Reviewerly/exHarmony huggingface dataset:
Integrated photonic delay-lasers for reservoir computing

Currently, multiple photonic reservoir computing systems show great promise for providing a practical yet powerful hardware substrate for neuromorphic computing. Among those, delay-based systems offer a simple technological route to implement photonic neuromorphic computation. Its operation boils down to a time-multiplexing with the delay length limiting the processing speed. As most optical setups end up to be bulky employing long fiber loops or free-space optics, the processing speeds are ranging from kSa/s to tens of MSa/s. Therefore, we focus on external cavities which are far shorter than what has been realized before in such experiments. We present experimental results of reservoir computing based on a semiconductor laser, operating in a single mode regime around 1550nm, with a 10.8cm delay line. Both are integrated on an active/passive InP photonic chip built on the Jeppix platform. Using 23 virtual nodes spaced 50 ps apart in the integrated delay section, we increase the processing speed to 0.87GSa/s. The computational performance is benchmarked on a forecasting task applied to chaotic time samples. Competitive performance is observed for injection currents above threshold, with higher pumps having lower prediction errors. The feedback strength can be controlled by electrically pumping integrated amplifiers within the delay section. Nevertheless, we find good performance even when these amplifiers are unpumped. To proof the relevance and necessity of the external cavity on the computational capacity, we have analysed linear and nonlinear memory tasks. We also propose several post-processing methods, which increase the performance without a penalty to speed.
Study of Features and Number of Time Steps to Improve Hourly Solar Power Forecasting via LSTM

The number of time steps used for machine learning methods on the hourly prediction of solar photovoltaic (PV) generation is typically set to one. In this paper, we investigate the larger-than-one time steps for long short-term memory (LSTM)-based method to improve the accuracy of prediction with a limited dataset. Besides, we analyze the contribution of all available features toward a different number of time steps and select proper features for better training. By using real-world dataset, the experimental results show that the proposed method can effectively outperform the conventional one whilst using the same dataset.
QuCCs: an experimental of quantum key distribution using quantum cryptography and communication simulator

The applications of quantum information science move towards bigger and better dimensions for the next generation technology. In the field of quantum cryptography and quantum computation, the world already witnessed various groundbreaking tangible products and promising results. Quantum cryptography is one of the mature fields of quantum mechanics and the devices are already available in the markets. In order to reach the heights of digital cryptography, the current state of quantum cryptography is still under various researches. However, the complexity of quantum cryptography is high due to combination of hardware and software. The lack of effective simulation tool to design and analyze the quantum cryptography experiments delays the reaching distance of the success. Therefore, in this paper, a framework to achieve an effective single photon based quantum cryptography simulation tool is proposed. The limitations of a commercial photonic simulation tool based experiments are also highlighted. Finally, the ideas for achieving one-stop simulation package for quantum based secure key distribution experiments are discussed. The proposed modules of simulation framework have been analyzed from the programming perspective.
Optimization in Determining Routes of Goods Distribution Vehicle Using the Ant Colony Optimization Algorithm Method at PT XYZ

PT XYZ is one of freight forwarding companies in Indonesia, which is located in the city of Bandung. This company has managerial functions related to Collecting, Processing, Transporting, Delivery, and Reporting. However, the fact is in the process of Transporting this company still uses a zoning system which is a shipping system that still divides tertiary areas and each of these areas uses one vehicle. One problem that arises is that companies want effective and efficient performance in the distribution system of goods with the minimum total transportation costs. However, the company does not know yet whether the company's shipping routes have been effective and efficient or not. The company has tertiary network distribution route that are 2 routes with a total distance of 143.4 Km and a total transportation cost of Rp 5,681,484 /month. This research aims to determine the optimal goods distribution route using the Ant Colony Optimization Algorithm method, which is the method of finding the shortest path following ant behavior in taking food to its nest. Based on the results of the research, it is obtained a total distance of 109.2 Km because it becomes 1 route and total transportation costs Rp 3,337,992 /month, then it is obtained optimal results with a difference in distance is 34.2 Km and a total transportation cost of Rp 2,343,492 /month using one vehicle.&#x0D; Keywords: Optimization, Distribution, Ant Colony Optimization Algorithm&#x0D; &#x0D;
Transformation of Classroom Teaching in Modern Russian Schools: State of the Art

Education is getting more informed, digitalised and person-centred.The transition to active learning blurs the boundaries of traditional classroom teaching and encourages the development of new teaching formats.As a result, more and more teachers are turning from "rigid" teaching formats to ones that are more flexible.However, new teaching formats and their role in achieving the goals of education remains little studied.New teaching formats in Russian school education emerge due to the awareness of the need to establish a proper subject-object relationship between the participants of the educational process.Another factor is the growing profile of electronic resources and technologies as means to train effective approaches to information processing (both textual and non-textual).The article aims to analyse advantages and disadvantages of the new formats of teaching and their possible application in a school (evidence from teachers of biology).It will also determine the readiness of teaching community to grasp and implement new formats in teaching practice in a school.
RESim - Automated Detection of Duplicated Requirements in Software Engineering Projects.

