Reviewerly/exHarmony huggingface dataset:
Consistent Dialogue Generation with Self-supervised Feature Learning

Generating responses that are consistent with the dialogue context is one of the central challenges in building engaging conversational agents. We demonstrate that neural conversation models can be geared towards generating consistent responses by maintaining certain features related to topics and personas throughout the conversation. Past work has required external supervision that exploits features such as user identities that are often unavailable. In our approach, topic and persona feature extractors are trained using a contrastive training scheme that utilizes the natural structure of dialogue data. We further adopt a feature disentangling loss which, paired with controllable response generation techniques, allows us to promote or demote certain learned topics and persona features. Evaluation results demonstrate the model's ability to capture meaningful topics and persona features. The incorporation of the learned features brings significant improvement in terms of the quality of generated responses on two dialogue datasets.
Implementation of New Educational Principles in Alignment with the Smart City Concept

The modern cities are being transformed into intellectual systems. Digital technologies provide solutions for all the spheres of city functioning: healthcare, utilities, power engineering, traffic lines, resource management and education.Municipalities become the communities, in which government, post-secondary institutions, private business and citizens work as partners to build a better tomorrow.The goal of this transformation is sustainable development, which means resource savings, efficient environment management and the new format of employment. Postmodernism is replaced by the epoch of auto-modernism because of correlation of technological automation and autonomy of a human being. Auto-modernism merges such notions as capitalism, democracy and science and transforms their interdependence due to technological globalization. Internet becomes the center of their interconnection. Consequently, modern technologies reshape the social relationships and build foundations for remote work and distant studies.People at present try to use the possibilities of digital technologies in all spheres of life for the sake of savings, intensification and optimization. Education as one of the priorities in a value system of any society is also involved in the transformation process. Logic of teaching and learning processes is being changed in order to adapt to the needs of the modern students (due to the principle of continuous learning). Flipped classroom model for EFL and ESP teaching is one of the solutions of the above mentioned issues.
Implementation of IoT as an Android-Based Monitoring Fee Payment System

In a boarding house, there is a boarding house owner/manager who monitors and supervises. For tenants, you can make payments only when meeting with the boarding house owner/manager. In practice, boarding house owners are not always in the boarding house so there is a difficulty in monitoring the boarding payments for each room. The purpose of this final project is to make a tool to be able to monitor and manage boarding through the android smartphone media. In this system, boarding house owners can find out the payment status of each room and tenants can also find out the remaining rental time. This system is also installed with a doorlock solenoid which can be controlled by the boarding house owner via the Android application to open and close the boarding house door if the tenant has/has not made a payment. The process of sending data from the device installed in the room to the Android smartphone using an intermediary NodeMcu and sending data to Firebase so that the status can be monitored in realtime. In each room there is also a notification system in the form of an LED light. The LED light will give a warning about the remaining time of the boarding house rental. The conclusion in this final project, the application can perform monitoring realtime and tenants can control the solenoid with an average delay of 1m 68s. For sending data from hardware to the database, it has a delay of 0.2139673s which is quite good.
Password as a Special case of &amp;quot;Man-machine&amp;quot; Communication. A Pragmatic approach

The authorization on sites, in social networks and personal accounts with passwords is an extremely common practice today. It has become an integral part of people&amp;apos;s lives, even they are not aware of it. But despite this, most Internet users have difficulties in creating and remembering of the strong passwords. This article analyzes the problem using the speech act theory of John Austin and John Searle. It allows to shed light on a person&amp;apos;s behaviour on the Internet and his reaction to the question &amp;quot;Who is there?&amp;quot;, which the machine asks him.
THE EFFECT OF USING EXTENSIVE READING APPROACH TOWARDS STUDENTS’ READING ABILITY

This research is an quantitative research. The population of this research was the second grade of SMAN 3 Bukittinggi. in this research, the researcher used the purposive sampling technique in determining the sample. There were two classes as the sample of this research. In the experimental class the students were taught by using Extensive Reading Approach. While, in control class the students were taught by using traditional technique and both of classes were given post test at the end of meeting. In order to analyze the data, the researcher used the normality test by using Liliefors test and tested the homogeneity of the data by using F test. The researcher also used the t-test formula to test the hypothesis and consulted its result with the ttable with α = 0.05.
MOTIVASI BELAJAR SISWA MIS I'ANATUSHIBYAN 02 PARUNG

