Reviewerly/exHarmony huggingface dataset:
Acting in Delayed Environments with Non-Stationary Markov Policies

The standard Markov Decision Process (MDP) formulation hinges on the assumption that an action is executed immediately after it was chosen. However, assuming it is often unrealistic and can lead to catastrophic failures in applications such as robotic manipulation, cloud computing, and finance. We introduce a framework for learning and planning in MDPs where the decision-maker commits actions that are executed with a delay of $m$ steps. The brute-force state augmentation baseline where the state is concatenated to the last $m$ committed actions suffers from an exponential complexity in $m$, as we show for policy iteration. We then prove that with execution delay, deterministic Markov policies in the original state-space are sufficient for attaining maximal reward, but need to be non-stationary. As for stationary Markov policies, we show they are sub-optimal in general. Consequently, we devise a non-stationary Q-learning style model-based algorithm that solves delayed execution tasks without resorting to state-augmentation. Experiments on tabular, physical, and Atari domains reveal that it converges quickly to high performance even for substantial delays, while standard approaches that either ignore the delay or rely on state-augmentation struggle or fail due to divergence. The code is available at github.com/galdl/rl_delay_basic and github.com/galdl/rl_delay_atari.
Simple Quantum Computing with Quantum Bits Decoupled in Time and Space Implemented in Silicon and Coupled Back as Analog Signals and Waves Processed by Analog Computer

We propose using available silicon technology for simple implementation of quantum computing by decoupling its quantum bits in time and space then coupled back as analog signals and waves to present all possible superposition values of Q-Bits. Broadcasting waves allows Q-Bits to be available in space at different points at the same time creating an additional dimension for Q-Bits. The complexity of decoupling Q-Bits in space and time is evaluated and an optimized decoupling in both time and space is presented. We suggest using an analog computer to process the Q-bits implemented as analog signals or waves. The analog computer needs to be reconfigurable by a digital computer for initialization and reconfiguration to run quantum applications.
Interference analysis of the public walkie-talkie on the Cospas-Sarsat system’s uplink

In China, the public walkie-talkie operates in the band 409.750MHz ~ 409.9875MHz, which may cause harmful interference to the adjacent frequency band, a security application--Cospas-Sarsat system. Considering the popularity of the public walkie-talkie and the development trend of multi-function integration of the phone, it is necessary to study the interference of the public walkie-talkie on the global satellite search and rescue system. Firstly, this report investigate the situation of the public walkie-talkie and the Cospas-Sarsat system. Secondly, the interference scenario of the system is analyzed. Based on the above contents, a reasonable interference calculation method is designed, and the interference situation is analyzed using the method.
Characteristics of Mathematics Teachers' Practices and Beliefs about Project-based Learning and Teaching Mathematics in Ukraine

This empirical study determines the obvious and hidden factors that affect the Ukrainian Mathematics teachers to use Project-Based Learning and Teaching (PBL and PBT) Mathematics.A survey of 126 practicing Mathematics teachers was conducted using a Standard closed ended questionnaire.The study confirms that modern Mathematics teachers believe that it is impossible to teach Mathematics for modern students without using PBL and PBT.On the one hand, teachers demonstrate their beliefs in these educational techniques.On the other hand, the survey reveals hidden factors that are inhibitory in the practice of PBL and PBT Mathematics.The study shows the following statistically confirmed factors in teachers' beliefs concerning the use of PBL and PBT Mathematics: Content-Technological Factor; Result & Age Factor; Factor of the Target Audience on the expediency of using PBL and PBT Mathematics; Teacher's Overload Factor; Praxeological Factor; Locality Factor; Teacher's Awareness Spectrum Factor.The previous assumption that the experience of a Mathematics teacher is an influential factor in the use of PBL and PBT has not been statistically confirmed.The results show that an influential factor is the Locality Factor.So, it's important if a teacher teaches Mathematics in a city or a village.Its origins (genesis and causes) and the consequences of this factor influence on educational processes in Ukraine need more detailed study.
Technology Tetheredness and Creative Process Engagement during COVID-19: A Moderated Mediation Model of Spousal Support and Cognitive Fatigue

Furthermore, cognitive fatigue more negatively influenced the focal relation [ ]for employees with higher spousal support, tetheredness to technology during COVID-19 may not be complicated and might even help-finings spousal support;however, this influence depends upon employee interpersonal factors as well [ ]this research is contributed by studying the uncertain relationship between tetheredness to technology during COVID-19 and employee creative process engagement [ ]contribution of this research is based on the signaling theory by Spence (1973) to relate worker cognitive fatigue to creative process engagement through manager perception [ ]this research extends the literature on workrelated effects associated with tetheredness to technology which has primarily concerned with employee engagement in creative processes
AN IMAGE TRANSFER USING NI-USRP

