Reviewerly/exHarmony huggingface dataset:
Shortcuts to adiabaticity for a qubit using detuning control

Abstract We derive shortcuts to adiabaticity for a two-level system using the detuning as sole control parameter while the Rabi frequency is kept fixed. We work in the adiabatic basis while we also employ a time-rescaling. The control function that we use is the time-derivative of the magnetic field angle relative to the z -axis. We find that a constant control attains adiabatic passage with perfect fidelity only at particular durations, which we call resonances. We also find that, if we use a control with appropriate on-off modulation, a perfect adiabatic passage is achieved for all durations exceeding the bound π/Ω, with Ω being the constant Rabi frequency. The advantage of the proposed methodology over previous works is that the detuning control obtained is continuous and monotonic. The present work may find applications in the field of quantum information. As an example we mention the problem of designing a CZ gate, which can be formulated as the problem of adiabatically controlling a two-level system using only the detuning.
Developing a semantic image model using machine learning based on convolutional neural networks

This paper describes the main areas of research in the field of developing computer models for the automatization of digital image recognition. The concept of the semantic image model is introduced and the implementation of the machine learning model for solving the problem of automatic construction of such a model is described. The semantic model consists of a list of objects represented in the image and their relationships. The developed model was compared to other solutions and showed better results in all but one case. The performance of the model is justified by the use of the latest achievements of machine learning, including ZNM, TL, Faster R-CNN, and VGG16. Much of the links represented in the image are spatial links, so for the model to work better, you need to use that fact in designing it, which was done.
Dual-Language Programme (DLP) implementation in Malaysian secondary schools: from the lenses of school administrators

The implementation of Dual-Language Programme (DLP) in the Malaysian education system has entered the fourth year since its inception. Resembling the previous educational policy, DLP emphasises the use of English as a means of instruction in the teaching and learning of Science and Mathematics. The execution of the programme requires the adherence of four main regulations, including schools’ readiness to implement DLP. This study surveyed 80 school administrators’ perception of the programme, the reasons the schools decide to take part in the programme, and the challenges encountered by the school in the programme. Questionnaire and interviews were used to collect data. Findings revealed that the school administrators have positive perceptions towards the DLP programme, where they believe that DLP should be continued, yet improvements are needed to make the programme more effective. In addition, the main reason that the schools decided to take part in the programme was because they perceived that the DLP as a means to develop and improve English language mastery among the students in particular as well as the teachers indirectly. The findings implicate that the implementation of DLP needs serious attention by the school administrators, that encompasses the resources and facilities provision, human resource development as well as DLP students’ welfare.
The effect of using dialogue conversation video in teaching listening comprehension at eight grade students of SMPN 2 Percut Sei Tuan

The aim of this research is to shows the student of listening skill in teachingcomprehension for improvement student in listening which was observed and analyzedfrom students of eight grade at SMP Negeri 2Percut Sei Tuan. The method applied in thisresearch was the quantitative method with the experimental research design. Thepopulation of this study was the students at eight grade at SMP Negeri 2Percut Sei Tuan.This study was conducted with two groups, namely experimental and control class. Thenthe researcher taught in the experimental class bylistening a video and listening oral andcontrol class taught by using lecturing method, practice, product learning. Aftertreatment, the researcher gave the post-test to both of classes. The score of post-test werecollected from written test. After the calculated by using SPSS V 22, tobserved = 4,451 >ttable= 2,010 in the significance level of 0.05 (5%) and the Sign. (2-tailed) is 0.000 < 0.05. Tosum up, the tobserved>ttable and the Sign. (2-tailed) < 0.05, it means that Hα is accepted. So,the researcher can be concluded that task-based learning It means that there was the effectof listening a video on students’ Listening Comprehension procedure text.
Cultivation for Volunteers for School Support toward Programming Education

For the starting of Programming education in elementary school from 2020, it is necessary to keep the people who has skills of technical programming, education and volunteer for children. These kinds of human resources should be ideally organized from the people who lives in the local area around the school. In this paper, several activities results to promote the programming education and the cultivating the staff of educational support have been reported. Through the analysis of questionnaire survey for participants of each event, validities and improvement of our activities have been discussed.
Proposal of multi-finger robot hand end-effectors with iris mechanism

In this paper, we propose a multi-finger robot hand with iris mechanism. This new robot hand is based on the iris robotic mechanism. Construction of the new robot that blades of iris robot hand which attached each finger are denuded outside of mechanism enables gripping the long target lying on its side, tiny target such as M3x5 bolt without height adjustment base. Then new robot hand can grip more kind target than a conventional iris mechanism robot hand.
MONITORING LAND SURFACE CONDITION TOWARD PESAWARAN DISTRICT USING WATERSHED SEGMENTATION METHOD

