Reviewerly/exHarmony huggingface dataset:
Path Planning of Industrial Wheeled Robots Based on Wireless Communication and Machine Learning Algorithms

With the advancement of science and technology, robotics has made considerable progress. Robots can free humans from heavy repetitive labor. From the industrial field to the lives of the general public, robots are playing an increasingly important role. Path planning is one of the core contents of industrial wheeled robotics and has very important significance. Based on the reinforcement Q learning and BP network, this work studies the path planning of industrial wheeled robots. According to task requirements of path planning, design learning strategies, and control rules, use wireless communication to transmit environmental perception information and propose corresponding control strategies. The main researches are as follows: (1) Based on grid map environment, a path planning algorithm with Q-CM learning is designed. The algorithm first designs robot states and actions based on reinforcement Q learning and grid map and establishes Q matrix. Secondly, a coordinate matching (CM) obstacle avoidance control rule is designed to improve the efficiency of robot avoidance. Then, a reward function is designed for the evaluation problem of action execution. (2) Based on the map environment of free space and the generalization ability of BP neural network, a robot path planning with Q-BP learning is designed. The algorithm first designs the sensor detection mechanism and action selection strategy according to the state of the robot in the map environment. Secondly, a dynamic reward function is designed. Then, according to the obstacle avoidance requirements of special obstacles, the obstacle avoidance rules after three shocks were designed. The experimental results show robots can perform better path planning in a discrete and continuous free space map, and the obstacle avoidance effect is good.
Efficient personnel training among researchers and teaching staff at the higher educational institutions of the Russian Ministry of Internal Affairs

The improvement of the post-graduate studies at the higher educational institutions of the Ministry of Internal Affairs of Russia efficiency depends on the identification of the challenges that arise in the course of personnel training and finding the possible resolution of the found issues. In order to identify the issues leading to the lack of performance of the post-graduates, who currently do not achieve a complete success in thesis defenses, the author compared and analyzed the findings from the identical surveys conducted in 2021 among the adjuncts of the Academy of Management of the Ministry of Internal Affairs and their research advisors. Some of the obtained results are compared with the similar findings acquired in the previous studies. The author used quantitative and qualitative methods to interpret and systemize the answers from the both samples and have identified four distinctive types of problems: 1) issues stemming from social and macro-scientific factors; 2) issues emerging as the part of the institutional process of personnel training; 3) problems of communication between the post-graduates and their research advisors; 4) issues caused by personal characteristics, such as the cognitive and psychological unpreparedness to conduct the research and defend the thesis. Concluding the analysis, the author offers the ways to solve the problems in the sphere of enhancing the competency of higher educational institutions of the Ministry of Internal Affairs of Russia.
Analisis Kelengkapan Pengisian Resume Medis Rawat Inap di RS Darurat Covid-19 Wisma Atlet Kemayoran

The completeness of medical records is very important to affect the process of services provided by health workers and impact on the quality of services of a hospital. Preliminary study results conducted at RSDC Wisma Atlet Kemayoran, filling out medical resume form 5 out of 10 files no signature name of medical resume form. Also found, 3 out of 10 files have no outgoing diagnostic information. The purpose of this study is to identify the completeness of the patient's identity, review of important reports, authenticity review and review of the correct completeness of the medical resume form at RSDC Wisma Atlet Kemayoran. This research is qualitative research. The study subject consisted of 2 doctors who filled out a medical resume. The object of the study was a sample of inpatient medical records from June 7-21, 2021 based on slovin formula as many as 98 files. The results of the study on the completeness of filling a medical resume seen from 4 aspects have not been high enough. Incomplete filling of medical resume forms is influenced by several factors, namely man, methode, material, and machine factors.
Software Requirements Engineer’s Ability Assessment Method Based on Empirical Software Engineering

With the expansion of the scale and complexity of modern software systems, the failure rate of software projects remains high. One of the main reasons for the failure of software projects is the defects in processing software requirements. This paper proposes a software requirements engineer’s ability assessment method based on empirical software engineering to measure the matching degree between the software requirements engineer’s ability and industry expectations. First, collect the recruitment information of software requirements engineers from mainstream recruitment websites. Through natural language processing, the words related to the abilities of the software requirements engineer are counted. These words are summarized in the requirements acquisition, requirements analysis, and other SRE activities, then the industry expectations for various abilities are obtained. Later on, the authors collect the teaching settings of representative SRE courses, reflecting the software requirements engineer’s ability to learn the course. After that, this article defines the ratio of the industry expectation weight to the weight of each SRE activity in teaching as the software requirements engineer’s ability coefficient, which can intuitively reflect the matching degree between the software requirements engineer’s ability and industry expectations. Finally, take the national first-class undergraduate course “SRE” of Jinling Institute of Technology as an example to verify the method’s practicality to a certain extent.
Unsupervised Anomaly Detection in Rotating Machinery Using Variational Autoencoder

