, addressed in the report, is the need to change the goals and the content of education, the innovation of educational resources, and educational technologies aimed at heuristic learning, constructive learning and learning through research (The Theory of Solving Inventory Problems – TSIP, Montessori Pedagogy, Jump Math and others). This change also affects mathematics lesson as a basic form of education. The pedagogical ideas of the TSIP are systematized in the article. A model of a modern mathematics lesson for the 6th grade, based on the TSIP pedagogy, was developed, and it is aimed at developing the universal learning activities of the students.
Enhanced Scheduling Algorithms for Cloud Computing

In today’s era, Cloud Computing is widely used for parallel processing and distributed computing. Shared computer processing resources and data to computers and additional devices on the demand are provided by cloud computing these days. The suitability and execution of Cloud computing services is always dependent on the completion of the user tasks. The main form of scheduling performed is the task scheduling. For the establishment of cloud computing system the major problem is scheduling. The scheduling algorithms should sort the jobs in a manner that there is a balance between quality of service and improving the performance as well as maintaining the fairness and efficiency among the jobs. The main aim of the paper is to study different scheduling methods as there are several scheduling techniques that are developed by different researchers, for example, Priority based Job Scheduling Algorithm, GA (Genetic Algorithm), PSO (Particle Swarm Optimization), Min-Min and Max-Min.
네이버 데이터랩 검색어 트렌드 서비스를 이용한 온라인 포털에서의 한약재 검색 트렌드와 의미에 대한 고찰

Objectives : From January 2020, when the first confirmed case of COVID-19 in Korea, the use of health information using the Internet is expected to increase. It is expected that there will be a significant change in the general public''s interest in Korean herbal medicines for health care. Therefore, in this study, we tried to confirm the change in the search trend of Korean herbal medicines after the COVID-19 epidemic.Methods : Using the “Naver DataLab (http://datalab.naver.com)” service of a Korean portal site Naver, search volume was investigated with 606 Korean herbal medicines as keywords. The search period was from January 2020, right after the onset of COVID-19, to June 2021. The search results were sorted by the peak search volume and the total search volume.Results : ‘Cheonsangap (천산갑, 穿山甲, Manitis Squama)’ was the most searched Korean herbal medicine in the peak search volume and total search volume with least bias.Conclusions : The problem of supply and demand of Korean herbal medicines of high public interest was identified. Broadcasting and media exposure were the factors that had a big impact on the search volume for Korean herbal medicines. As it was confirmed that the search volume for Korean herbal medicines increased rapidly due to media exposure, it is necessary to provide correct information about Korean herbal medicines, improve public awareness, and manage stable supply and demand based on continuous search trend monitoring.
AN ANALYSIS OF VOCABULARY TRAINING FANPAGEON INSTAGRAM

ABSTRACTKhomaisaroh, Nurul, 2020. An Analysis of Vocabulary Training Fanpage onInstagram”. Skripsi, English Education Study Program, Faculty of Language and Arts Education, IKIP PGRI Bojonegoro, theFirst Advisor: ChyntiaHeruWoro, S.Pd, M.Pd and theSecond Advisor :OkhtaIkaRahmawati, S.Pd, M.Pd.This research is to describe the tutor trainng fanpage method vocabulary on instagramand identify the followers responses towards material vocabulary on english fanpage.It is conducted to know how the tutor used,the media to give explanation the vocabulary through video on instagram and the visitor’s followers response to the method the teacher gave in video on instagram.The researcher used descriptive qualitative to analyze the data.The researcher collected the data by observation and documenting some important the data from the tutor and the visitors’followers that support to this research..The data were collected from interview,and identify the visitor’s followers responses to this method.The techniques of analyzing data were reduction the data,data analysis,presenting the data,and drawing the conclusion.The subject of this research focuses on the tutor method vocabulary and the response of the visitor’s followers.The object of this research is the method of vocabulary training fanpage on instagram.Based on the collecting of the data,the researcher concluded that the material used by the english tutor were (1) synonym,idiom,and idiom expression.The media used by english tutor were real things,video.Then,the strategies used by the tutor were : (1) ask the visitor to make an example from the tutor method vocabulary.The problems of implementation is : (1) the teacher didnn’t give and put the method of vocabulary on instastory as the famous fiture the instagrammer used.The visitor’s didn’t has any problem about the method,because the response from the participant comment the researcher gotten the data,the visitor’s always satiesfied with the method of vocabulary the teacher has given to the visitor’s followers.Keyword : Analysis, The Method Of Vocabulary, Identify the Participants on Instagram
Possibilities of using interactive methodology in teaching geography

