Reviewerly/exHarmony huggingface dataset:
A Robust Representation with Pre-trained Start and End Characters Vectors for Noisy Word Recognition

Powered by the advanced neural network, many tasks in the field of natural language processing could be completed by the network models. As the noise in the input text can affect negatively on the performance of these model, researchers are gradually paying more attention to the word recognition, which is placed before the downstream task to accomplish those tasks better. Text noise, in terms of words, usually includes random insertion, deletion, swapping, or keyboard errors. They belongs to the category of Out-of-vocabulary (OOV) in the word-level language model. Using a vector to represent all OOV words is the most common technique. However, such a representation may cause information loss as it overlooks the meaning of the word. In this paper, we propose a reasonable and effective representation method for the noisy words identifying, based on the semantic correlation and dependency of words. When modeling character level dependency, we imitate the process of human recognizing noisy words, paying more attention to the start and end characters while ignoring the order of internal characters. To get a better embedding representation of noisy words, we train a neural network to predict the start and end characters, and then combine the predicted start and end character vectors with other character vectors into the whole word representation. Empirical results on the publicly available Penn Treebank datasets have shown that our proposed noisy word representation improves the accuracy of word recognition.
Cloud Native Development Best Practices

From the previous chapters, you amassed a good amount of knowledge on how to use Serverless technology. The current chapter will give you practical tips on how to adjust your development strategies to deal with the limits imposed by Apache OpenWhisk services or the vendors offering you Cloud-based OpenWhisk, like IBM Cloud Functions.
China’s Institutionalized ‘May 4th Day’ and the ‘New May 4th Movement’ in the 1950s

초록·키워드 목차 오류제보하기 In this paper I looked at how the ‘May 4th Day’ executed in the 1950"s after the founding of the People"s Republic of China. In December 1949, the ‘May 4th’ was officially established as a national memory day. It happened 30 years after the May 4th Movement. In addition, guidelines for national supervision of the ‘May 4th Day’ have been issued almost every year. It specifically supported the institutionalized ‘May 4th Day.’ Since then, Youth Day has held a grand celebration every 10 years, in the middle, the celebrations were relatively small each year. This pattern has been established and continues to this day. This has changed considerably compared to the period of the Republic of China. At that time, the activities of the ‘May 4th Day’ were largely suppressed, but it was not until the establishment of the People"s Republic of China that the ‘May 4th Day’ was institutionalized and organized by state power. Based on the institutionalization as above, the activities of the ‘May 4th Day’ were carried out regularly throughout the 1950s. A striking feature of the ‘May 4th Day’ in the 1950s is that political messages have been strongly transmitted from above to the ‘May 4th Day’ every year. Every year, major events or pending issues have been featured in the ‘May 4th Day’ as a political message. The political message above was not related to the May 4th Movement or the student class. So I will call this feature ‘the politicization of the May 4th Day given from above.’ In reality, however, there was a certain difference between the political power and the masses of students in recognizing the important values of the May 4th, such as democracy and science, freedom and equality. This was evident in the ‘May 19th Movement’ which were initiated by students at Beijing University during the ‘Hundred Flowers Campaign’ in 1957 and the ‘Anti-Rightist Campaign’ suppressed it. In the end, students" demands for ‘true socialism’ or ‘socialist democracy’ are soon suppressed by Anti-Rightist Campaign. This leads to ‘extreme left conservatism’ such as the Great Leap Forward and the Cultural Revolution. The ‘socialist democracy’ that students claimed in 1957 is an ideological legacy to be restored and referenced for political reform in China. It is also an ideological legacy that we should not be wiped out. Now remembering and restoring the ideological legacy of 1957 is very important for the commemoration of ‘May 4th.’ #중화인민공화국 #중국공산당 #‘5·4 기념’ #5·4운동 #5·19운동 #‘백화제방 백강쟁명’ #정풍운동 #반우파투쟁 #中华人民共和国 #中国共产党 #‘五四’纪念’ #五四运动 #五·一九运动 #‘百花齐放百家争鸣’整风运动 #反右派斗争 #People"s Republic of China #Communist Party of China #‘May 4th Day’ #May 4th Movement #May 19th Movement #Hundred Flowers Campaign #Anti-Rightist Campaign Ⅰ. 머리말Ⅱ. ‘오사기념’의 제도화와 정치화 : ‘오사기념’의 연대기Ⅲ. ‘新5·4운동’과 ‘사회주의 민주’ : 또 하나의 ‘오사기념’Ⅳ. 맺음말참고문헌Abstract
LibGuides: Online resources and support: Communicate and collaborate