This research will produce a segmentation using watershed segmentation. This method will be used to segment the aerial image of an area in Pesawaran district. The image of Pesawaran district that will be taken is an image for the past 5 years, more precisely the image from 2015-2019. The accuracy of this experiment will be tested using a method called ROC (receiver operational characteristics) and studying the changes in the land surface from year to year using watershed segmentation, then the image will change into a color pattern that represents each area such as forest areas and human settlements.
Collision-free Robot Path Planning under Multiple Obstacle Conditions with Latent Space of cGANs

No matter their environment, it is important for robots to ensure safety and prevent malfunctions. An important aspect to robotics is therefore collision-free path planning. Conventional methods such as RRT and potential field have difficulty adapting to dynamically changing environments, and have high calculation cost for iterating or searching. In this research, we propose a new path planning method in which the latent space of Conditional Generative Adversarial Networks (cGANs) represents the workspace where the robot avoids obstacles, and a path is planned in this latent space. The selected path is then mapped to a path in joint space. Since the latent space is collision-free, path planning can be performed by connecting the start and the goal robot posture without iteration or searching processes. We confirmed that our single trained model can handle various types of multiple untrained obstacle conditions.
Construction of walking analysis system and data analysis

The rapid aging of the recent years, the number of patients in need of rehabilitation is increasing. However, the number of caregivers (P.T., O.T. et al) is in short supply, and various problems have been raised. Our laboratory aims to improve the environment by performing rehabilitation remotely, such as at home.
Mammographic Screening and Breast Cancer Management – Part 2

The anatomy of the breast is relatively simple compared to other anatomic areas. Parenchyma and fat make up most of the image on a mammogram. Additional common findings are various types of calcifications, skin and lymph nodes. This relative simplicity makes the breast a great starting point for the emergence of artificial intelligence (AI) algorithms as a first-line diagnostic tool that can potentially completely answer the clinical question being asked by the physician ordering the screening mammogram. Other emerging clinical algorithms can also identify a significant finding such as 98the presence of blood on a CT scan of the brain (Halon, 2015), but detecting that finding alone does not come close to a complete report for the CT brain scan. There are many other pathologies in the brain such as a stroke that would need to be commented upon for the study report to be complete. A breast cancer detection algorithm has the potential of producing essentially a complete report for the screening mammographic study, remembering, however, that the decision to proceed with a biopsy to prove cancer is made by a radiologist after additional diagnostic mammogram views and/or ultrasound are completed.
Learning la-sol-fa-mi, with Some Hints on Musical Grammar

The chapter details how singing solfeggio allowed students to experience melody as a kind of language and to acquire fluency in it from experience rather than conscious learning. To try to reimagine this pedagogical process, as well as to demonstrate how to decipher complex solfeggio manuscripts, the chapter surveys some of the ways in which a common stock pattern of syllables was realized in song. Examples from manuscripts show how singers transformed the syllables <italic>la-sol-fa-mi</italic> into countless versions of Gjerdingen’s Prinner schema, prefacing them with a <italic>sol/do</italic> or <italic>fa/do</italic> lead-in, continuing them with a <italic>la-sol</italic> half cadence or a <italic>mi/mi</italic> or <italic>la/mi</italic> modulation, dividing them into coherent grammatical units with internal punctuation, and combining their two locations to generate complex counterpoint. The chapter also touches on the treatment of the <italic>sol-fa-mi</italic> and its role within the Monte, Fonte, and Meyer schemas.
Minimum Description Length Revisited

This is an up-to-date introduction to and overview of the Minimum Description Length (MDL) Principle, a theory of inductive inference that can be applied to general problems in statistics, machine learning and pattern recognition. While MDL was originally based on data compression ideas, this introduction can be read without any knowledge thereof. It takes into account all major developments since 2007, the last time an extensive overview was written. These include new methods for model selection and averaging and hypothesis testing, as well as the first completely general definition of {\em MDL estimators}. Incorporating these developments, MDL can be seen as a powerful extension of both penalized likelihood and Bayesian approaches, in which penalization functions and prior distributions are replaced by more general luckiness functions, average-case methodology is replaced by a more robust worst-case approach, and in which methods classically viewed as highly distinct, such as AIC vs BIC and cross-validation vs Bayes can, to a large extent, be viewed from a unified perspective.
Photon Statistics Effects on a QRNG of Vacuum Fluctuations