Besides that, school is also a product where humans are educated and nurtured to become smart, productive, and qualifield human beings. The main purpose of education is to help students develop every potential that exsists in them so that they can become human beings who are balanced between their personal and social lives. The quality of student education outcomes can be determined by many factors, one of the most important is student motivation. Student motivation to learn greatly determines the success achieved by these student. Student who have high learning motivation will be able to achieve high learning achievement as well, but conversely, stuydent who have low motivation tend to get low learning achievement as well and will experience higher learning disabilities. To help increase a student’s motivation to learn, it is necessary to know the level of student motivation to learn. The phenomenon in the field shows that the level of student learning motivation is very important to know so that it can help these student to improve it, this is known after the researcher conducted interviews with supervisors at the school, according to the supervisor some students in the school had low motivation. To actively participate in teaching and learning activities in the classroom. Student motivation in this study is related to motivation, driving, change, and goals of motivation it self. The school that was taken as the research location was MI I’anatusshibyan 02 Parung. The students referred to in this study were all students of MI I’anatusshibyan 02 Parung.
Digital competence of the future teacher: Component composition

With the introduction of digital technologies, the daily life of a person and industrial relations are changing, the economy and education are being transformed. Digital technologies are not only a tool, but also an environment for the existence of a modern person, which opens up new opportunities: learning at any convenient time, continuous education, the ability to form individual educational routes, from users of electronic resources to become creators. However, such an environment requires teachers to take a different approach to organizing the educational process, to acquire new skills and abilities to work in the digital educational space. In these conditions, the pedagogical education system should provide training for a graduate with a high level of digital professional competence formation. The purpose of this article is to identify and theoretically substantiate the component structure of the phenomenon of “teacher's digital competence ” based on the analysis of scientific and pedagogical literature. The article is based on the analysis of studies by foreign scientists.
EFFECTIVENESS OF INFORMATIONAL TECHNIQUE ON KNOWLEDGE REGARDING PREVENTION FROM SIDE EFFECT OF EXCESS TELEVISION WATCHING AMONG MOTHERS OF PRIMARY SCHOOL CHILDREN

In this pre experimental design, sample consisted of 100 mothers of primary school children, selected by Non probability convenient sampling technique. Self structure knowledge questionnaire tools was used for assessing the knowledge of mothers Pre test was conducted by using the same self structured knowledge questionnaire and after 30 days post test was conducted using the same self structured knowledge questionnaire for assessing the effectiveness of informational technique Mean percentage of the knowledge score of  post test 21.06 was higher than  pre test 28.09. The‘t’ value for total pre test and post test was 19.23. The data was analyzed in terms of descriptive and inferential statistics. Another significant change in our social environment in the 21st century has been the fullness of our culture and our daily life by television. Unfortunately, the effects of one of the most common forms of electronic media have a devastating effect on children's well-being. Now it's not just children who are in the wrong place or having friends who are likely to be exposed to bad things when they go out on the street. The ugly real road is easily accessible to many young people now in their homes.
Real Time Face Detection With Image Dataset Load On Haar Cascade Algorithm

Human face identification has been a difficult issue in the regions of picture preparing and patter acknowledgment.[1] Another human face location calculation by crude Haar course calculation joined with three extra feeble classifiers is proposed in this paper. The three powerless classifiers depend on skin shade histogram coordinating, eyes location and mouth identification.[2] To start with, pictures of individuals are prepared by a crude Haar course classifier, almost without wrong human face dismissal (low pace of bogus negative) yet with some off-base acknowledgment (bogus positive)[3]. Furthermore, to dispose of these wrongly acknowledged non-human faces, a frail classifier dependent on face skin shade histogram coordinating is applied and a dominant part of non-human appearances are taken out. Next, another powerless classifier dependent on eyes identification is annexed and some leftover non-human countenances are resolved and dismissed. At long last, a mouth location activity is used to the excess non-human countenances what's more, the bogus positive rate is additionally diminished [4] With the help of OpenCV,test results on pictures of individuals under various impediments and enlightenments and some level of directions and revolutions, in both preparing set show that the proposed count is successful and accomplishes cutting edge execution. Moreover, it is productive due to its effectiveness and straightforwardness of execution
Focusing on Discrimination Between Road Conditions and Weather in Driving Video Analysis

We study an often ignored problem, the discrimination between road conditions and weather in driving videos, which may possibly lead to imperceptible errors on driving data analysis. We explore BDD100K, a common driving video database, and Kyushu Driving Data, a huge driving database created by ourselves. In our experiments, we use road condition labels and weather labels respectively to train several deep models on driving image sequences and demonstrate the difference between the two varieties of labels. The results indicate a significant difference between the two varieties, which leads to different performance of deep models.
The Structure of Team Search Behaviors with Varying Access to Information

