Reviewerly/exHarmony huggingface dataset:
An Interactive System for Motor and Cognitive Assisted Activities

In this paper we present a hardware-software system for the administration of motor and cognitive exercises to people affected by mild or moderate cognitive impairment. This system was built in the framework of the Intesa project, funded by the Tuscany region.
A Quantile K-means Bayes Approach to Classification for Imbalanced Data

Abstract This paper focuses on the classification of imbalance data. In Machine Learning, a data set is imbalanced when the class proportions are highly skewed. A natural way of handling imbalanced data is to attempt to equalise the class frequencies and train the classifier of choice on balanced data. A new approach called Quantile K-means Bayes was proposed to solve the problem. The first focus is on a modified q-classifier. The second focus is on combine the k-means and Bayes algorithm using the data density. The proposed approach is evaluated by 101 benchmark data sets from KEEL collection. A comparison of the proposed approach and other conventional approaches is presented in terms of the G-mean. It can be seen that the proposed approach is able to acquire good performance among the other conventional approaches do. Therefore, this novel approach is an added value for the classification problem for imbalance data.
LibGuides: Resources for Linguistic Minority Community Members: Language

One of the objectives of the library is to provide a broad range of materials to accommodate the diversity of the community the library serves.
A Slice-based Character Recognition Technique for Handwritten Devanagari Script

The conventional Character Recognition for English character has been widely analyzed in the last few decades and now highly advanced for creating different technology driven applications. Indian languages which are relatively complicated in terms of geometrical shape are far behind from this perspective. Government office, library, bank and publishing houses now prefer digital document processing to make their services fast and economical. Devanagari is the official script (Hindi language) of India, and spoken by major population of the country. Many researchers have shown interest mainly on recognition of digitally printed Devanagari character. However, very little work has been done in the area of handwritten Devanagari character recognition. Therefore, there is a need to focus in this handwritten Devanagari character recognition as it will help in solving many real life problems like bank check processing, post offices and government offices in India where most of the applications and documents are written in Devanagari characters. In this paper, we have suggested a handwritten Devanagari character recognition method using the topological and geometrical features of the character. First, we cut the characters into slices and then with the help of a slice or a set of slices a feature set is formed to uniquely identify a character. The experimental result shows that the proposed method provides more than 82% accuracy which is quite better than many existing methods.
MODEL DESIGN FLOWMAP LABORATORIUM DI RUMAH SAKIT IBU DAN ANAK DENGAN INFORMASI KELAS PERAWATAN PASIEN ANAK

Maternal and child hospitals are a health service facility that is specifically intended to serve maternal examinations during the pre-pregnancy to post-partum period and all health problems for infants and children. The hospital also provides support services, namely laboratories. In the laboratory there is a flowmap as a picture of the SOP that has been determined to design HCI. The design of laboratory HCI (Human Computerized Interface) is implemented and analyzed in order to facilitate the performance of medical personnel and patients while in the Maternal and Child Hospital Laboratory. The use of the interface model begins with the design of the laboratory flowmap. Flowmap is used as a basic reference in the preparation of interfaces. The column in flowmap is divided into the following sections; [1] Registration, [2] Patient Data Input [3] Laboratory Officers and [4] Examination Results. The columns are then implemented in interface forms. Interface [1] Patient Data Input, beginning when the patient is about to go to the laboratory. [2] Payment Input, used together when the patient registers at the beginning. The next interface is the interface used for the results of laboratory tests, consisting of [3] Inputs of Stool Examination Results, [4] Input of Blood Chemistry Examination Results, [5] Input of Urine Test Results, [6] Input of Immunology and Serology Results, [7] Input of Blood Examination Results, [8] Input of Morphological Examination Results, [9] Input of Pleural Fluid Examination Results, [10] Input of Results of Examination of Blood Gas Analysis, [11] Input of Sperm Examination Results. The results of the patient examination in the laboratory are then put together in the interface column of the Patient Examination Results. The laboratory officer then fills out the Laboratory Patient Visit Report. With the presence of HCI (Human Computerized Interface) workers in the laboratory can input data from patient examination results more easily and efficiently. Keywords : Mother and child hospital, flowmap, HCI
STUDI KOMPARASI ALGORITMA DECESION TREE (C4.5) DENGAN ALGORITMA K-NN DALAM MEMPREDIKSI KELULUSAN TEPAT WAKTU MAHASISWA