The work presented in this paper has been supported by the GENESIS project under the National Spanish Program for Research Aimed at the Challenges of Society (RETOS) 2016, contract TIN2016-79269-R.
Corporate Social Responsibility and Community Development Outcomes in the Niger Delta: An Empirical Analysis of the SPDC Global Memorandum of Understanding (GMoU)

As corporations adopt innovative ways to secure business interests, they seek to influence social space. Stakeholder’s increasing awareness of their rights serve to hold corporations responsible for their actions and inactions to foster sustainable development in their operational areas. While not all stakeholder demands can be met by corporations, managing stakeholder expectations of Corporate Social Responsibility (CSR) outcomes proves difficult partly due to the ambiguity of defining the content of development investments. This study evaluated the nature and types of development projects and outcomes implemented through the GMOU in selected clusters in Rivers and Bayelsa States. The study disaggregated the programme and project content of the SPDC GMoU in selected Rivers and Bayelsa State clusters. The study relied on the qualitative approach with the adoption of key informant interviews and focus group discussions as methods of data collection. A key finding of the study was that CSR and Community Development outcomes in the Niger Delta indicates a preference for quick win infrastructural projects over other forms of human development programmes such as income, poverty, health, education, and individual socio-economic development.  The paper concludes that at every stage of development, people know what their needs are and can prioritise according to expediency, available resources and future development needs. While there are no pre-ordained paths to development, the study makes a case for expansion of development focus beyond infrastructural projects to accommodate human capital development and other forms of interventions in a broader community framework in order to meet more stakeholder needs in a sustainable way.
Pengaruh Intensitas Pemanfaatan E-Commerce Dan Tingkat Literasi Ekonomi Terhadap Tingkat Konsumsi Siswa Di SMA Negeri 4 Malang

The level of consumption is how extent the level of consumption is carried out by students.It is because there is a convenience in doing consumption through the famous shopping application that commonly known as Shopee.In this study, the level of consumption is affected by two factors, they are e-commerce utilization intensity as well as the level of economic literacy.The aims of this study are 1) to know the effect of e-commerce utilization intensity on the level of student's consumption in SMA Negeri 4 Malang 2) to know whether there is an effect of the level of economic literacy on the level of students' consumption in SMA Negeri 4 Malang 3) to know whether there is an effect of e-commerce utilization intensity and the level of economic literacy on the level of students' consumption in SMA Negeri 4 Malang.The populations of this conducted study were all students of class X IPS SMAN 4 Malang that consist of 103 students, whereas only took samples of 82 students.The type of this present research is explanatory research in which using multiple linear regression analysis techniques.The results of this study were that ecommerce utilization intensity had a significant effect on the consumption levels of 38.67%.It is because in the industrial revolution 4.0 era, teenagers want to be fast, easy and practical in fulfilling their needs.The level of economic literacy had a significant effect on the consumption levels of 5.80%.Moreover, in the industrial revolution 4.0 era, teenager in fulfilling their needs no longer apply the economic literacy, because e-commerce has provided more convenience in fulfilling the people's needs.Especially for class X students who were still in basic level understanding of economics, so that they had not been able to apply economic literacy that is included in everyday life.
Cybersecurity for higher education institutions: adopting regulatory framework