In industrial, agricultural, and chemical plants, rotating machinery is the most regularly used and important equipment, and its troubles and failures have a significant impact on production and quality. Therefore, the development of technology for detecting abnormalities and diagnosing the soundness of rotating machinery has been an important topic of study for many years. Recently, anomaly detection using unsupervised learning methods of machine learning has been studied in various fields. In this study, we attempted to develop an unsupervised anomaly detection method that does not require damage data in advance. Using a Variational Autoencoder (VAE), which is one of the machine learning techniques, we conducted an anomaly detection experiment through vibration experiments simulating some typical damages of rotating machines and investigated whether the system can recognize situations different from normal appropriately.
Automatic Correcting Mathematics Operating System based on AI

With the development of society, the advancement of science and technology has become an important basis for whether a country is strong or not, and the development of science and technology cannot do without a solid mathematical foundation. Mathematics is the most important is to calculate, and the enhancement of computing power is to need constant practice to do the problem and correct the wrong problem, so this design of an ai-based automatic correction math homework system. The design of the system can be divided into two parts, the front user operating platform interface design and background function design. The function realization of the background can be divided into five modules, which are image recognition module, mathematical operation module, answer comparison module, data interaction module and image processing module. The image recognition module is used to recognize the text in the picture and obtain the coordinates. The mathematical operation module is used to carry on the operation to the identified problem; The answer comparison module is used to judge right and wrong; The data interaction module USES MySQL database for data interaction. Image processing module is used to identify right and wrong.
Tantangan Kurikulum 2013 Untuk Menghadapi Pembelajaran di Era Modern

The rapid advancement of data and correspondence innovation in all areas of life has marked the beginning of the 21st century. the Indonesian government for this situation continues to strive to further develop the parts of teaching at each level economically by changing the world of training improvement. One of them is to implement 21st century inventive learning structures. The type of technique used in this research is library research. This strategy limits its implementation to only using library resources to obtain research information, without directing field research, collecting library information, perusing, recording, and handling disparate data on improving education plans in Indonesia to face the demands of 21st century capabilities through various related sources. The basic standards of 21st century learning include: training must be cooperative (teaching must work together), learning must be organized (learning must have organization), guidance must be student focused (learning focused on students), schools should be included with the community (schools should be coordinated with the local area). There are two things such as two basic methodologies in the discovery of K-13 which are very closely related to the needs of the 21st century, namely demand and logical methodologies that are used as references in creating different 21st century inventive learning models.
Multiple Spatial Resolutions for Categorical Variables

Analysis at multiple spatial resolutions allows insight concerning the spatial relationship between False Alarms and Misses for a category. A coarsening algorithm converts fine-resolution observations into blocks that have a coarser spatial resolution, which can cause each block to have membership to more than one category. This chapter shows how to construct a square contingency table when a block can have membership to more than one category. Then the concepts of Chap. 4 analyze the contingency table to compute results at each resolution. The sum of Exchange and Shift shrinks as the spatial resolution grows coarser. The spatial resolutions at which these components shrink gives insight to the spatial allocation of a category’s False Alarms and Misses. Relevant software includes the CROSSTAB module in TerrSet available at https://clarklabs.org and the diffeR package available at https://cran.r-project.org/web/packages/diffeR/index.html .
Anonymity in the Age of the Internet

While in its early phases the Internet had been based on anonymous communication within virtual communities, the past two decades have brough about a reversal. The proliferation of digital networking platforms, on one hand, and loose internet privacy policies, on another, have been narrowing the space for anonymous use of the Internet. Based on these trends the paper deals with the transformation of the role of online anonymity in the socio-legal perspective. In the first part we demonstrate that anonymity accompanies the modernization of contemporary societies, but there are also various freedom and security challenges. In the second part of the paper, we analyze internet anonymity as a phenomenon, assessing both arguments in favor and against it. We are particularly interested in identification of the stakeholders who advocate overall deanonymization, as one of the crucial characteristics of public and private life in contemporary society.
Item Analysis of a Reading Test in a Sri Lankan Context using Classical Test Theory

