Reviewerly/exHarmony huggingface dataset:
Guidelines for reporting blood cell morphology – Are laboratories following?

In 2015, the International Council for Standardization in Haematology (ICSH) released a report outlining recommendations for the standardisation of nomenclature and grading of peripheral blood cell morphological features. Based on these, lymphoid cells with a suspected malignant or clonal aetiology should be classified as abnormal lymphocytes with an accompanying description of the cells.1 We sought to evaluate if laboratories were following the ISCH reporting recommendations. Method: Laboratories enrolled in the 2019 RCPAQAP Manual Differential program were provided with clinical notes, a stained blood film (which featured a T-cell prolymphocytic leukaemia case) and asked to categorise the different white blood cells. Assessment was based on robust statistical analysis and the clinical scenario. Results: 79% (378/480) of labs reported the presence of abnormal lymphocytes, however, only 10% (41) provided a description of the abnormal cells. 23 participants included the abnormal cells as part of the lymphocyte count, while 15 participants counted the abnormal cells as ‘others’ without a description. Discussion and conclusion: The main morphological features that were expected to be reported were the presence of abnormal lymphocytes and an associated description (T-cell prolymphocytes). Based on the results for this survey, either laboratories have a low uptake on the ICSH guidelines or they are missing important morphological features indicating the need for standardisation in blood film morphology reporting. Reference1.Palmer L, Briggs C, McFadden S, et al. ICSH recommendations for the standardization of nomenclature and grading of peripheral blood cell morphological features. Int J Lab Haematol 2015; 37: 287–303.
The Students’ Perspectives Toward The Letter Friendship Activity By Using E-Mail In Writing Class At The Tenth Grade of SMA Banua Bilingual Boarding School

This research described about the students’ perspectives toward the letter friendship activity by using E-mail which applied in writing class at Sman Banua Bilingual Boarding School. This research involved 18 students from tenth grade.The objectives of this research were to find out and describe students’ perspectives toward the letter friendship activity by using E-mail in writing skill.The researcher analyzed the data descriptive qualitatively. For data collection the researcher did the observation and interview. The result of the research indicated that according to the students’ perspectives there were 7 advantages and 2 disadvantages. Advantages were as follow; giving much time to prepare the students writing texts, giving the students to have new learning experiences, enabling the students to have a self reflection, making students more interest with writing, minimizing lacks of grammar in writing, encouraging the students to use technology in learning English, giving the students opportunity to use e-mail to communicate the other people. The disadvantages were time consuming and technological deficiencies.The research gave us the belief of positives perspectives and benefits for using technology in classroom. Most of the students thought that the letter friendship activity by using e-mail is usefull in classroom.
Locally Convex Kernel Mixtures: Bayesian Subspace Learning

Kernel mixture models are routinely used for density estimation. However, in multivariate settings, issues arise in efficiently approximating lower-dimensional structure in the data. For example, it is common to suppose that the density is concentrated near a lower-dimensional non-linear subspace or manifold. Typical kernels used to locally approximate such subspaces are inflexible, so that a large number of components are often needed. We propose a novel class of LOcally COnvex (LOCO) kernels that are flexible in adapting to nonlinear local structure. LOCO kernels are induced by introducing random knots within local neighborhoods, and generating data as a random convex combination of these knots with adaptive weights and an additive noise. For identifiability, we constrain all observations from a particular component to have the same mean. For Bayesian inference subject to this constraint, we develop a hybrid Gibbs sampler and optimization algorithm that incorporates a Lagrange multiplier within a splitting method. The resulting LOCO algorithm is shown to dramatically outperform typical Gaussian mixture models in challenging examples.
LibGuides: Paper Monuments: Citing Your Work

Library resources that can be used to research subject of your Paper Monument Mini Project, what it represents, the history of it. These resources can be useful with citing your works used and organizing your resource citations.
Mengidentifikasi Kecerdasan Anak

This article aims to deliver the variety of intelligence that a child can possess also identifying children's intelligence so called multiple intelligence. The thing that lies behind this writing is a people belief that someone's success in the future is the fruit of his success in school today. A measure of one's success at school is his ranking or ability in answering all the questions tested at that time. But in fact it is not always true, that there are examples of people who are successful people who are dropped-out students. In this paper, it discusses the multiple intelligences presented by Howard which include 8 intelligences, namely: 1) Linguistic intelligence (word smart); 2) Spatial intelligence (picture smart); 3) Mathematical intelligence (logic smart); 4) Intelligence of kinesthesis (body smart); 5) Music intelligence (music smart); 6) Interpersonal intelligence (smart people); 7) Intrapersonal intelligence (self smart); 8) Naturalist intelligence (nature smart). A child's intelligence can be identified by a consultation and test for the child.
Pengembangan Modul Pembelajaran Elektronik IPA Terpadu pada Materi Sistem Ekskresi Manusia Kelas VIII SMP