Cybersecurity is defined as the protection of networks, data and systems in the cyberspace.It should have the ability to protect or defend an organization's use of cyberspace from any attack, conducted via cyberspace with the intention of disrupting, disabling, destroying, or maliciously controlling a computing environment and even destroying the integrity of the data or stealing controlled information.As the rapid technological developments have provided vast opportunities and potential sources of efficiency to every organization, these new technologies have also brought unprecedented threats and could be a critical issue for every organization.In this study, Phase I delved into the different Cybersecurity frameworks and regulatory environments presented through review of related literature.One of the frameworks is the Cybersecurity Framework released in 2014 by the National Institute of Standards and Technology (NIST).Establishing an internal cyber security policies and procedures, management of cyber security risk and the alignment to international information security standards will be the highlight of the literature review of this study.The Phase II will focus on the design, and analysis of a specific cyber security dealings guided by the standard regulatory framework intended for selected State Universities in Region III in the Philippines.Facing the threat of cyber-attacks, the researchers believed that educational administrators and leaders need to implement the right solutions to protect their resources from cyber threats.All organizations need to understand these cyber threats they face.The challenge now is the establishment of imperative tasks related to preservation of confidentiality, integrity and availability of information in the Cyberspace while facilitating an essential operating function.
Relationship among Career Exploration Behavior, Career Aspiration, and Academic Effort of Physical Education College Students

The purpose of this study was to investigate the relationship among career exploration behavior, career aspiration, and academic effort of physical education college students. Through convenience sampling method, selected 287survey questionnaires were used for final analysis from physical education college students. With the collected data simple and multiple regression analysis were performed by SPSS 20.0. The results of the analysis were summarized as follows. First, the self exploration impacts positively(+) influence on career aspiration and academic effort of physical education college students. Second, the career aspiration impacts positively(+) influence on academic effort of physical education college students. Third, the career aspiration was revealed to function as a mediator on the relationship between career exploration behavior and academic effort of physical education college students. These results were improved career aspiration and academic effort through the career exploration behavior of physical education college students, and it also means improving the academic effort through the career aspiration. And the career aspiration is also a mediator in the relationship between career exploration behavior and academic effort.
Feature matching based on curve descriptor and local D-Nets for fish-eye images

Most feature-matching algorithms based on perspective images, such as scale-invariant feature transform (SIFT), speeded up robust features, or DAISY, construct their feature descriptors from the neighborhood information of feature points. Large nonlinear distortion results in different amounts of neighborhood information at different feature points within the fish-eye images, especially for the case when a feature pixel is at the central region and the corresponding feature pixel is at the periphery. In contrast, descriptor-Nets (D-Nets) is a feature-matching algorithm based on global information. It is more robust, but it is time-consuming. In this paper, we employ the SIFT detector to extract feature pixels, and then we propose a novel feature-matching strategy based on the D-Nets algorithm. We modify the linear descriptors in the traditional D-Nets algorithm and propose a curve descriptor based on the hemispheric model of a fish-eye image. In the traditional D-Nets algorithm, each feature point is described by all other pixels of the entire image, and complicated calculations cause slow matching speed. To solve this problem, we convert the traditional global D-Nets into a novel local D-Nets. In the experiment, we obtain image pairs from real scenery using the binocular fish-eye camera platform. Experimental results show that the proposed local D-Nets method can achieve more than 3 times the initial matching pixels, and the percentage of bad matching is reduced by 40% compared with the best performing method among the comparison methods. In addition, the matching pixel pairs obtained by the proposed method are evenly distributed, either in the center region with small distortion or in the peripheral region with large distortion. Meanwhile, the local D-Nets algorithm is 16 times less than that of the global D-Nets algorithm.
Improving Continuous Variable Quantum Secret Sharing with Weak Coherent States

Quantum secret sharing (QSS) can usually realize unconditional security with entanglement of quantum systems. While the usual security proof has been established in theoretics, how to defend against the tolerable channel loss in practices is still a challenge. The traditional ( t , n ) threshold schemes are equipped in situation where all participants have equal ability to handle the secret. Here we propose an improved ( t , n ) threshold continuous variable (CV) QSS scheme using weak coherent states transmitting in a chaining channel. In this scheme, one participant prepares for a Gaussian-modulated coherent state (GMCS) transmitted to other participants subsequently. The remaining participants insert independent GMCS prepared locally into the circulating optical modes. The dealer measures the phase and the amplitude quadratures by using double homodyne detectors, and distributes the secret to all participants respectively. Special t out of n participants could recover the original secret using the Lagrange interpolation and their encoded random numbers. Security analysis shows that it could satisfy the secret sharing constraint which requires the legal participants to recover message in a large group. This scheme is more robust against background noise due to the employment of double homodyne detection, which relies on standard apparatuses, such as amplitude and phase modulators, in favor of its potential practical implementations.
Analysis of Game Elements in Digital Educational Game According to Gagne Nine Events of Instruction