This paper is based on a research study on a reading test that evaluates the different cognitive processes prescribed by Khalifa and Weir (2009). The 25-item test was designed based on a test specification targeted at the B2 level of the Common European Framework of Reference for Languages (CEFR). The responses of 50 students were used to check the validity and reliability of the test. The validity of the test was ascertained through item analysis involving item difficulty indices, item discrimination indices, and distractor analysis. Each item was studied to provide detailed information leading to the improvement of test construction. To achieve test reliability, the Kuder-Richardson Formula 20 (KR-20) was applied. The results were achieved by simply using Microsoft Excel. Findings revealed that the test met the standards for content validity, indicating acceptable item difficulty indices, with 17 items at the moderate level between the ranges of 0.30 and 0.79. Except for three items, all others functioned well to differentiate between high- and low-ability students, and only five items had malfunction distractors. Meanwhile, the reliability value of the test scores was 0.82, which is deemed a good value, proving the consistency of the test results. It signifies that more than half, that is 88%, of the test items were well functioning and that the test proved to be valid and reliable. The present research can contribute to students, teachers, and test-makers having an insightful understanding of item analysis and test development.
Students' perception of the quality of virtual education in times of COVID-19 pandemic

This article presents a study on the perception of students pursuing technical careers, on aspects related to the quality of virtual education during times of covid-19 pandemic. The data analyzed were obtained from surveys of 75 students of various educational levels in aspects such as quality in teaching, accessibility to virtual resources, teacher training, continuity of the curriculum, equal conditions, and the influence of policy on the quality of education in general. It was concluded that the educational process in its virtual modality is acceptable from the point of view of intrinsic advantages such as flexibility and yet there is also a change of focus in the educational institution that pays attention to providing a better virtual educational process diverting attention from equally important processes such as the communication of internal and external actions to the institution.&#x0D; Keywords: Virtual education, challenges, pandemic, COVID-19.
Classic Probability Revisited (II): Algebraic Operations of the Extended Probability Theory

Part II of this paper presents a set of comprehensive algebraic operators on the extended mathematical structures of the general probability theory. It is recognized that the classic probability theory is cyclically defined among a small set of highly coupled operations. In order to solve this fundamental problem, a reductive framework of the general probability theory is introduced. It is found that conditional probability operation on consecutive events is the key to independently manipulate other probability operations. This leads to a revisited framework of rigorous manipulations on general probabilities. It also provides a proof for a revisited Bayes’ law fitting in more general contexts of variant sample spaces and complex event relations in fundamental probability theories. The revisited probability theory enables a rigorous treatment of uncertainty events and causations in formal inference, qualification, quantification, and semantic analysis in contemporary fields such as cognitive informatics, computational intelligence, cognitive robots, complex systems, soft computing, and brain informatics.
Pesantren Students’ Religious Beliefs and Attitudes toward Learning English in Indonesia

Some students in Indonesian Pesantren (Islamic Boarding School) reported negative attitudes toward English as lingua Franca due to their environmental background, socio-cultural awareness, and identities. However, there are limited studies conducted in investigating their religious beliefs as the basis of pesantren students' attitudes toward learning English. Thus, this study aimed to investigate Indonesian pesantren students' attitudes toward learning English based on their religious beliefs and practices. The survey method was addressed to 250 respondents from three pesantren in Central Java. The researchers used a close-ended questionnaire adapted from the Attitudes/motivation Test Battery and 12 items focusing on the students' religious beliefs toward English. Besides, semi-structured interviews were conducted to get a deep understanding. This research employed one-way ANOVA and revealed a significant difference of the students' educational background in the pesantren on the mean of L2 attitudes, F = (14.40), Sig. = .000. The qualitative analysis revealed that ethnoreligious background shaped the positive attitudes of pesantren students toward English. Although most English speakers were non-believers, the students believed that learning English does not indicate the equal faith of non-believers and threat their religious identity. Furthermore, the participants claimed that learning English is important and not forbidden by religious teaching. They also thought that learning English can be considered as a kind of worship depending on the learner's intention, such as for communicating Islamic values to non-believers, future education, and improving careers. Keywords: Attitudes; Ethnoreligious Background; Pesantren Students; Religious Beliefs
Book Review: How to Write and Get Published: A Practical Guide for Librarians