The National instruments (NI) Universal Software Radio Peripheral (USRP) are RF transceivers used for the advancement and study of software -defined Radio (SDR).The NI-USRP transceivers can transmit and receive the radio-frequency signals in several bands and are used in the area of communication, education and research.In this paper we are trying to transfer an image using NI-USRP using LabVIEW.
노인의 사회적 자본에 대한 고찰

This study intends to emphasize the importance of expanding and increasing social capital as a personal social solution for social burden of supporting the elderly as the baby boom generation enters the aging population, and will have to develop into a structure of coexistence based on policies and reciprocal trust in the government through mutually compatible structure between the public and private sectors. Therefore, social, psychological, mental, and physical problems of the elderly became a social task and various support systems for healthy and happy lives of the elderly became necessary. Social capital is a variety of social opportunity resources that can be acquired through the network and social engagement that each individual has in social relationships rather than the substantial aspect. The desire for positive life in old age is a social paradigm that goes beyond personal dimensions. Social capital makes the elderly to make positive effects on trust, participation, and regulation in social relationship that allow the elderly to reach successful aging, and this study identified that social capital is an important influence in providing jobs for the elderly and motivation through social, cultural, leisure, and volunteer activities. Therefore, this study suggests that social capital of the elderly is an important factor for meeting social opportunities as social integration, for preventing psychological, social, and physical problems and poverty, and to lead a satisfying life in their old age.
Hybrid Distance-based, CNN and Bi-LSTM System for Dictionary Expansion

Dictionaries like Wordnet can help in a variety of Natural Language Processing applications by providing additional morphological data. They can be used in Digital Humanities research, building knowledge graphs and other applications. Creating dictionaries from large corpora of texts written in a natural language is a task that has not been a primary focus of research, as other tasks have dominated the field (such as chat-bots), but it can be a very useful tool in analysing texts. Even in the case of contemporary texts, categorizing the words according to their dictionary entry is a complex task, and for less conventional texts (in old or less researched languages) it is even harder to solve this problem automatically. Our task was to create a software that helps in expanding a dictionary containing word forms and tagging unprocessed text. We used a manually created corpus for training and testing the model. We created a combination of Bidirectional Long-Short Term Memory networks, convolutional networks and a distancebased solution that outperformed other existing solutions. While manual post-processing for the tagged text is still needed, it significantly reduces the amount of it.
A Brief Tour of Electromagnetism

So far you will have encountered various expressions from electrostatics and magnetostatics which we will show can then be synthesised into four equations, the Maxwell equations which, with the Lorentz force law, are a complete description of the behaviour of charged particles and electromagnetic fields.
Meta-learning with negative learning rates

Deep learning models require a large amount of data to perform well. When data is scarce for a target task, we can transfer the knowledge gained by training on similar tasks to quickly learn the target. A successful approach is meta-learning, or "learning to learn" a distribution of tasks, where "learning" is represented by an outer loop, and "to learn" by an inner loop of gradient descent. However, a number of recent empirical studies argue that the inner loop is unnecessary and more simple models work equally well or even better. We study the performance of MAML as a function of the learning rate of the inner loop, where zero learning rate implies that there is no inner loop. Using random matrix theory and exact solutions of linear models, we calculate an algebraic expression for the test loss of MAML applied to mixed linear regression and nonlinear regression with overparameterized models. Surprisingly, while the optimal learning rate for adaptation is positive, we find that the optimal learning rate for training is always negative, a setting that has never been considered before. Therefore, not only does the performance increase by decreasing the learning rate to zero, as suggested by recent work, but it can be increased even further by decreasing the learning rate to negative values. These results help clarify under what circumstances meta-learning performs best.
Image retrieval system for citizen services using penalized logistic regression models

This paper describes a procedure to deal with large image collections obtained by smart city services based on interaction with citizens providing pictures. The semantic gap between the low-level image features and represented concepts and situations has been addressed using image retrieval techniques. A relevance feedback procedure is proposed for Content-Based Image Retrieval (CBIR) based on the modelling of user responses. One of the novelties of the proposal is that the feedback learning procedure can use the information that citizens themselves can provide when using these services.
Comparative Analysis of United States and South Korean High School

