Reviewerly/exHarmony huggingface dataset:
PENINGKATAN HASIL BELAJAR SISWA MELALUI MODEL QUANTUM TEACHING BERBANTUAN MEDIA APLIKASI EDMODO PADA SISWA SEKOLAH DASAR

This study aims to describe the improvement of teacher teaching skills with the application of the Quantum Teaching model assisted by edmodo application media and describe the improvement of student learning outcomes in social studies content and Indonesian language class IV SDN Doropayung 01.The research method used is classroom action research. This research was conducted in two cycles, each of which consisted of planning, action, observation and reflection. The subject of the research is the fourth grade students of SDN Doropayung 01 with a total of 20 students. The data source of this research is the teacher, students. Data collection techniques include interview, observation, test and documentation techniques. Data validity uses expert judgment techniques and data analysis used is qualitative and quantitative data analysis.The results showed that the Quantum Teaching model assisted by edmodo application media can improve teacher teaching skills, student learning outcomes aspects of knowledge and skills. Teachers' teaching skills showed an increase in which in the first cycle obtained a score of 80 and the percentage of success of 80% with a good category, then in the second cycle scored 86 and the percentage of success by 86% with very good criteria. Student learning outcomes have increased aspects of knowledge, the social studies content of the first cycle 70% and cycle II to 83%. Furthermore, on the Indonesian content the percentage of classical completeness of students in the first cycle was 70%, then increased in the second cycle to 77%. Student learning outcomes in the aspect of skills also increased, in the first cycle of 78%, then in the second cycle increased significantly to 83% with a very good category.
PENERAPAN KEAMANAN REMOTE SERVER MELALUI SSH DENGAN KOMBINASI KRIPTOGRAFI ASIMETRIS DAN AUTENTIKASI DUA LANGKAH

Abstract - System security is an absolute requirement that must be considered by users, especially network administrators to protect data. Every time a system is maintained and monitored, an administrator requires remote access such as a secure shell (SSH) to enter the system with a secure channel. By default, SSH is not secure because there is a great chance that the account will be taken over by brute force techniques. The application of asymmetric cryptography on SSH accounts is considered safe than SSH remote login by default. However, this is still not enough because hackers could control the computer that is used by administrators to do remote servers. It also can be hacked with key scanning techniques. The combination of asymmetric cryptography and two-step authentication can be a solution so that the server will be very difficult to penetrate.Keywords - Server Security, SSH, Asymmetric Cryptosystems, Two-Step Authentication.Abstrak - Keamanan sistem menjadi syarat mutlak yang harus diperhatikan oleh pengguna, khususnya administrator jaringan guna melindungi data. Setiap melakukan pemeliharaan dan monitoring sistem, seorang administrator membutuhkan akses masuk dengan cara remote seperti secure shell (SSH) ke dalam sistem dengan saluran yang aman. Secara default, SSH tidak aman karena berpeluang besar akun diambil alih dengan teknik brute force. Penerapan kriptografi asimetris pada akun SSH dinilai aman daripada remote login SSH secara default. Akan tetapi hal tersebut masih belum cukup karena bisa saja peretas justru mengendalikan komputer yang digunakan oleh administrator dalam melakukan remote server. Selain itu juga dapat diretas dengan teknik key scanning. Kombinasi kriptografi asimetris dan autentikasi dua langkah dapat menjadi solusi sehingga server akan sangat susah ditembus.Kata Kunci – Keamanan Server, SSH, Kriptografi Asimetris, Autentikasi Dua Langkah.
Split Over-Training for Unsupervised Purchase Intention Identification

Recognizing user-expressed intentions in social media can be useful for many applications such as business intelligence, as intentions are intimately linked to potential actions or behaviors.This paper focuses on a binary classification problem: whether a text expresses purchase intention (PI) or not (non-PI).In contrast to existing research, which relies on labeled intention corpus or linguistic knowledge, we proposed an unsupervised method called split over-training for the PI identification task.Experiments on PI identification from tweets showed that our approach was effective and promising.The best classifying accuracy of 84.6% and PI F-measure of 70.4% was achieved, which are only 7.7% and 4.9% respectively lower than fully supervised models.This means our unsupervised method may provide reasonable preprocessing for intention corpus labeling or intention knowledge acquisition.
Banka kimlik doğrulayıcı cihaz için kaotik osilatör tabanlı rasgele sayı üretecinin kriptanalizi