The article considers the features of the types of interactive methods and the possibility of their use in geography lessons. The importance of methods and formative skills in the student is emphasized. At present, the Republic of Kazakhstan, as a young independent state, is reorganizing all aspects of public life, defining its own path of development. In particular, the social role of the teacher is growing. Taking into account the development needs, it was able to independently address the requirements and issues related to education. One of the important tasks in the field of education is the introduction of new learning technologies, informatization of education, access to the global system of international communication. The search for and implementation of new innovative learning technologies aimed at meeting the needs of time and society at a high level has become widespread. Over the years, time has shown that interactive technologies are in demand with a variety of ideas, information and knowledge. Therefore, the article focuses on the interactive methods of teaching students, which are used in my pedagogical practice. It proves that the use of interactive methods in the classroom in the study of modern pedagogical technologies has a significant impact on the quality and fun of the lesson.
THE EFFECT OF USING ENGLISH ON INSTAGRAM PROMOTION TOWARD PURCHASE INTENTION AT MILK BAR CAFÉ PONTIANAK

Promotion is an essential process where the business builds a bridge to the public and makes an impression to attract potential consumers and also to maintain the consumers. In this modern era, one of the ways to do the promotion is through social media, which is Instagram. Besides the media, language plays an important role that able leading to a purchase intention. The purchase intention occurs when the target market feels the product suitable for their need inparticular aspects. This research is conducted to find the effect of using the English Language for business promotion in non-English spoken countries, specifically in Pontianak, and to narrow down the research, the writer chose Milk Bar Cafe as the object of this research. This research is quantitative associative research using SPSS version 25. The associative approach is suitable for this research since the writer wants to know the relation between the EnglishLanguage for promotion on Instagram toward purchase intention and the effect that emerged. The result of this research shows that using the English Language for business promotion has a significant effect on increasing the markets’ purchase intention in the connecting and community building aspects.
THE EDUCATIONAL PROCESS DURING A PANDEMIC. THE EXPERIENCE OF THE RSUH

The article deals in the analysis of the organization of the educational process at the university during a pandemic. It shows the ability of universities to adapt to possible changes, to make decisions in conditions of uncertainty and risk, to act in extreme situations. The article also considers the reaction of the educational system, executives, teachers and students to the challenges associated with the pandemic. The authors distinctly show the role of digitalization that made it possible not to interrupt the educational process and that is an important factor in sustainable development. Much space in the article is paid to the issues of emotional stability of all categories of the staff employees and students. The prospect for a mixed format in realizing the educational process, the acquisition of digital competencies by teachers and students is shown.
Teaching C++ as a First Programming Language

Nowadays, most C++ introductory courses begin by studying the procedural constructs of C language, following the imperative-first strategy described in CC2001 [7]. While this has been a successful approach in the near past, our experience shows that it does not lead to the development of skills to create a good C++ code. That’s why in recent years we’ve been teaching C++ to beginners in a totally different way – with avoidance of C-style strings and raw arrays; delayed introduction to pointers (just after references); polymorphism with references instead of pointers; smart pointers instead of raw pointers; early use of standard library features, and writing modern C++ from day one.
LibGuides: Landing Your Dream Job: Job Searching