A guide to help you with basic and more advanced digital skills for university learning How to use Zoom and Office 365 apps
LibGuides: Library Events: Zen Activities

Want to know what is going on at the Library? Check out all of our past and upcoming events here! Need to move around or just do you need to give your brain a total break? Yoga or meditation will help with that. Or do you need some background music that isn't going to distract you from your studies? Something that will help you concentrate?
VIRTUAL EDUCATION – THE STRATEGIC DIRECTION IN THE XXI CENTURY

Considering the new sense and objectives of virtual education with the common indications, the essence of such principles is considered, such as: navigation, creative convergence, communicative development, ethical reflection, integrating of experience.
Adaptive Retraining of Visual Recognition-Model in Human Activity Recognition by Collaborative Humanoid Robots

We present a vision-based activity recognition system for centrally connected humanoid robots. The robots interact with several human participants who have varying behavioral styles and inter-activity-variability. A cloud server provides and updates the recognition model in all robots. The server continuously fetches the new activity videos recorded by the robots. It also fetches corresponding results and ground-truths provided by the human interacting with the robot. A decision on when to retrain the recognition model is made by an evolving performance-based logic. In the current article, we present the aforementioned adaptive recognition system with special emphasis on the partitioning logic employed for the division of new videos in training, cross-validation, and test groups of the next retraining instance. The distinct operating logic is based on class-wise recognition inaccuracies of the existing model. We compare this approach to a probabilistic partitioning approach in which the videos are partitioned with no performance considerations.
Navigation Strategies for Improved Positioning of Autonomous Vehicles

This report proposes three algorithms using model predictive control (MPC) in order to improve the positioning accuracy of an unmanned vehicle. The developed algorithms succeed in reducing the unce ...
Extraposition from NP in English

The impact of phonology on word order phenomena has become a central research agenda ever since the Minimalist Program emphasised the role of interface conditions on syntactic operations. This book is a detailed study of extraposition from NP, which has traditionally been the domain of syntactic investigation and information-structural studies. After an examination of syntactic accounts of PP and relative clause extraposition, which are largely found inadequate, it explores the possibility of phonological solutions by comparing the prosodic structure of canonical and extraposed word orders. Particular attention is payed to the informational status of extraposed constituents and the focus structure of the sentence. The book shows that extraposition optimises the prosodic structure of sentences and in some cases their rhythmic structure, while focus structure only plays a role in extraposition of defocused constituents. The book further argues that extraposition occurs at PF, while certain binding-theoretical consequences of extraposition can be resolved by LF movement. With its focus on the interface between syntax and phonology, the book will appeal to researchers working on either domain.
Research Guides: Using the CSULB Library: Videos by Dr. P.: Library Overview

A series of videos that explain the Steps to Research Handout and other research & library support. And overall view of how the online library works.
On the talent cultivation path of surveying and mapping major in university

Surveying and mapping engineering; Modern mapping; Cultivation of talents
The Complete iOS App Using Serverless Swift

In this chapter, you will be introduced to typical development strategies using Serverless Swift in an iOS app. You will build a basic AI powered app and then leverage the Serverless backend for Cloud-based functionality. The Serverless actions will be responsible for analyzing the Hacker News articles with the AI service – Watson Natural Language Understanding (NLU) in order to detect keywords, entities, and categories in the article.
Change and Crisis: An Empirical Analysis of Effect of the Change of Local Government Leader on the Policy Process

The purpose of this paper is to examine how the change of the local government leader affects the policy process. This research was performed based on empirical analysis through theoretical research and questionnaire survey. The main research results are as follows. First, the change of local government leaders has a profound effect on the policy process. Second, the more frequently the local government leader was changed, the more the government officials policy changes appeared. Third, the change in policy due to the change of the local government leader was felt stronger as the official level of the official was higher and the education level of the official was higher. Fourth, the more frequent the change of local government leaders, the more cases of major policy changes.
LibGuides: RLB Library Resources & Services: Online services for students

Information about the RLB Llibrary resources and services available to UB students, faculty and staff
ENHANCEMENT OF DECISION TREE METHOD BASED ON HIERARCHICAL CLUSTERING AND DISPERSION RATIO