This article is based on the information and data of European education technology departments and related higher education industry associations. Through comparative analysis of several cases, this article preliminarily discusses the characteristics and development trends of scientific research in European universities of applied sciences.Through this article, it is economic to carry out applied scientific research.After the society has developed to a certain stage, an important mission of the University of Applied Sciences.European countries have established a scientific research development mechanism for universities of applied sciences, which is composed of national, local governments, enterprises, and applied, for universities.Countries can learn from these experiences and establish.The scientific research management system of the University of Applied Sciences with its characteristics encourages the integration of applied scientific research and talent training and contributes outstanding talents and achievements to the local and national social and economic development.
Developing and Maintaining Trust Within Organizations: Tech One Global in Nepal

ABSTRACTAim: This study aims to ascertain how firms develop and maintain trust and the influences trust have in organizations.Method: This study was conducted through a qualitative research method ...
PENGAMANAN PESAN MENGGUNAKAN TEKNIK STEGANOGRAFI DENGAN ALGORITMA LEAST SIGNIFICANT BIT (LSB)

&lt;strong&gt;&lt;em&gt;Steganography is a technique or art to hide a secret message into a cover so that the existence of the secret message cannot be known by other people or third parties who do not have the ability to know the contents of the secret message. The Least Significant Bit (LSB) method is one of the methods used in steganography to hide a message by changing the value of the rightmost bit of a stego cover with a secret message. The purpose of this study was to hide a text message into an image using the LSB method.&lt;/em&gt;&lt;/strong&gt;
Robustness in Compressed Neural Networks for Object Detection

Model compression techniques allow to significantly reduce the computational cost associated with data processing by deep neural networks with only a minor decrease in average accuracy. Simultaneously, reducing the model size may have a large effect on noisy cases or objects belonging to less frequent classes. It is a crucial problem from the perspective of the models' safety, especially for object detection in the autonomous driving setting, which is considered in this work. It was shown in the paper that the sensitivity of compressed models to different distortion types is nuanced, and some of the corruptions are heavily impacted by the compression methods (i.e., additive noise), while others (blur effect) are only slightly affected. A common way to improve the robustness of models is to use data augmentation, which was confirmed to positively affect models' robustness, also for highly compressed models. It was further shown that while data imbalance methods brought only a slight increase in accuracy for the baseline model (without compression), the impact was more striking at higher compression rates for the structured pruning. Finally, methods for handling data imbalance brought a significant improvement of the pruned models' worst-detected class accuracy.
Simple deductive reasoning tests and numerical data sets for exposing limitation of today's deep neural networks

Learning for Deductive Reasoning is an open problem in the machine learning world today. Deductive reasoning involves storing facts in memory and generation of newer facts over time. The concept of memory, processor and code in deduction systems is fundamentally different from the purpose and formulation of weights in a deep neural network. A majority of the machine learning models are inductive reasoning models including state of the art deep neural networks which are effectively tensor interpolation based models. A step towards realization of memory is through recurrent neural networks and its variants, however the formal representation is not sufficient enough to capture a complex mapping function between input and output patterns. Deep neural networks are positioned to do away with feature engineering which is essentially deductive reasoning methodology. There are existing works in deductive reasoning in neural networks that require learning of syntax, unification and deduction and operate on text data as sequence of tokens. However the performance of deductive reasoning networks is far from perfection which may be either due to syntax or deduction aspects. In this context, we have proposed a suite of completely numeric data sets which do not require parsing as with text data. The 10 data sets are for - (a) selection (3 data sets) - minimum, maximum and top 2nd element in an array of numbers; (b) matching (3 data sets) - duplicate detection, counting and histogram learning; (c) divisibility tests (2 data sets) - divisibility of two numbers and divisibility by 3; (d) representation (2 data sets) - binary representation and parity. Though extremely simple in terms of feature engineering, in all of these tests, simple deep neural networks, random forest and recurrent neural networks have failed with very low accuracies. We propose these as numerical test-bed for testing learning models for deductive reasoning.
Label Smoothed Embedding Hypothesis for Out-of-Distribution Detection