Abstract: The aim of this research is to develop an Integrated Sciens Electronic module learning in human excretion system for VIII grade of junior high school which is valid, practical, and effective. The type of this research is Research and Development (R & D). The development of this module used ADDIE models. The stages of ADDIE are analysis, design, development, implementation, and evaluation. The components of science process skills that used in the module which are observing, communicating, measuring, predicting, and concluding. Assesment of this module was evaluated with two expert validators. The result from expert validators showed that the module is suitable to use because the validity of this product is 4.35 (valid). The practicality of this product was obtained by teachers responses with the value 90.35% (very practical) and students responses with value 94,29% (very practical). The effectiveness of this module is obtained from the learning outcomes of students who follow the entire series of research process that have largely reached the KKM value. Based on these results, it is can be concluded that the development of Integrated Sciens Electronic module learning in human excretion system were valid, practical and effective. Keywords: teaching material, module, electronic
Unsupervised Labeling and Keyword Identification from Conversational Contexts

It is very practical and worthwhile to develop an Unsupervised labeling and keyword identification from conversational contexts. It can modify or add the custom labels you need at any time. We believe that there is no way to achieve this goal in the past because no way to clearly understand the sentence topic or sentence intention. Getting the semantic keyword means getting the meaning of the sentence. In this case, we focus on keyword extraction. We have an accuracy of 0.78125 in commercial conversations. In this paper, we propose a method of keyword extraction and propose ways to do unsupervised labeling and keyword identification from conversational contexts in the future.
Fine tuning of MapReduce jobs using parallel K Map clustering

Advancement and development of information technology has led to huge growth in data, which pose huge challenge into data storage and analysis to conclude meaningful information from data. Size of data ranges from petabyte or exabyte range, to mine information out of large data set will increase the computing capacity. Thus to address and manage this high velocity data growth an advanced processing algorithms and methods are required for data analysis. To achieve same MapReduce word count program and P-KMeans a parallel clustering algorithm used in Hadoop .Through experiment, it has been concluded that execution time reduce when nodes count increases in a cluster, but also some of the important points has been observed while conducting experiment. Various performance change, and plotted results on different performance charts. This paper aims to study MapReduce applications and its performance verification and improvement recorded for Parallel KMeans algorithm on four nodes Hadoop Cluster.
Model for the evaluation of usability of scientific workflows

Scientific workflows are extensively important among scientific communities, which unified scientific data, analysis, simulation tasks to conduct any computational experiments. Existing scientific workflow systems, which consist of dozens of detailed and systematic steps, enable scientists to create and visualize scientific processes without much difficulty. Regardless of their potential for advancement in science, there are still improvement that can be made especially in unification of scientific workflow systems since different scientific communities required different notations to model. As scientific workflows evolved over time, it is also difficult for scientific communities to discover suitable scientific workflows for their task. In this research, evaluation of usability of scientific workflows is being done since it is a key characteristic of determining the success of any software system. Empirical study was applied for the usability evaluation, based on creation of questionnaire to develop survey and statistic hypotheses checking. Statistical Package for the Social Sciences (SPSS) was used to analyse the data after responses were collected. For validation of survey, the collection of data from 101 respondents of scientific community and developers of scientific workflow systems was collected then the reliability analysis (Cronbach’s Alpha), One Sample t Test, factor analysis (KMO and Bartlett’s Test), ANOVA test were used. MATLAB was use for development of coding for Cronbach’s Alpha. Results of this research, which is the proposed model of usability of scientific workflows, will help to upgrade the quality attributes in scientific workflow systems.
The Effectiveness of Edmodo and Schoology in Teaching Speaking