The classification process using a decision tree is a classification method that has a feature selection process. Decision tree classifications using information gain have a disadvantage when the dataset has unique attributes for each imbalanced class record and distribution. The data used for decision tree classification has 2 types, numerical and nominal. The numerical data type is carried out a discretization process so that it gets data intervals. Weaknesses in the information gain method can be reduced by using a dispersion ratio method that does not depend on the class distribution, but on the frequency distribution. Numeric type data will be dis-criticized using the hierarchical clustering method to obtain a balanced data cluster. The data used in this study were taken from the UCI machine learning repository, which has two types of numeric and nominal data. There are two stages in this research namely, first the numeric type data will be discretized using hierarchical clustering with 3 methods, namely single link, complete link, and average link. Second, the results of discretization will be merged again then the formation of trees with splitting attributes using dispersion ratio and evaluated with cross-validation k-fold 7. The results obtained show that the discretization of data with hierarchical clustering can increase predictions by 14.6% compared with data without discretization. The attribute splitting process with the dispersion ratio of the data resulting from the discretization of hierarchical clustering can increase the prediction by 6.51%.
Enhancing decision tree accuracy and compactness with improved categorical split and sampling techniques

Decision tree is one of the most popular algorithms in the domain of explainable AI. From its structure, it is simple to induce a set of decision rules which are totally understandable for a human. ...
The Strategies to Translate the Sentences from English into Indonesian

The aims of the research is how to translate the English sentence into the Indonesian sentence using the translate model of the sentence with the approach of the systematic approach of functional linguistics. To produce the qualified translation which covers the accuracy, acceptability and readability. To achieve the qualified translation, the translation process involves the model which consists of input (an English sentence), the process consists of equivalence and translation techniques, the output consists of the Indonesian sentence, the outcomes consists of acceptability and readability of the translation.  The English sentence is divided into: (1) subject, (2) finite, (3) predicator, (4) complement and (5) adjunct. Then the process of translation is done which involves the analysis of equivalences and translation techniques. The output is an accurate translation. The translation is accepted by the readers, and the translation is easily understood by the readers
Visual Designing and Debugging of Deterministic Finite-State Machines in FSM

This article presents a visualization tool for designing and debugging deterministic finite-state machines in FSM-a domain specific language for the automata theory classroom.Like other automata visualization tools, users can edit machines and observe their execution, given some input.Unlike other automata visualization tools, the user is not burdened nor distracted with rendering a machine as a graph.Furthermore, emphasis is placed on the design of machines and this article presents a novel design recipe for deterministic finite-state machines.In support of the design process, the visualization tool allows for each state to be associated with an invariant predicate.During machine execution, the visualization tool indicates if the proposed invariant holds or does not hold after each transition.In this manner, students can validate and debug their machines before attempting to prove partial correctness or submitting for grading.In addition, any machine edited with the visualization tool can be rendered as executable code.The interface of the visualization tool along with extended examples of its use are presented.
Implications of quantum optics in high harmonic generation

Effects of extreme nonlinear optics, such as high harmonic generation (HHG), are conventionally modeled with classical electromagnetic fields: both the driving and emitted fields are treated classically. We present the fully quantum electrodynamical theory of extreme nonlinear optics and use it to predict new quantum effects in HHG. The quantum description shows new effects in both the spectral and statistical properties of HHG. We also describe how the HHG process changes in the single-atom regime and discuss experiments that can test our various predictions. Revealing the quantum-optical nature of HHG could lead to novel sources of attosecond light having intrinsically quantum statistics, such as squeezing and entanglement.
Spatial Constrained K-Means for Image Segmentation

In this paper, we propose a novel spatial constrained clustering method, it is simple yet very effective, which has been validated it for image segmentation. The key observation of our model is that traditional K-Means clustering is popular for segmentation but it lacks effective spatial constraint. To address this issue, a general spatial constrained K-Means clustering framework is proposed and shows its effectiveness in image segmentation. Spatial constraints are expressed by points on adjacent positions, which cannot be segmented only by color gaps. With the expectation maximization algorithm, our method could be efficiently optimized, and a locally optimal solution could be guaranteed. Experiments on the Berkeley image segmentation dataset show that our method outperforms compared methods.
How To Get The Best Out Of Deep Tone Face Yoga

What is Face Yoga? The anti-aging industry at present is worth around 50.2 billion dollars. People try many different methods to look younger like ...
A lot of time the @microsoftteams assignment ...

A lot of time the @microsoftteams assignment tab doesn't even load and I have to shut down and relaunch the app...Maybe @microsoftteams isn't
Oversampling Based on k-NN and GAN for Effective Classification of Class Imbalance Dataset

Class imbalanced dataset is common in real world and may degrade the performance of the classifier. To address this, oversampling method that artificially creates the samples of minority class is adopted but is known to be ineffective for the high-dimensional dataset because it generates the samples whose distribution is far different from that of existing samples. Novel oversampling methods based on the generative adversarial networks (GAN) have been recently developed, but generated samples may have different degrees of impact on the performance of the classifier. Therefore, more efficient method that can capture the characteristics of the generated samples and select those samples that will be used to train and improve the performance of the classifier is necessary. This study proposes a GAN-based new oversampling method which generates artificial samples based on the distribution of existing minority class samples and extracts only those which are effective to expand the realm of samples of minority class using the k-nearest neighbor. We show the proposed method outperforms existing methods with respect to F1-measure by several illustrative datasets.
LibGuides: Databases and E-books: Citing Sources