In this study, cryptanalysis of a non-equilibrium point chaotic oscillator based random number generator (RNG) that developed as a high security authentication tool for internet banking systems is presented. The security vulnerabilities of the algorithm that generates random bits by using the digits of floating-point numbers have been analyzed and the convergence has been shown by using the master slave synchronization scheme. Simulation and numerical results of the proposed method confirm that both next bit and output bit stream are predictable. Therefore, producing random numbers by using such an algorithm for the authentication tool is very unsecure and master slave synchronization cryptanalysis method is useful to validate chaotic systems.
The Effects of Team-Based Learning Education on Critical Thinking, Interpersonal Relationships, Self-Leadership and Academic Major Satisfaction

This study was conducted to develop and evaluate the effects of Team-Based Learning (TBL) education program, in the college course "Theory of Nursing Process, on critical thinking, interpersonal relationships, self-leadership and academic major satisfaction among nursing college students.The methodology used in this research is an experimental study of one group pre-post-test design, which was designed to check the difference before and after intervention through TBL education program to the treatment group.The participants in this study are second-year nursing students at H University in J city, South Korea.From March 24, 2019, to June 15, 2019, TBL education program was applied to "Theory of Nursing Process" classes 2 hours per week, 10 weeks in total.The collected data was analyzed with descriptive statistics and paired t-tests using the SPSS win 21.Program.The effects of TBL educational program on critical thinking ability, interpersonal relationships, self-leadership and satisfaction toward the nursing major were statistically significant, as follows: critical thinking ability (t=-4.09,p=.000),interpersonal relationship(t=-3.35,p=.001),self-leadership (t=-3.48,p=.001)and major satisfaction(t=-2.47,p=.016).The above findings confirm that the application of team-based learning in nursing education can positively affect critical thinking, interpersonal relationships and self-leadership among nursing students, and increase academic major satisfaction.
Predicting Tap Locations on Touch Screens in the Field Using Accelerometer and Gyroscope Sensor Readings

Research has shown that the location of touch screen taps on modern smartphones and tablet computers can be identified based on sensor recordings from the device’s accelerometer and gyroscope. This security threat implies that an attacker could launch a background process on the mobile device and send the motion sensor readings to a third party vendor for further analysis. Even though the location inference is a non-trivial task requiring machine learning algorithms in order to predict the tap location, previous research was able to show that PINs and passwords of users could be successfully obtained. However, as the tap location inference was only shown for taps generated in a controlled setting not reflecting the environment users naturally engage with their smartphones, the attempts in this paper bridge this gap. We propose TapSensing, a data acquisition system designed to collect touch screen tap event information with corresponding accelerometer and gyroscope readings. Having performed a data acquisition study with 27 participants and 3 different iPhone models, a total of 25,000 labeled taps could be acquired from a laboratory and field environment enabling a direct comparison of both settings. The overall findings show that tap location inference is generally possible for data acquired in the field, hence, with a performance reduction of approximately 20% when comparing both environments. As the tap inference has therefore been shown for a more realistic data set, this work shows that smartphone motion sensors could potentially be used to comprise the user’s privacy in any surrounding user’s interact with the devices.
ProbAnch: a Modular Probabilistic Anchoring Framework

Modeling object representations derived from perceptual observations, in a way that is also semantically meaningful for humans as well as autonomous agents, is a prerequisite for joint human-agent understanding of the world. A practical approach that aims to model such representations is perceptual anchoring, which handles the problem of mapping sub-symbolic sensor data to symbols and maintains these mappings over time. In this paper, we present ProbAnch, a modular data-driven anchoring framework, whose implementation requires a variety of well-orchestrated components, including a probabilistic reasoning system.
Quantum Key Distribution: A Safer Alternate To Asymmetric Key Exchange Policies

The encryption process of Symmetric Key Cryptography is quicker as compared to Asymmetric Key Cryptography, but the key exchange process is a challenge.This paper focuses on Quantum Cryptography techniques for that purpose as traditional digital cryptography techniques are not safe.In "Quantum Key Exchange" Technique, "Heisenberg uncertainty principle" and "quantum no cloning theory" are used to resist attacks.The Quantum Key Exchange is demonstrated through BB84 algorithm and the result is analyzed.Discussion is made on the practical applications of the technique
Hardware Implementation of Compressed Data Packing