This study was attempted to describe the effective use of Edmodo and Schoology in teaching speaking and the students’ perception of the application practicality in the learning process. It is an experimental study. The subject of the study was eleventh-grade students of MAN N 2 Semarang. There were two groups in this study; experimental group (E) at XI IPA 3 and the control group (C) at XI IPA 5. The research instruments were tests (pre and post-test), questionnaires, and audio documentation. The t-test or value obtained was (0.325) and t result was lower than t table (1.66724). Hence, it can be said that both the learning management system (LMS) using Edmodo and Schoology had equal effects to improve students’ speaking performance. It was proved by the mean value of pre-test and post-test, in which the experimental group was 67.71 and 69.71. Meanwhile, in the control group, there were 66.53 and 68.57. Moreover, the result of the questionnaire was 3.40 for students' perception as good criteria related to the practicality in the experimental group. Then, there were 3.42 on good criteria related to the practicality in the control group. It means that the teacher can use either Edmodo or Schoology LMS system in teaching speaking to achieve students’ speaking performance, particularly on pronunciation and grammar. In conclusion, Edmodo and Schoology are effective to teach speaking in eleventh graders.
Pengaruh Media Kartu Bergambar Berbasis Model Discovey Learning Terhadap Motivasi Belajar Peserta Didik Materi Sistem Ekskresi di SMP Negeri 5 Pallangg

Abstract:  The purpose of this study was to determine the effect of picture card media based on the Discovery Learning model on students' motivation in excretory system material at Pallangga 5 Middle School. The study was a quasi experimental (quasy experimental) namely nonequivalent control group design. The research sample of this study was the  VIII grade students of Pallangga 5 Junior High School in class VIII.F (experimental class) and VIII.G (control class) with a total of 60 people. This research was conducted in the even semester of the school year 2018/1019. The variables of this study consisted of independent variables namely pictorial card media based on Discovery Learning models and the dependent variable was learning. Data collection techniques are learning motivation questionnaires. the data were analyzed descriptively and inferentially. The results of this study indicate that illustrated card media based on the Discovery Learning model (experimental class) is effectively used to increase student motivation and learning outcomes compared to conventional learning models (control class). Learning motivation towards picture card media based on Discovery Learning model 83,33% is in the very high category, 16,67% in the high category, and 6.67% so there are no more students in the sufficient category, low and very low categories.  Keywords: learning motivation, picture card media, discovery learning
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IMU BASED SMARTPHONE CONTROLLED HUMAN FOLLOWING ROBOT WITH FALL DETECTION

The advancement in robotic technology has improved drastically in the past decade, from load carrying to assembling of huge aircrafts has made it easier and has reduced human labour.Furthermore, with technologies like Artificial Intelligence and Machine Learning becoming pervasive robots are tending to grow smarter.Human following robots employing RFID and vision techniques like camera and laser are current trend in the market.But they all are mainly based on line of sight which implies that it cannot reacquire the target when lost.In this paper, a novel method is employed to obtain the human following feature using Inertial Measurement Unit (IMU).Unlike the former techniques, using IMU would not pose any shortcomings of losing the target.The most important feature needed is the ability for the robot to follow that particular person.The application called the Hyper IMU is utilised to convert a regular Smartphone into a powerful IMU device.The availability of the sensors which are already embedded in the Smartphone these days is highly advantageous for the implementation of human following robot.The robot tracks the movement of the human and heads in the same direction as guided by the sensors.The implementation of ultrasonic sensor is to obtain obstacle detection which can avoid damages to the robot in case of its absence.
Effectiveness Evaluation of Deep Features for Image Reconstruction from fMRI Signals

Reconstruction of human cognitive contents based on analyzing of functional Magnetic Resonance Imaging (fMRI) signals has been actively researched. Cognitive contents such as seen images can be reconstructed by estimating the relation between fMRI signals and deep neural network (DNN) features extracted from seen images. In order to reconstruct seen images with high accuracy, translation fMRI signals into meaningful features is an important task. In this paper, we validate the reconstruction accuracy of seen images by using visual features with some DNN feature extraction models. Recent works for image reconstruction used VGG19 to extract visual features. However, newer models such as Inception-v3 and ResNet50 have been proposed and these models perform general object recognition with higher accuracy. Thus it is expected the accuracy of image reconstruction is improved when using features extracted by these newer models. Experimental results for images of five categories show the effectiveness of the use of visual features from newer DNN models.
LibGuides: A Guide for Reader's Advisory and Collection Development: Webinars

This LibGuide offers an array of websites, webinars, articles, and blogs providing helpful information to help staff members in their interactions with patrons.
Нейросетевой метод классификации текстов групп социальной сети Вконтакте