Detecting out-of-distribution (OOD) examples is critical in many applications. We propose an unsupervised method to detect OOD samples using a $k$-NN density estimate with respect to a classification model's intermediate activations on in-distribution samples. We leverage a recent insight about label smoothing, which we call the \emph{Label Smoothed Embedding Hypothesis}, and show that one of the implications is that the $k$-NN density estimator performs better as an OOD detection method both theoretically and empirically when the model is trained with label smoothing. Finally, we show that our proposal outperforms many OOD baselines and also provide new finite-sample high-probability statistical results for $k$-NN density estimation's ability to detect OOD examples.
UPAYA MENINGKATKAN HASIL BELAJAR ILMU PENGETAHUAN SOSIAL DENGAN MENERAPKAN METODE KOOPERATIF MODEL JIGSAW PADA SISWA KELAS V MI MIFTAHUL HUDA PUCANGAN MONTONG TUBAN TAHUN PELAJARAN 2017/2018

This research is motivated by the fact that the still low learning outcomes of Social Sciences subjects in fifth grade MI Miftahul Huda Pucangan students. Possible learning methods that can affect student achievement are the cooperative jigsaw model. The problem of this research is to explain the efforts to improve learning outcomes of social science by applying the cooperative jigsaw method. The theories used in the conduct of this research include LAN about learning outcomes, social science and the cooperative jigsaw model method.&#x0D; This research is expected to provide answers to the formulation of the problem (1) How is the application of the jigsaw cooperative method in the learning process of social science in class V MI Miftahul Huda Pucangan Montong Tuban in the academic year 2017/2018? and (2) Can the cooperative jigsaw method improve social studies learning outcomes for fifth grade MI Miftahul Huda Pucangan Montong Tuban students in the 2017/2018 academic year?&#x0D; This type of research is classroom action research (CAR). The subjects of this study were 36 grade V students, consisting of 18 boys and 18 girls. This research lasted for 2 cycles. For data collection techniques used observation techniques and data collection tools in the form of test questions. The collected data is then analyzed using a data processing method with descriptive statistical analysis which presents the data in the form of tables and bar charts. Then presented in each cycle to get information (observations), both from data collected from observation sheets and written tests.&#x0D; The results of the study in the first cycle showed the average percentage of teacher activity in the first cycle meeting 1 78% and 2% meetings 86%, while in the second cycle 1 meeting 90% and 95% meetings 2. In addition to teacher activity, student activity in groups also increased, in cycle I meeting 1 the percentage of student activity was 68% and meeting 2 was 77%, whereas in cycle II at meeting 1 the percentage increased 80% and meeting 2 90%. Social studies learning outcomes in pre-cycle with an average value of 68.94 and classical completeness of 42%, the first cycle obtained an average value of 78.27 with classical completeness of 78%. In the second cycle learning outcomes increased with an average value of 82.61 with 92% mastery learning. Means that at the end of the second cycle it has been shown that classical learning completeness is in accordance with indicators of success.&#x0D; The results of these studies can be concluded, that by using the cooperative jigsaw model can increase teacher activity in managing learning and student activities in the learning process. Student learning outcomes in social studies lessons increase in accordance with predetermined minimal completeness criteria standards.
SOFTWARE IMPLEMENTATION ON ANDROID OS OF THE INFORMATION LEAK DETECTOR BY MEANS OF VISIBLE LIGHT MODULATION

The transmission of information by means of visible light intensity modulation is confirmed by the works of many authors and the existence of a Li-Fi data transmission network. The wide-spread use of led lighting controlled by controllers potentially creates a channel for acoustic information leakage through visible light modulation. In this paper, the authors consider the block diagram of the device for detecting the channel of information leakage. The authors sug-gest using a modern smartphone running Android OS to determine the modulation of the re-fresh rate detected by the smartphone’s light sensor
The problem of modern corporate education humanization

There is not enough systematic philosophical research in the scientific works that fully consider the problems of the corporate education forming and peculiarities of its functioning. The article presents the socio-philosophical approach to analyze the problems of the corporate education humanization in the modern information society. To understand the corporate education as a socio-philosophical phenomenon, it is necessary to find out the prerequisites for its emergence, conditions of its formation and development process. To do this, a systematic philosophical approach should be used based on the research analysis both in social philosophy, and related fields. The study of this problem is a complex cognitive process necessary for the cor porate education philosophical analysis. The article considers the basic categories for the socio-philosophical analysis of this phenomenon, such as, «social reality», «education», «continuing education», «corporate education» etc. The authors conclude that there is a steady trend of institutionalization and humanization of this social phenomenon as a result of the corporate education actively developing problem in the context of the information and communication society. An analysis of modern foreign and domestic scientific literature allows concluding that each country has a certain specificity of the corporate education, which is due to cultural characteristics, mentality, economy and the technology and production development level.