The purpose of this study is to study which is better between the Decision Tree (C4.5) Algorithm and the k-Nearest Neighbor (k-NN) algorithm based on Particle Swarm Optimization (PSO) based on an assessment of its accuracy on passing the right delivery time. The results showed the closest k-Neighbor (k-NN) algorithm based on PSO at k-optimum = 19 had better results than the Decesion Tree (C4.5) algorithm, with an Accuracy value of 76.69% for the k- algorithm NN and 69.82% for the Decesion Tree Algorithm (C4.5). Increasing the accuracy value of the k-NN algorithm (6.88%) is greater than the Decesion Tree Algorithm (5.80%). Semester Achievement Index Attribute (IPS) 6 has the highest weighting value with the Decesion Tree Algorithm (C4.5) and the k-NN Algorithm. The Age attribute has a weighting value of 0,000 meaning it does not make a real contribution to the right graduation of student time. Keywords: Accuracy, Algorithm, Decision Tree (C4.5), k-Nearest Neighbor (k-NN), Particle Swarm Optimization (PSO)
A Study on the Effect of Irrelevant Attribute with Self-Construal on Product Attitude in Single Mode

This study was conducted to investigate whether the effect of irrelevant attribute in the single mode varies depending on the disclosure of irrelevance of product benefits(experiment 1) and the propensity of self-construal(experiment 2). The results of the analysis showed that first, attractive irrelevant attribute had a positive effect on the product attitude even in a single mode, while the effect of irrelevant attribute disappeared when the irrelevance of the attribute was disclosed without providing contextual variables or inferential clues such as choice set. Second, the product attitude varied according to the propensity of self-construal when the irrelevance of product benefit was disclosed. In other words, when the irrelevance of the attribute was revealed, the product attitude for independent self-construal person was significantly lower than before the disclosure, as in experiment 1, while the product attitude for interdependent self-construal person was not significantly changed either before and after the disclosure.
LibGuides: Online Resources For Music Study: Find Dissertations Online

Subscription and open-access content for the study of both applied and academic music studies. Sources of Dissertations available online (not specifically music)
An architectural proposal for the interactive publication of the data classification obtained through a Differentially Private Random Decision Forest

Data are generated in several contexts, by various devices, and are collected by organizations whose aims to obtain as much information as possible to add value to their business. There are plenty of ethical and non-ethical purposes involved such as identifying consumers' needs and then recommend products and services, developing new business, conducting health-related research in order to reduce medical errors, assessing risk of people developing diseases, so on. The organizations' concerns about risks associated to potential privacy leaks and their impacts have increased dramatically. Thus, apply data mining in process optimization without compromising sensitive data and provide a strong privacy standard are challenges imposed to data stewards, who use techniques and privacy models during data release process. This study aims to propose a classification decision tree application, developed under the Differential Privacy model definition, whose architecture was designed according to the interactive data release model that deploys a barrier to forbid users to have access data in their raw format. In addition, a self-tuning feature that controls the forest growth was put in place, resulting in a better classification performance if compared to the adoption of a fixed amount of trees in the forest. However, there was an increase in processing time. It also was observed in most of the datasets used in the experiment that beyond a threshold the classification performance is reduced by increasing the number of trees that compose the forest.
LibGuides: Toxins Project: Open

Resources for teachers leading the Toxins Project Resources to grab all students' attention
Self-Learning Based Cognitive Reading and Character Recognition in Image Processing Techniques

There are many techniques involved in Handwritten character recognition and many of the methods uses common process like pre-processing, segmentation, stroke identification and character interpretation. But the technique applied for these steps differ from different implementation. Building the training data is a tedious task but it is more important as the success of entire recognition system lies on the amount of training the neural network and building the knowledge base. Hence this is an important task and it is costly due to amount of time and resource used for training the dataset. This article explains some of the methods in Cognitive reading in image processing for character recognition and introduces a self-learning based training system which provides improved method in less time/resource consuming in automatically training the knowledge base.
LibGuides: RPGs: More RPGs

This libguide is dedicated to tabletop roleplaying games. It is meant to be a resource for new players and existing players.
Penentuan Prioritas Penerima Dana Bantuan Operasional Pendidikan Lembaga Pendidikan Anak Usia Dini dengan Metode KNN, TOPSIS dan K-Means

Education Operational Aid of the Early Childhood Education unit is the financial assistance which is provided to educational institutions, especially for those who engaged in non-formal education, which is used for the process of education in the curriculum of educational institutions in order to give the appropriate and adequate education for students. However, the reality has stated that there is a lot of financial irregularity and inaccuracy of data in the disbursement of the fund of education operational aidat the institute units of Early Childhood Education. On the other hand, there are many complaints that come from the institution itself due to the inaccuracy of data. This research was conducted by applying the KNN, K-Meansalgorithmand TOPSISmethods. The results of the experiment will be tested with two methods that is using cluster distance performance and K-Means cluster count performance. Meanwhile, to measure the level of ranking of TOPSIS method,the experiment will use the percentage calculation method between the experimental data with the implementation of the data to determine the accuracy of TOPSISmethods.
LibGuides: Continuity of Horn Library Services - Spring 2020 Semester: Instructor Resources