Optical scattering enhances randomness characteristics, increases the chaotic behavior of coherent sources, broadens the distribution of photon statistics and makes it super-Poissonian which allows faster sampling compared to Poissonian.
중국 대학생의 강의 동영상 학습에서 이미지 분량이 학습 스타일에 따라 학습만족도와 학업성취도에 미치는 효과

The study experimentally analyzed the effect that the amount of Images and learners’ earning styless has on learning satisfaction and academic achievements of Chinese university students in video learning. For this study, 167first-year students of XingTai University in China were selected as experimental participants. The collected data were analyzed through Multivariate ANOVA (MANOVA), using a statistical analysis program SPSS 25.0.The results are as follows: First, it was found that there was a statistically significant difference in learning satisfaction and academic achievements according to the amount of images in video learning. The groups who were exposed to a large amount of images showed higher learning satisfaction and academic achievements than those to a small amount of images. Second, there was no statistically significant difference in the interaction effect of the amount of images and information input styles in terms of students’ learning satisfaction and academic achievements. On the other hand, the interaction effect of amount of images and information perception styles showed a statistically significant difference in students’ learning satisfaction and academic achievement. Particularly, the amount of images was found to have a significant impact on learning satisfaction and academic achievements of intuitive learners.
AN INVESTIGATION OF PRE-SERVICE TEACHERS' ABILITY IN LESSON PLANNING

Lesson planning is an important part of the teaching process. However, it becomes a problematic area especially for pre-service teachers since they did not have much experience on it. This paper reports on the result of a study aiming to investigate seven pre-service teachers’ abilities in lesson planning, how they create their lesson plan, in what aspects they are already good, and in what aspects they still need guidance or improvement. This present study employed a qualitative case study method with three data collection techniques, including: questionnaires, documents, and interviews. The data were collected from 19 participants, however, there were only seven participants who were willing to be interviewed for further investigation. As many as seven lesson plans written by seven pre-service English teachers were also collected and analyzed. The data from document analysis revealed that most pre-service teachers were good at formulating lesson objectives which were derived from basic competence. Besides, most pre-service teachers were also good at providing the teaching procedures into three stages (opening, main activity, and closing) with the detailed activities on each stage and the specific time allocation. Nevertheless, the findings also revealed that there were some aspects that still need improvements in terms of formulating lesson objectives which contain the complete ABCD (Audience, Behavior, Condition, and Degree) aspects, sequencing the activities in teaching procedures into the correct order, and also selecting assessment tools which congruent with the lesson objectives. For those reasons, their weaknesses in creating a lesson plan caused pre-service teachers encountered several difficulties in lesson planning.
Penerapan Algoritma Greedy Untuk Menentukan Rute Terpendek Antar Klinik Gigi Di Kota Medan Berbasis Mobile.

Dental and oral health is an indicator of public health. The presence of healthproblems in teeth and mouth leads to a decrease in individual health functions.Dental and oral health problems are caused by the habit of a person brushing teethunregularly. Many options can be made to get to the location where the nearestdental clinic is desirable, but there are circumstances where the planned dentalclinic is not open. Therefore it takes the shortest route to get to another dentalclinic. Data in the form of distance, time and route to get to the desired dentalclinic is taken from Google map, with a total of 10 vertices to apply to the map(maps). For the results of the map, an algorithm is used, in which case the Greedyalgorithm is used to solve the problem of finding the shortest route. Based on theresearch results from the dental clinic closest to the starting point is sought usingthe Greedy algorithm it generates the total distance, travel time and the pointpassed.
Research on educational assistance by educational humanoid

In previous research, we developed an educational humanoid robot Nicot for using humanoids in education. Nicotte is 126cm tall and weighs 15kg, making it much lighter for a humanoid robot. When humanoid robots are used in educational settings where there are many opportunities to interact with humans, a lightweight design of the robot body is required in consideration of safety. As the weight is reduced, the output of the actuator decreases, and it becomes difficult to mount the hand on the hand in terms of the output torque of the arm. However, when a humanoid robot conducts a lesson, it is necessary to have a communication ability using hand signs in order to easily transmit linguistic information. It is therefore an object of the present invention to manufacture a lightweight and hand-signable hand unit that can be mounted on a lightweight humanoid robot and to complete a control system.
Disaster Rescue System using Flying Vehicle and Small Robotic Swarm

We suggest the disaster countermeasures information gathering system using the flying vehicle and ground robots. In order to accurately and quickly collect information and find an escape route in a situation where infrastructure has been destroyed, we will efficiently operate flying vehicles and small robotic swarm on the ground. In this study, we have developed and improved a small robot to establish a system that acquires wide area information from the air with a drone and obtains local information with sensors of a ground robot carried by the drone. The small ground robot was actually manufactured using the rapid prototyping method.
EDUCATIONAL PROJECT TO CREATE AN AUTOMATED CONTROL SYSTEM OF THE GREENHOUSE COMPLEX