Classification of text data using neural networks is used in numerous projects. Different structures of artificial neural networks with varying parameters can be used. This article describes the process of creating and training a neural network aimed at the classification of records from the social network Vkontakte. The aim of the work is to check the applicability of neural networks to solve the problem. Tensorflow package was used as a software tool to create a neural network. Data for neural network training are obtained from the records of groups with specific topics (biology, information technology, cinema). The algorithm of automatic of Vkontakte groups texts, tested in the study, will be used in the development of the content component of the functional psychometric model of cognitive – behavioral predictors of personal activity in the framework of its educational activities.
The life of Zaha Hadid

A PowerPoint presentation accompanying the talk given at the CPBRA CCCU conference on 29.05.2019. The music file is also provided separately. It consists of a first significant foray into the realm of electronic music and depicts five areas of Zahah Hadid's life, Suprematism, fluidity, organicism, topography and parametricism, also her imagination, her interest in all things new and her sudden death in 2016.
Applying ANFIS Inverse Control Approach for Level Control Reactor in a Urea Fertilizer Plant

The Reactor Unit in the Urea fertilizer plant is one of the units that functions to react to the components forming the Urea fertilizer, so that this unit is one of the most important systems. During the operation of this unit, the fluid height of the liquid inside the reactor will be kept stable so that the reaction in the reactor can react perfectly according to the product specifications. Therefore we need a model that can describe the behavior of the reactor so that the level of the liquid in the reactor can be maintained. In this research, a model for reactor units will be developed at the Urea plant using the Adaptive Neuro Fuzzy Inference System (ANFIS) method using real-time operational data collected. This level control of reactor is maintained steady by level controller designed using inverse dynamics based on ANFIS. Results of simulation study demonstrate how the designed control technique performs well in tracking set-point. Performance comparison is also made between the designed and PI controllers
목표원가, 개발일정 관리가 신제품 매출에 미치는 영향: 품질목표 달성도의 매개적 역할

This study analyzes the effects of managing target cost and development time for a new product on achieving target quality level, which should be simultaneously considered in New Product Development(NPD) processes, and on sales weights of selling new products which is one of the NPD performances through the mediating role of achieving target quality level. Besides, we also explored whether R&D resource input intensity as moderating effect influences the effects of managing target cost and development time on achieving target quality level.As the results of this study, from the perspective of small and medium sized manufacturers and the first tier suppliers who play a leading role in customer and market change by developing new products before their competitors for the main products, we could empirically identify that the management of target costs and development time showed positive(+) influences on achieving the target quality level of new products. Furthermore, as a result of empirically examining the mediating role of achieving target quality level in order to specifically understand the relationships between the management of target cost along with development time and the sales weight of new products, it has a partially mediating role in the relation between the management for target cost and the sales weight, and it has fully mediating role in the relation between the management of development time and the sales weight. Finally, we found that there is no moderating effect in the positive influences of target cost management on achieving the target quality level as the size of the R&D resources increases.
LibGuides: 53rd Annual CBHL 2021 Meeting: Registration

Program and schedule the 53rd meeting of the Council on Botanical and Horticultural Libraries in Washington D.C., May 5-7, 2021
Penerapan Artificial Intelligence (AI) Pada Sistem Informasi Optimasi Jadwal Kuliah Menggunakan Algoritma Genetika

Scheduling lectures is one important aspect to support the implementation of lectures. With the scheduling of lectures, lecture time can be arranged, so that the room can be used effectively. To arrange lecture scheduling, it is of course needed the right way so that arranging the lecture schedules becomes easier and faster. At the College of XXXX, lecture schedules is still done in the conventional way that is arranging the schedule manually using Microsoft Excel software so that it takes a long time in preparing the scheduling of lectures. To simplify and accelerate the process of preparing lecture schedules optimally, the Lecture Scheduling Information System is one of the right solutions. Genetic Algorithm is one way to make logical and systematic steps so that the Information System Scheduling lectures can provide solutions that are easy, faster and more optimal. The genetic algorithm is one of the advances in the field of information technology in the field of Artificial Intelligence (AI) that can solve optimization problems. So that the process of making a schedule using genetic algorithms prepares lecture schedules faster, more precise and optimal. The results obtained from the modeling of genetic algorithms in the lecture schedules system include reguler morning class schedules, reguler evening class schedules, and extention class schedules in all majors at XXXX Higher Education.