Iinformation related to Horn Library's current operations, access to remote services, and other helpful tips
The Effectiveness of Synthetic Phonics in Developing Reading Fluency among Year 2 Intermediate Pupils

Reading skill is an essential skill that is taught in every language subject in schools.Its importance is irrefutable as it relates closely to the pupils' academic and future success.Today, many Malaysian pupils are still struggling hard to read with fluency and understanding.It is noticed that educators in schools have been giving limited attention on reading fluency since reading comprehension is the ultimate goal in reading development.Researches show that mastery of reading fluency is required for comprehension to take place subsequently.Therefore, this action research aims to examine the effectiveness of synthetic phonics in developing the reading fluency of the Year 2 intermediate pupils in a sub-urban school in Dalat, Sarawak and their perception towards the intervention.Six pupils were involved in this research.Data were collected through pre-post-tests, classroom observation and structured interviews.Paired T-tests were conducted to determine the significant difference between pre-test and post-test scores of ORF assessments which were analysed in mean, standard deviation and p-value whereas classroom observation and structured interviews were analysed through content analysis.The findings indicated that pupils had improved in their reading fluency after the intervention and had positive perceptions towards the intervention.For further research, more sampling is recommended to generalise the findings.
Discretized Bottleneck in VAE: Posterior-Collapse-Free Sequence-to-Sequence Learning

Variational autoencoders (VAEs) are important tools in end-to-end representation learning. VAEs can capture complex data distributions and have been applied extensively in many natural-language-processing (NLP) tasks. However, a common pitfall in sequence-to-sequence learning with VAEs is the posterior-collapse issue in latent space, wherein the model tends to ignore latent variables when a strong auto-regressive decoder is implemented. In this paper, we propose a principled approach to eliminate this issue by applying a discretized bottleneck in the latent space. Specifically, we impose a shared discrete latent space where each input is learned to choose a combination of shared latent atoms as its latent representation. Compared with VAEs employing continuous latent variables, our model endows more promising capability in modeling underlying semantics of discrete sequences and can thus provide more interpretative latent structures. Empirically, we demonstrate the efficiency and effectiveness of our model on a broad range of tasks, including language modeling, unaligned text style transfer, dialog response generation, and neural machine translation.
THE ROLES OF NON-NATIVE PARENTS AND FIRST LANGUAGE (L1) IN THE ACQUISITION OF ENGLISH AS A SECOND LANGUAGE (L2)

This paper provides different perspectives and evidence on how interactions to non-native parents would influence the language development of child L2 learners of English. The discussion itself is an extension of recent debates of a relevant issue with supports from research data obtained in a project that longitudinally explores the naturalistic acquisition of the second language by Indonesian child L2 learners of English in England. Two different types of main data are involved in the study; a comprehensive language exposure study through Utrecht Bilingual Language Exposure Calculator (UBiLEC) and a twelve-month longitudinal data collection of everyday language production. Data from UBiLEC and the entire language corpus from research participants are analyzed to reveal important information about whether parental input and L1 play any role in shaping the language development of the children. Findings from the study indicate that exposures to parent's non-native language do not necessarily accelerate or delay a child's language growth. Further, the study reflects that similar L2 errors produced by parents at home can be traced in the language production of the research participants. It was also revealed that L1 plays an important role in the production of L2 errors. Keywords: L2 Acquisition, Non-Native Input, Child L2 Learners
BU Library: BU Canvas Support & Resources: Importing & Organizing Content

We've moved to Canvas! This space offers essential updates and important information to help you learn to use it effectively. Check back for more updates. Information on Transferring & Inserting Content
One-Class Classification: for high-dimensional data

This M.Sc. thesis report investigates the application of one-class classification techniques to complex high-dimensional data. The aim of a one-class classifier is to separate target data from non-target data, but only a dataset containing target data is available for training. The issue with high-dimensional data is that it is difficult to perform density estimation due to the `curse of dimensionality'. Most conventional method for one-class classification rely on density estimation. This thesis focusses on the use of autoencoders and generative adversarial networks (GANs) for one-class classification problems involving image data. Autoencoders can learn encoding and decoding functions for samples from the target dataset. These encoding and decoding functions are, however, expected to not perform well for non-target samples, as they have never been seen during the training phase. This makes it possible to separate target and non-target data. For GANs, the discriminator is used to distinguish between target and non-target data. Autoencoders and GANs are evaluated extensively in this report. Their behavior, desired parameters and strengths and weaknesses are evaluated by performing experiments. The main findings are that GANs do not perform well for one-class classification tasks, because of mode collapse and insufficient sampling of the non-target data. Even for extremely simple datasets these issues were observed. Autoencoders are shown to perform much better and behave according to the theoretical expectations.
Experiential Learning of Networking Technologies: Evolution of Socket Programming – Part II