The purpose of this study is to analyze the game elements based on Gagne Nine Events of Instruction and to develop instrument which will be use to analyze the game elements needed in the development of digital educational games.The study was conducted using qualitative design where the interview and observation involved.A total of 20 students from a school in Tanjong Malim Perak participated in this survey.The findings of the study show that eight game elements are analyzed based on Gagne Nine Events of Instruction that are mystery, action, challenge, being at risk, uncertainty of outcome, opportunity for mastery, visible signs of progress and emotional content.These elements will be aligned with Gagne Nine Events of Instruction to develop an instrument.In conclusion, this study will further enhance the digital educational games design process and further promote innovation in teaching and learning in line with the Malaysian Education Blueprint 2013-2025.
The Effect of Use Interactive Learning Media Environment-based and Learning Motivation on Science Learning Outcomes

The study aims to determine the effect of the use of interactive learning media environment-based and learning motivation on science learning outcomes. This research was conducted on grade V students of SDN Wijaya Kusuma 07 Jakarta Barat from September to November 2019. The method used was an experiment with a research design using two-way ANAVA (treatment by level 2x2), with the sample of 61 students was obtained using a multi-stage random sampling. Based on data analysis, it was obtained: First, the science learning outcomes of students who learn to use interactive learning media environment-based are higher than the science learning outcomes of students who learn to use non-interactive learning media, as evidenced by Fcount (5.90) &gt; Ftable (4.17 ); second, there was an effect of learning media interaction and learning motivation on the science learning outcomes, this can be seen from the acquisition price of Fcount (26.05) &gt; Ftable (4.17); third, in groups of students who have high learning motivation, the science learning outcomes of students who learn to use interactive learning media environment-based are higher than the science learning outcomes of students who learn to use non-interactive learning media, with the Tukey-test Qcount Test (7.53) &gt; Qtable (4.04); fourth, in groups of students who have low learning motivation, the science learning outcomes of students who learn to use interactive learning media environment-based are lower than the science learning outcomes of students who learn to use non-interactive learning media, with the Tukey-test Qcount Test (2.67) &lt; Qtable (4.04).
A note on generalization of bent boolean functions

<p style='text-indent:20px;'>Suppose that <inline-formula><tex-math id="M1">\begin{document}$ \mu_p $\end{document}</tex-math></inline-formula> is a probability measure defined on the input space of Boolean functions. We consider a generalization of Walsh–Hadamard transform on Boolean functions to <inline-formula><tex-math id="M2">\begin{document}$ \mu_p $\end{document}</tex-math></inline-formula>-Walsh–Hadamard transforms. In this paper, first, we derive the properties of <inline-formula><tex-math id="M3">\begin{document}$ \mu_p $\end{document}</tex-math></inline-formula>-Walsh–Hadamard transformation for some classes of Boolean functions and specify a class of nonsingular affine transformations that preserve the <inline-formula><tex-math id="M4">\begin{document}$ \mu_p $\end{document}</tex-math></inline-formula>-bent property. We further derive the results on <inline-formula><tex-math id="M5">\begin{document}$ \mu_p $\end{document}</tex-math></inline-formula>-Walsh–Hadamard transform of concatenation of Boolean functions and provide some secondary constructions of <inline-formula><tex-math id="M6">\begin{document}$ \mu_p $\end{document}</tex-math></inline-formula>-bent functions. Finally, we discuss the <inline-formula><tex-math id="M7">\begin{document}$ \mu_p $\end{document}</tex-math></inline-formula>-bentness for Maiorana–McFarland class of bent functions.
Classifying constructive comments

We introduce the Constructive Comments Corpus (C3), comprised of 12,000 annotated news comments, intended to help build new tools for online communities to improve the quality of their discussions. We define constructive comments as high-quality comments that make a contribution to the conversation. We explain the crowd worker annotation scheme and de ne a taxonomy of subcharacteristics of constructiveness. The quality of the annotation scheme and the resulting dataset is evaluated using measurements of inter-annotator agreement, expert assessment of a sample, and by the constructiveness sub-characteristics, which we show provide a proxy for the general constructiveness concept. We provide models for constructiveness trained on C3 using both feature-based and a variety of deep learning approaches and demonstrate, through domain adaptation experiments, that these models capture general rather than topic- or domain-specific characteristics of constructiveness. We also examine the role that length plays in our models, as comment length could be easily gamed if models depend heavily upon this feature. By examining the errors made by each model and their distribution by length, we show that the best performing models are effective independently of comment length. The constructiveness corpus and our experiments pave the way for a moderation tool focused on promoting comments that make a meaningful contribution, rather than only filtering out undesirable content.