This guide is based on information provided by Jan-Marie Lanuzza, Experiential Education Coordinator and Jean Moats, Director of Library Services.
Quantitative patterns in the poetic structure of The Temple Hymns by Enkheduanna

The Temple Hymns by Enheduanna, high priestess of Sumer Moon god Nanna in Ur and daughter of king Sargon of Akkad (2334-2279 BCE), consist of 42 hymns that praise the significant temples of the Mesopotamian cities and their deities. By their writing the goal of uniting the Sumer-Akkad pantheon was set as a part of the wider political task of uniting the Sumerian and Akkadian peoples set by Sargon of Akkad. Numerical patterns in the structure of the hymns are studied in the present paper, with special attention to the number of the lines in each hymns as stated in the colophons. It is demonstrated that the sum of the lines of all hymns is an exact multiple of 100 whereas the sums of the number of lines in both first and second halves of the hymns and several of their subsets make exact multiples of 50 and 10 respectively. A hypothesis is proposed for the deliberate choice of these exact numbers by the author of the hymns and their considerable achievement in the poetic structure of the hymns, as well as achieving the set goal, among other means, by the means of quantitative poetic structure of the hymns.
Concert performances in support of the future musical pedagogue

The article examines the role of stage performances of future musical pedagogues in coping with stress when standing in front of students in class. The presence of direct and indirect parallels between the two types of activities: performing and teaching, justifies the assumption that the skills acquired and the routine established in concert performances can be successfully applied in music lessons.
Digital signatures over HMAC entangled chains

In this work we present a new digital signature method based on hash chains and the hash message authentication code (HMAC). Unlike Blockchain technology, our approach establishes that the database of transactions is distributed among users, so each one maintains a personal record called Singlechain. The Lizama HMAC protocol defines a double authentication mechanism that verifies the origin and destination of the signature. Our analysis shows that the system generates a block size of around 6 kilobytes to perform double authentication using SHA-256, making it a promising alternative for digital signature using public key infrastructure. Since the method is based on the mathematical properties of hash functions and hash chains, the security of the method can be properly evaluated and thereby achieve a robust method of digital signatures in the quantum era.
ADVANCED ROBOTICS & MECHATRONICS AND THEIR APPLICATIONS IN CONSTRUCTION AUTOMATION

The keynote gives the satisfy of-the-workmanship Japanese R&D in mechanical technology and mechatronics firmly identified with the development mechanization. There are three noteworthy household robot gatherings in Japan. Based on the quantity of papers and members the non specific mechanical innovative work is still extremely dynamic. Despite the fact that the development business has been going up against the serious monetary circumstance, we are attempting to keep our R&D exercises in the development computerization. To start with, non specific mechanical autonomy innovations are studied from some Japanese local gatherings, and new application points are presented demonstrating a few case in the development mechanization.
FACTORS AFFECTING THE FORMATION OF THINKING

Scientific stability and instability in the development of thinking are reflected in the exchange of ideas in the activities aimed at meeting the material and spiritual needs of people. The political system and ideology of a society ensure the variability of human thinking. Therefore, man is the main driving force of society, and his thinking is the transforming force. In this context, this article reveals the importance of the formation of human thinking.
Phase transitions for high dimensional clustering and related problems