In our last article [1], we discussed the concept of a perpetual server handling multiple concurrent clients and explored several design/implementation choices. These included creating one child process (or thread) per client connection, pre-creating a number of children processes (and/or threads) and assigning a new TCP connection to one of the free child process/thread and a single threaded server using the socket API call select()[2][3]. We briefly discussed the latter approach using select(), in which, the process maintains a list (array) of open sockets, and each time whichever socket is active, the process uses that socket. For example, when data is available to read from the socket or the socket has enough buffer for the data to be written into, then the network stack will be transmitted subsequently. The approach of using select() performs better than other approaches of creating multiple threads/processes. As discussed in [1], one of the limitations of using select() is that it is generally limited to handling 1024 concurrent connections. This number turns out be quite insufficient today as modern servers need to deal with many more than 1024 concurrent connections [4]. There are other inefficiency issues when using select() especially on account of frequent switching between user space and kernel space execution of a process. In this article we focus on these limitations of select() and alternatives available (such as poll() [5], and epoll() [6]) to improve upon the performance.
Optimized energy and SLA-aware virtual machine placement strategies in Cloud: study

Pay-as-you-go is the latest trend for most of the business applications and to suit it precisely a process should be followed which might be the Service Level Agreement (SLA). Cloud computing requires a clear agreed SLA signed by the service consumer and committed by a service provider. The efficiency of a datacenter depends a lot on how virtual machines are provisioned and where they are located. Virtual machine placement is an optimization problem aiming for multiple goals. An efficient VM allocation policy will improve energy efficiency while limiting the degradation of the quality of service (QoS) and alleviate hotspots, but will also reduce the operating costs of the data Center. In this paper, we study strategies of optimal VM allocation policy to minimize power consumption in a data center while preserving QoS. CloudSim simulator is used to create a cloud environment. We evaluate and compare our algorithms corresponding to different approaches in order to find the one that optimizes VM placement. The simulation result shows that some virtual machine placement strategies minimize the energy consumption and SLA violations
Research Guides: Gender and Women's Studies (GWS) Portal: Home

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UJI AUTOMATIC PROCESSING DI KAMAR GELAP ATRO BALI

Automatic processing tests in ATRO Bali darkroom. Research has been conducted on Automatic processing testing use stepwedge as objects in ATRO Bali darkroom. This study aim to determine the performance of automatic processing tools in ATRO BALI dark rooms and their suitability with the Minister of Health Decree No. 1250 of 2009 concerning Radiodiagnostic Quality Control. This study usesurvey approach with quantitative method on stepwedge. The research was carried out by conducting stepwedge exposures which were then washed using automatic processing tools. After the radiograph is produced, density measurements are carried out to determine the speed index, contrast index and fog index. The activity was carried out for five consecutive days. Based on automatic processing tests, the speed index results are still in accordance with the rules of the Decree of the Minister of Health No. 1250 of 2009 concerning Radiodiagnostic Quality Control on the first day to the second day, which is still less than 0.15. The index contrast is still within the standard limit of 0.15 and the second and third first day indexes are still within the standard limit below 0.25. But the fourth and fifth days have exceeded the standard limit. All of these results are caused by the malfunctioning of the bottle replenisher, the weaker the solution used.
A Study on Ontology Creation, Change Management for Web-Based Data

The research and development of artificial intelligence (AI) involve a generic representation known as ontology. Ontology is a generic representation of the domain data like medical ontology, manufacturing ontology, etc. The present work deals with the construction of the ontologies with Web pages like Naukri, Monster and Time Jobs Web sites, and the name of the ontology is job portals ontology. The reason behind the development of this work is to propose simple methods and models to create the ontology, to handle the changes happened to the source data and to apply the changes dynamically to the existing ontology. The concept of dynamic ontology creates more impact on the research of ontology models. We believe that the change management aspect is also helpful to the researchers so as to track the changes caused in the source data, in this case the Web portal data. The other dimension of the work is integration of recommender systems with ontology model so as to emit the resultant technologies which are not having sufficient resources in the job market. The proposed work involves the simple way of ontology creation, change management and dynamic ontology creation based on the changes of the source data. The outcome of the work is ontology creation, change management, dynamic ontology generation and a brief description of recommender systems usage.