"Book Review: How to Write and Get Published: A Practical Guide for Librarians." Journal of Access Services, 19(1), p. 9
Conservativity, Restrictedness, and Quantification

This chapter develops the idea that aboutness in natural language has a reflex in semantics in the notion of conservativity (a concept that is familiar from work in generalized quantifier theory). Ludlow and Živanović show that the syntactic counterpart of conservativity is restrictedness, which they define in terms of their notion of p-scope, thus connecting restrictedness and the Dynamic Deductive System. Finally, Ludlow and Živanović show that with a notion of restrictedness in place they can use logical polarity to define away quantificational operators in natural language, and also replace disjunctions and conjunctions with a neutral junction. They treat all quantification as involving quantificational closure over free variables; whether quantificational closure is existential or universal, and whether the neutral junction is to be a conjunction or a disjunction, is determined by polarity and restrictedness. In other words, polarity and restrictedness can “rule it all.”
Efficient Generation of Roots of Power Residues Modulo Powers of Two

We propose a characterization for the roots of power residues modulo powers of two. By this characterization, the remainder of dividing a root by a power of two is uniformly distributed in a set with two odd integers, while the quotient is uniformly distributed in an initial segment of positive integers. This property allows us to generate roots of power residues modulo powers of two efficiently.
Correction to: Inception of Perception—Augmented Reality in Virtual Reality: Prototyping Human–Machine Interfaces for Automated Driving

Correction to: Chapter “Inception of Perception—Augmented Reality in Virtual Reality: Prototyping Human–Machine Interfaces for Automated Driving” in: A. Riener et al. (eds.), User Experience Design in the Era of Automated Driving, Studies in Computational Intelligence 980, https://doi.org/10.1007/978-3-030-77726-5_18
Computer-Aided News Article Summarization

This paper presents a parameter-settable text summarization system for news articles. The basic system design concept involves having the system generate various types of summaries that meet diverse user preferences. From a statistical viewpoint, we design 24 text skimming parameters for the system. These parameters are categorized into five groups: locations, sentence types, keywords, special expressions, and miscellanies. Experimental simulation employing 16 Japanese sample news articles shows that the parameters are powerful enough to generate various types of summaries for text summarization.
English-Mongolian, Mongolian-English Neural Machine Translation

The latest neural machine translation not only performs better than systems that consider simple words and sentence structures, but also finds a delicate connection between source and target words. Neural machine translation provides a simple modeling mechanism that is easy to use in practice and science. Thus, it does not require concepts such as word ranking, a key component of the system that takes into account the structure of words and sentences. While this simplicity may be seen as an advantage, on the other hand, the lack of careful spelling is to lose control of the translation. Systems that take into account the structure of words and sentences create translations consisting of word sequences in the curriculum data. On the other hand, the neural machine translation is more flexible in terms of translations that don't exactly match the training data. This provides more opportunities for such models, but exempts translation from pre-determined restrictions. Failure to connect specific words can make it difficult to connect the target words you create to the original word. The widespread use of neural networks in the translation system has the advantage of allowing users to translate certain terms and translate uneducated data to a certain extent. In some cases, however, the structure of a sentence is often distorted. The paper is intended to address issues such as the control of neural machine translation, more accurate translation of unidentified data, the accuracy of sentence structure and grammar boundaries.
Heterogeneous gradient computing optimization for scalable deep neural networks

Abstract Nowadays, data processing applications based on neural networks cope with the growth in the amount of data to be processed and with the increase in both the depth and complexity of the neural networks architectures, and hence in the number of parameters to be learned. High-performance computing platforms are provided with fast computing resources, including multi-core processors and graphical processing units, to manage such computational burden of deep neural network applications. A common optimization technique is to distribute the workload between the processes deployed on the resources of the platform. This approach is known as data-parallelism. Each process, known as replica, trains its own copy of the model on a disjoint data partition. Nevertheless, the heterogeneity of the computational resources composing the platform requires to unevenly distribute the workload between the replicas according to its computational capabilities, to optimize the overall execution performance. Since the amount of data to be processed is different in each replica, the influence of the gradients computed by the replicas in the global parameter updating should be different. This work proposes a modification of the gradient computation method that considers the different speeds of the replicas, and hence, its amount of data assigned. The experimental results have been conducted on heterogeneous high-performance computing platforms for a wide range of models and datasets, showing an improvement in the final accuracy with respect to current techniques, with a comparable performance.