Author(s): Prants, Matthew James; Simpson, James; Nalepka, Patrick; Kallen, Rachel W.; Dras, Mark; Reichle, Erik D; Hosking, Simon; Best, Christopher J; Richardson, Michael J | Abstract: In many team-based activities, members search for information to gain situational awareness and thereby structure their own behavior. The extent to which members are coupled and in control of their surrounding environment can be accessed via the fluctuations of their searching behaviors. To facilitate prospective control, assistive technologies such as a head-up display (HUD) can alleviate the demands of search and facilitate team performance. This study investigated how three-person teams divided their labor and structured their search behavior when playing a multiplayer search-and-retrieval task where first-person visibility and access to a HUD were manipulated. Results showed that access to task relevant information facilitated performance and division of labor, and increased prospective control of searching behaviors, as indexed by detrended fluctuation analysis (DFA). Over multiple sessions, teams learned to use the HUD to structure their behavior to achieve the task goal. Results indicate the potential in using DFA for monitoring prospective control in team contexts.
Application of sinusoidal speech modeling to the sound diarization problem

Speech is a specific feature of human and his advantage over other species within evolution. Sound diarization is a process of sound separation, taking into account belonging to the speaker. Before the advent of deep learning and the availability of the necessary computing resources, the quality of the algorithms that determine the speaker by voice left much to be desired. Diarization has numerous applications: smart speakers, mobile phones, automatic speech translation systems. But it should be noted that the existing diarization algorithms have drawbacks, for example, the complexity of work with simultaneous speech by several speakers or the lack of diarization results for its automatic application in some areas. This explains the relevance of research in this area. The sinusoidal model is an algorithm for tracking sequences of points in timeamplitudefrequency space. In existing researches, it is applied to simulations of echolocation, human speech, and speech synthesis. At the time of the study, no applications of the sinusoidal model in the problem of diarization were found in the literature. The paper considers the problem of diarization and the main quality indicators used in assessing the solutions to this problem. The main intermediate representations of sound used in existing solutions are considered, and a diarization algorithm using sinusoidal speech modeling is proposed. The advantage of the proposed algorithm is the ability to operate sinusoidal representations as VAD, which in general made it possible to make the used diarization algorithm more efficient.
Efficient Micro-Structured Weight Unification for Neural Network Compression

Compressing Deep Neural Network (DNN) models to alleviate the storage andcomputation requirements is essential for practical applications, especiallyfor resource limited devices. Although capable of reducing a reasonable amountof model parameters, previous unstructured or structured weight pruning methodscan hardly truly accelerate inference, either due to the poor hardwarecompatibility of the unstructured sparsity or due to the low sparse rate of thestructurally pruned network. Aiming at reducing both storage and computation,as well as preserving the original task performance, we propose a generalizedweight unification framework at a hardware compatible micro-structured level toachieve high amount of compression and acceleration. Weight coefficients of aselected micro-structured block are unified to reduce the storage andcomputation of the block without changing the neuron connections, which turnsto a micro-structured pruning special case when all unified coefficients areset to zero, where neuron connections (hence storage and computation) arecompletely removed. In addition, we developed an effective training frameworkbased on the alternating direction method of multipliers (ADMM), which convertsour complex constrained optimization into separately solvable subproblems.Through iteratively optimizing the subproblems, the desired micro-structure canbe ensured with high compression ratio and low performance degradation. Weextensively evaluated our method using a variety of benchmark models anddatasets for different applications. Experimental results demonstratestate-of-the-art performance.
Using Disinformation to Promote the Security of SMMWB Image Steganography Method

Information security researchers are interested in maintaining the secrecy, reliability and accessibility of data.The importance of information security comes from the need for protecting information and information system from unauthorized access, revelation, disruption, alteration, annihilation and use.Steganography and Cryptography are the two major techniques for information security.Steganography is the process that primarily concerned with hiding existent data in another transmission medium to achieve secret communication while Cryptography is about hiding the content of the message or scrambling it.However, steganography does not take the place of cryptography but rather boosts the security using its obscurity features.In this paper, the security of a previously proposed image steganography method SMMWB (Secret Message Matching With Braille) will be promoted by using the principle of disinformation instead of encryption as previously proposed methods, which means if the image steganography method has been steganalysed the eavesdropper will be able to read a fake secret message,he has been implicitly directed to read, not the real one.
Organizational Structures Leveraging Disruptive Innovations: A Conceptual Framework