Data compression algorithm based on the usage of different length code for symbol representation may be effective only if output stream is tightly packed. Hardware realization of these procedures has definite advantages in comparison with the software execution. Structures of devices that provide fast packing and decoding messages encoded according Huffman and similar algorithms are presented. Messages may be packed into dense bit sequence or word-by-word sequence. Both forms are discussed.
Attendance Marking System using Facial Recognition

Marking attendance is of significant importance in many places such as classrooms, conferences, or even prisons.It is possible to have a system (application) which marks attendance of people with least possible human intervention.This paper discusses on the face recognition methodologies using the concepts of image processing, computer vision and machine learning.The system is implemented using two different feature extraction techniques namely Histogram of Oriented Gradients (HOG) and Principle Component Analysis (PCA).The HOG features are classified using Support Vector Machine (SVM) classifier.Euclidean distance is used for classification in the case of PCA.The process of face detection is performed using Viola-Jones algorithm.Real-time or live facial recognition is also possible in the said system using HOG feature extraction and SVM classifier.The face detection and tracking in real-time face recognition is performed using Viola-Jones and Kanade-Lucas-Tomasi (KLT) algorithm respectively.
MuseoDabawenyo: An Interactive Virtual Reality Museum Application using Unity

The study aims to develop a virtual reality mobile application museum for those who are unable to visit Museo Dabawenyo in Davao City, Philippines.The virtual museum displays indigenous objects, artifacts, and old pictures of landmarks of Davao City.In this study, the three-dimensional user interface development methodology (TRES-D) was used to identify the roles, tools, and information needed for the development of the mobile app.This methodology allows a different set of tasks to be performed simultaneously during the development of the application.A 3D environment for the virtual reality museum is developed in unity.To create the digitized objects in the virtual museum, the software called Blender is used.The application allows the player to roam around the virtual museum and interact with the environment.The users are able to view information as to the object and pictures displayed within the virtual environment.
A strong feature representation for siamese network tracker

Because AlexNet is too shallow to form a strong feature representation, the trackers based on the Siamese network have an accuracy gap comparing with state-of-the-art algorithms. Both deep features and appearance features benefit tracking accuracy. To combine these two kinds features, the modified pre-trained VGG16 network is fine-tuned as one branch of the backbone network. Secondly, an AlexNet branch is attached after the third convolutional layer of VGG16. Thus the response maps from both branches are merged to form a preliminary strong feature representation with deep features and shallow appearance features. Thirdly, a new mean Peak-to-side ratio(mPSR) loss is designed to help network learn target features adaptively. A channel attention block and the Average-Peak-to-Correlation Energy(APCE) are designed to help select contributed features and suppress distractors. SiamPF only takes ILSVRC2015-VID as training dataset, but it achieves excellent performance on OTB-2013 / OTB-2015 / VOT2015 / VOT2016 / VOT2017 while maintaining the real-time performance of 41FPS on the GTX 1080Ti.
Criminality and the new information and communication technologies

This work aims to present concepts related to crime in the face of new information and communication technologies.Methodologically, articles and books were used in addition to the legislation dealing with the matter, in particular the Brazilian Penal Code and Law 12.737/12 (Carolina Dieckmann Law).The increasing advance of technology, in addition to providing convenience to people, has expanded the possibility of commitment of crimes.Some already covered by traditional legislation, others needing new classification.In this context, after presenting fundamental notions to understand the topicsuch as the concept of computer crime, classification, subjects and applicable legislation -, we sought to analyze some of the main computer crimes, especially the crime of computer device invasion.It was concluded that Criminal Law, in its purpose of protecting the most important legal assets, must act in order to curb the practice of computer crimes.In addition, despite the legislation covering a large part of the crimes committed on the network, the law must continue to update itself in the face of new threats, and the criminal offense of computer device invasion must be improved.Finally, it is addressed the difficulties related to the criminal investigation of this type of crime.
Multi-view Face Recognition Using Deep Learning