The article presents the process of design of educational project to create an automated control system of the greenhouse complex, which includes a controller with sensors, as well as a cloud server with a universal web-interface for displaying data from sensors. All developments within the framework of the research were carried out on the basis of modern, free-distributed technologies of the Internet of things. The use of these technologies made it possible to implement a working version of a prototype controller for monitoring parameters of the greenhouse complex, with the least expenditure of resources.
On the performance sound design of a stringed instrument by the control of the stiffness and mass of the component part

In this study, an experimental study on the difference of the playing sound of the electric guitar caused by the difference of the material of its component part was conducted. We changed the material of the pickguard of the electric guitar from the plastic one which is commonly used to the copper one. In the experiments, simultaneous measurements of the vibrational acceleration of its peg, pickguard, and the output voltage of the guitar with a constant plucking force of the strings were performed. It was found that the profile of the RMS value of the vibrational acceleration on the pickguard changed when the copper pickguard was used. In addition, the vibrational modes of the pickguard also became quite different ones by using the copper pickguard. In conclusion, it was determined that the sound quality is affected by the vibrational characteristics; these can be adjusted by varying the means by which the pickguard is attached to the guitar body.
Observing High Speed Periodic Motion of Living Things by Naked Eyes

This paper proposes a new Strobe Imager that can make us to observe the high speed periodic motion of living things by naked eyes. The system is composed of miniature compressor, magnetic valve for controlling the periodic air puff, and LEDs for visualization by naked eye. This new version enables us to change the frequencies and duty factors independently for air puff and LED strobe, so that we can tune up the best condition for observing the dynamics of human skin, for example. This report shows the basic design and structure of the system and show a couple of experimental results.
Miniaturization of Light Devices using Plano-convex Lens and Verification of Canine Outside Guidance by Spotlight Guidance Suit

Our research is canine guidance using spotlights. Using dogs' habit following light, a spotlight guidance suit can remotely guide dogs by switching spotlight irradiation. The problem was that the spotlight devices were long and could get caught in the dog's surrounding environment. In this study, we considered lenses with different focal lengths and shapes using an optical simulator to shorten the length of the spotlight devices. By using a short focal length and a plano-convex lens, we succeeded in shortening the spotlight device. In addition, we verified to guide canine outdoors using a spotlight guidance suit. The difficulty of outdoor guidance is that people and animals walk around the field, and their movements and sounds attract the dog's attention. Also, we examined whether the dog could follow the spotlights even in a bright outdoor environment. As a result, we succeeded in the outdoor navigation.
Scalable Genuine multipartite Entanglement with Parametric Amplifier Networks

We propose a scheme to generate scalable genuine multipartite continuous-variable entangled light using a parametric amplifier network. We show the presence of genuine quadripartite, hexapartite, and octapartite entanglement through a violation of the PPT criteria.
Localization method of robot by TOF laser sensor and receiver

We propose a localization method for a mobile robot navigated by a TOF laser sensor on a pan-tilt actuator in a base station, and apply the method to a motion teaching interface for a caregiver robot. The position and orientation of the mobile robot can be estimated by measuring the pan-tilt angle, length of the laser beam as well as the laser spot position on a translucence screen equipped on the mobile robot using a camera. We conducted a simulation to verify the validity of this proposed method.
Constructing a Standard Model: Lessons from CHREST

Although it might be too early for a standard model of the mind (SMM), comparison between current cognitive architectures is a useful exercise. This article highlights some of the likely difficulties facing the development of a SMM – both empirical and theoretical. In particular, it follows Newell (1990) by arguing that a viable model of the mind must be constructed taking advantage of experimental constraints, based on comparisons of the model with (human or animal) data. We then describe our proposed methodology for ensuring a tight link between psychological data and a cognitive architecture. We also discuss CHREST, a cognitive model with a particular emphasis on modelling psychological results. CHREST has been applied in several domains, such as language acquisition and expertise. The article concludes by highlighting some of the features that distinguish CHREST from architectures such as Soar and ACT-R. Some of these differences are significant, creating challenges for a SMM.
A LEAP TOWARDS DEEP LEARNING FOR INVESTIGATING TOR TRAFFIC

TOR (The Onion Routing) is famous among the anonymous users over internet. Due to this anonymous presence of network activity it is very difficult for network surveillance .70-80% of illegal activities use multiple IP addresses which is provided in TOR .Now it’s very important to investigate our TOR network in order for providing cyber security. Now a model is proposed using deep learning and neural network for investigating TOR traffic by analyzing time based features