Companies are facing challenges to survive due to substantial transformations induced by digital technologies. Thus, companies need to be innovative to sustain competitive advantages. Recent literature recognizes the potential of disruptive innovations as a key factor for a company’s competitiveness. However, disruptive innovations often challenge established companies due to the conflict between their existing business model and the newly emerging, disruptive business model. This study investigates how established companies can overcome such challenges and successfully develop and implement disruptive business models. In particular, we analyze different organizational structures proposed in the literature that promote disruptive business model innovations in established companies. On the basis of a systematic literature review, we conceptualize a framework linking the different organizational structures to the challenges arising from conflicting business models. The developed framework identifies which structures leverage the capability of established companies to implement a disruptive business model and thus strengthen its competitiveness.
SearchSECO: A Worldwide Index of the Open Source Software Ecosystem

Repository mining research is a data-intensive domain with a focus on source code. There are many ways to search for code in the worldwide software ecosystem, but these search methods are inefficient and only cover small parts of the software ecosystem. One of the problems is granularity: it is possible to search through code on a file-level and cover a significant part of the software ecosystem or search for a line of code and only cover a small part of the software ecosystem, but not both. We propose SearchSECO: a language-agnostic search engine and research platform that searches through abstract representations of source code methods. We use SearchSECO to search across the worldwide software ecosystem and index the encountered methods. With SearchSECO, the field is advanced because it (1) provides finer-grained and more efficient searches, (2) covers more of the software ecosystem than other search mechanisms, and (3) provides mechanisms for source code provenance.
Pelatihan Bahasa Inggris Berequivalent TOEFL Pada Reading Test CBT Terhadap Mahasiswa Semester Akhir Di Universitas Muhammadiyah dan IAIN Palangka Raya

English is an international language. In Indonesia, English is taught as a foreign language (English as a Foreign Language/EFL) from Elementary Schools to Higher Education. Especially at the University of Muhammadiyah Palangkaraya and IAIN Palangka Raya consider the importance of English which is shown through the TOEFL test and meet the scores determined before they are Judisium or Munakasah and have completed the thesis hearing in one semester. There were 20 participants from the Palangkaraya UM Students and Palangkaraya IAIN. The training method used in the English equivalent of Toefl training on Reading Tests is to use the Toefl training module on Reading Tests and also using a computerized software program in Toefl training on Reading Tests. The results of this training The training activities showed an increase between the pre-test and post-test results. The mean pre-test was 61 and the post-test mean increased to 83.6. In the pretest conducted to 20 participants were in the low category with a total of 4 people, a medium category of 13 people and a high of 3 people. The post-test results showed an increase in the score, namely the low category of 4 people, the medium category of 12 people and the high category increased to 4 people.
Three surveys from the last two decades in comparison. On the diffusion of Francoprovençal in Faeto and Celle San Vito (Apulia, Italy)

Abstandsprachen with no standard and little elaboration are a kind of minority languages representing Italian sociolinguistic diversity. An example for this typology is provided by groups speaking Francoprovençal, a set of Gallic-Romance varieties spoken in Aosta Valley, in Piedmont and in two villages in Apulia, Faeto and Celle San Vito. The purpose of this article is to analyse these two communities, outlining the diachronic evolution of the minority language diffusion and use, which is correlated to the macro-sociolinguistic frame of each community. Moreover, these scenarios are used to reflect on the forms of conservation and revitalisation that need to be put in place.
Method for Integrating Measuring Systems of a Space Unmanned Aerial Vehicle

In this paper, the simple criteria for choosing the working contour of navigation systems during the flight of space unmanned aerial vehicles in a changing noise environment are proposed. Within the framework of a given control system and taking into account the logic of its operation, a route correction system has been built, which ensures that the unmanned aerial vehicle is brought to a given area of space with the required accuracy. Criteria for choosing the working contour of the navigation complex during the flight of an unmanned aerial vehicle, based on the analysis of estimations of the variances of the measurement and reduced measurement noise, are proposed. Simulation of a test mathematical model of INS errors with various external sources of information, as well as simulation based on the data of a laboratory experiment, has been carried out. Analysis of the simulation results showed that the developed algorithmic methods make it possible to increase the efficiency of the navigation systems of an unmanned aerial vehicle when it operates in various jamming conditions.