Consider a two-class clustering problem where we observe $X_{i}=\ell_{i}\mu+Z_{i}$, $Z_{i}\stackrel{\mathit{i.i.d.}}{\sim}N(0,I_{p})$, $1\leq i\leq n$. The feature vector $\mu\in R^{p}$ is unknown but is presumably sparse. The class labels $\ell_{i}\in\{-1,1\}$ are also unknown and the main interest is to estimate them. We are interested in the statistical limits. In the two-dimensional phase space calibrating the rarity and strengths of useful features, we find the precise demarcation for the Region of Impossibility and Region of Possibility. In the former, useful features are too rare/weak for successful clustering. In the latter, useful features are strong enough to allow successful clustering. The results are extended to the case of colored noise using Le Cam’s idea on comparison of experiments. We also extend the study on statistical limits for clustering to that for signal recovery and that for global testing. We compare the statistical limits for three problems and expose some interesting insight. We propose classical PCA and Important Features PCA (IF-PCA) for clustering. For a threshold $t>0$, IF-PCA clusters by applying classical PCA to all columns of $X$ with an $L^{2}$-norm larger than $t$. We also propose two aggregation methods. For any parameter in the Region of Possibility, some of these methods yield successful clustering. We discover a phase transition for IF-PCA. For any threshold $t>0$, let $\xi^{(t)}$ be the first left singular vector of the post-selection data matrix. The phase space partitions into two different regions. In one region, there is a $t$ such that $\cos(\xi^{(t)},\ell)\rightarrow 1$ and IF-PCA yields successful clustering. In the other, $\cos(\xi^{(t)},\ell)\leq c_{0} 0$. Our results require delicate analysis, especially on post-selection random matrix theory and on lower bound arguments.
SISTEM PAKAR DIAGNOSA SERANGAN KEPANIKAN MENGGUNAKAN PENELUSURAN FORWARD CHAINING DAN METODE TEOREMA BAYES BERBASIS WEB

Panic Attack or panic attack is a disturbance of criticism and excessive fear. Panic attacks occur very suddenly for no apparent reason Panic attacks occur when the heart is racing and it is difficult to breathe. Causes of panic attacks can be triggered by past traumatic events, health problems or having a phobia about situations that trigger panic disorders. Lack of information about panic attacks will have a negative impact on life that can affect the sufferer, both psychologically and physically if allowed to continue. This diagnosis is carried out using the knowledge possessed by an expert clinical psychologist which is implemented into an expert system. This expert system uses forward chaining tracing. This search performs a search starting from a set of facts that match the assumptions / hypotheses that lead to the conclusion. And make use of Bayes' Theorem as a method of decision making. The purpose of making this expert system is to check whether a person is diagnosed with a panic attack or not from the symptoms that arise and also to know how to help a person who has a panic attack without having to see a psychiatrist or psychologist. After testing the blackbox, it can be concluded that the system is running as expected. Based on the User Acceptance Testing (UAT) test, it is found that all features in the system have been implemented and received well. Determination of the sample in conducting this usability test using the Slovin formula with an error rate of 10% and a sample size of 17 respondents with a total result of 93.1% that users strongly agree with this system being built. And also the accuracy testing has been done, and the accuracy rate is 100%. Keywords: Expert System, Panic Attack, Forward Chainimg, Bayes Theorem, Web Based
Diagnosis of breast cancer using machine learning algorithms based on features selected by Genetic Algorithm: Assessed on five datasets

Breast Cancer is one of the chronic diseases occurred to human beings throughout the world. Early detection of this disease is the most promising way to improve patients’ chances of survival. The strategy employed in this paper is to select the best features from various breast cancer datasets using a genetic algorithm and machine learning algorithm is applied to predict the outcomes. Two machine learning algorithms such as Support Vector Machines and Decision Tree are used along with Genetic Algorithm. The proposed work is experimented on five datasets such as Wisconsin Breast Cancer-Diagnosis Dataset, Wisconsin Breast Cancer-Original Dataset, Wisconsin Breast Cancer-Prognosis Dataset, ISPY1 Clinical trial Dataset, and Breast Cancer Dataset. The results exploit that SVM-GA achieves higher accuracy of 98.16% than DT-GA of 97.44%.
A research on GPU transactional memory

GPU is one of the important architectures in parallel computing,however,when dealing with high data racing scenarios,programmers often need to design complex parallel schemes.In order to simplify this process,GPU transactional memory implements complex data synchronization and parallelism,and only provides simple API.The research background of GPU transactional memory was introduced.Then,the designs and strategies of GPU transactional memory in recent years were discussed,and the problems and solutions of different designs were analyzed,including the implementation of hardware and software.Finally,the current situation and future development of GPU transactional memory were summarized and prospected.