A listing of online databases and information about how to use our e-book collection Learn basic citation methods
Apache OpenWhisk Deep Dive

This chapter introduces main development concepts of Serverless technology with Apache OpenWhisk. After completing it, you will have a good notion of various techniques being used in building Serverless applications. You will find more details on functions, rules, triggers, event providers, iOS SDK, entities, namespaces, permissions, and sequences that are ready for you in IBM Cloud Functions – the managed Apache OpenWhisk platform.
LIDAR A*, An Online Visibility-Based Decomposition and Search Approach for Real-time Autonomous Vehicle Motion Planning

Author(s): Wang, Po-Jen | Advisor(s): Manduchi, Roberto | Abstract: Motion planning is the task of finding a sequence of feasible motions for a robot to transform from an initial state to a goal state avoiding collisions. Modern motion planner algorithms for non-holonomic vehicles typically rely on graph search or sampling-based techniques. However, graph search methods quickly become ineffective as the computational complexity scale exponentially to map size. Sampling-based methods have the shortcomings of creating highly suboptimal paths or having high run-times. This thesis introduces a new hierarchical motion planner, LIDAR A*, that features an online visibility-based decomposition and search process. It incrementally analyzes regional maps with locally simulated 2D LIDAR scans to search for the shortest opening gateway sequence toward the goal. These sequential gateways are used to guide the simulation of a robust local motion planner to generate a smooth and kinematic friendly path. Experiments show this method significantly reduces the number of nodes minimizing computation time while generating a near-optimal path compared to the recently proposed RRT-based algorithms.
LibGuides: Social Media in the Classroom: Social Media in the Classroom

This guide is meant to aid teachers in many ways social media can be used within the classroom setting.
MODIFIED GENETIC PROJECT PLANNING ALGORITHM IMPLEMENTED WITH THE USE OF CLOUD COMPUTING

The paper proposes a structure of a modified genetic algorithm for solving resource constrainedproject scheduling problem implemented with the use of cloud computing, a computationalexperiment was conducted, during which the results of the proposed algorithm were comparedwith the best known, at the moment, results. Based on the results of the experiment, it was concludedthat the proposed algorithm can be used to plan the work of real projects, since it is possibleto draw up schedules for projects with the number of works n = 90 for an acceptable period oftime. When planning projects with the number of jobs n = 30, n = 60, n = 90, 120, the executiontime of the proposed algorithm was less than the execution time of the standard genetic algorithmby 2.8, 4, 5.5 and 6.8 times, respectively. Due to the fact that the task of constructing a projectschedule taking into account limited resources is NP-difficult, the problem of creating new andmodifying existing methods for solving it remains relevant. For planning projects with a largenumber of works, it is advisable to use cloud computing, since planning such projects can requirea lot of time and computing resources. In this regard, the algorithm proposed in this paper differsfrom the existing ones by using cloud computing to distribute the load between workstations onwhich this algorithm is simultaneously running. The use of modified operators in the genetic algorithm,as well as the use of cloud infrastructure as a service for implementing a distributed geneticalgorithm, determines the scientific novelty of the study.
LibGuides: Library Events: Reviews

Want to know what is going on at the Library? Check out all of our past and upcoming events here! Let us know what you think of our recommendations
LibGuides: Library Events: Safety and Protection

Want to know what is going on at the Library? Check out all of our past and upcoming events here!
Video Action Recognition

Our brain is a superfast action recognition system that’s hard to match. In terms of deep learning, our brain routinely does many things to recognize actions, and it works fast! In this chapter we cover practical methods and tools for video action recognition and classification. We discuss data structures for loading, normalizing, and storing videos; datasets for sport action classification, such as Kinetics; and deep learning models. Using readily available pretrained models, we can classify hundreds of sport actions and train the models to recognize new activities. For a sport data scientist, this chapter provides practical examples for deep learning, movement analysis, and action recognition for video.
Actors in the Serverless Space

It wouldn’t be fair to just jump ahead and start the discussion of Apache OpenWhisk without providing some information about the Serverless technology vendor landscape. This chapter will therefore focus on providing an introduction to the Serverless space, as well as providing arguments for using one or the other Serverless platforms. At the moment of writing, only Apache OpenWhisk supports the Swift language; thus, only IBM Cloud with IBM Cloud Functions is described in the following chapters.