We present a technique for distinguishing objects in pictures utilizing a solitary profound neural system.Face acknowledgment is a PC vision issue that incorporates distinguishing faces in pictures.It is a straight forward errand for people to handle and conventional component based techniques, for example, the course classifier, have defeated genuinely well.All the more as of late , profound learning calculations have gotten best in class tests on standard face acknowledgment datasets.One model is the Convolutionary Neural Network, or MTCNN for short, Multi-task Cascade.Here in this venture we will find how to utilize traditional and profound learning models to lead face location in Python.Face recognition is a non-trifling issue with PC vision that distinguishes and finds faces in pictures.Utilizing the OpenCV programming, face acknowledgment can be accomplished utilizing the old style work based course classifier.Best in class facial recognition can be accomplished through the MTCNN library utilizing a Multi-task Cascade CNN.For both science and fiction facial acknowledgment has consistently been a difficult subject.A woman has hued her face, or wears a top to stow away.Profound learning errands for the most part expect numerous cases of a custom class to be taken care of for learning ( for example heaps of pictures of somebody).This permits the job of face acknowledgment satisfactory as preparing should be possible with a modest quantity of cases -there is just one shot of a person.Moreover, the presentation of new gatherings doesn't permit the example to imitate.In this article, we will work without any preparation a profound face acknowledgment model with Keras dependent on the ongoing work
Catching Cheats: Detecting Strategic Manipulation in Distributed Optimisation of Electric Vehicle Aggregators (Extended Abstract)

We consider a scenario where self-interested Electric Vehicle (EV) aggregators compete in the day-ahead electricity market in order to purchase the electricity needed to meet EV requirements. We propose a novel decentralised bidding coordination algorithm based on the Alternating Direction Method of Multipliers (ADMM). Our simulations using real market and driver data from Spain show that the algorithm is able to significantly reduce energy costs for all participants. Furthermore, we postulate that strategic manipulation by deviating agents is possible in decentralised algorithms like ADMM. Hence, we describe and analyse different possible attack vectors and propose a mathematical framework to quantify and detect manipulation. Our simulations show that our ADMM-based algorithm can be effectively disrupted by manipulative attacks achieving convergence to a different non-optimal solution which benefits the attacker. At the same time, our proposed manipulation detection algorithm achieves very high accuracy.
Analysis on Club Head Velocity versus Golf Handicap in Greenside Bunker

The purpose of this research study is to investigate the relationship between club head speed and golf handicap in relation to greenside bunkers.Biokin-Mobi sensor setup designed to capture three dimensional movement patterns of club head movements is employed in order to gather real time golf swing data.The angular velocity records captured during the greenside bunker shots are examined and correlated with handicaps of both skilled and amateur golfers.There is a significant difference between the club head speed of an elite and club head speed of an amateur golfers when executing greenside bunker shots.In particular, by examining peak velocities of the back and down swings, this study shows that club head speeds are valid indicators of golfers' performance measures.
Image Compression and Reconstruction using DOST and DCST

Image compression is a key step in the processing of images to reduce the data size and speed of image transmission and storage.Wavelets are usually said to be the innovative technique to compress the image, but the output of waves on smooth parts of the image is suboptimal.A new technique for image compression using Stockwell Transform is therefore being proposed.In this work MATLAB technical computing language is used to implement the proposed Stockwell Transforms.The quality parameters such as Mean Square Error, Peak Noise Ratio, Normalized Cross-correlation, Average Difference, Content Structural, Maximum Difference and NAE are computed to assess the methods.
Cryptocurrency: permanent money substitute or another temporary trend

Purpose: To identify that the cryptocurrency can be distinguished as a real-money equivalent in Kazakhstan in the near future.Methods: a SWOT (strengths– weaknesses– opportunities- threats) analysis supported with the results of a survey in Nur-Sultan city.Results: The majority of surveyed people claim that they refuse to use cryptocurrency due to its complexity and it demonstrably illustrates that people are not sure in new technologies’ potential, while the SWOT analysis proved that there certainly is a chance for the cryptocurrency to substitute money due to numerous possibilities.Conclusions: Undoubtedly, the cryptocurrency is capable to carry out ordinary cash’s functions and fully supplant it in the nearest future, offering such focal points as mechanized tax collection, robotized protections, and becoming globally acknowledged money. Although there are several obstacles as the cryptocurrency’s instability, administrative weight, and unwillingness of individuals to its integration into our everyday lives, the cryptocurrency can be a lasting money substitute, but the humankind needs more time to acknowledge it as the chief device.
Planning skills by heads of science departmentand academic performance in science subjects in public secondary schools in Nandi county, Kenya

Curriculum and instructional planning is important to ensure that academic activities run without interruption in an academic year or term. Heads of departments (HODs of Science) play a pivotal role in implementation of curriculum in secondary schools. Planning is one of the functions vested on HODs to ensure proper implementation of curriculum in their departments. This paper therefore looks at HODs planning skills towards academic performance improvement in three science subjects in public secondary schools in Nandi County, Kenya. The decision to choose HODs of science was due to the importance that is placed on science subject but which has recorded below average performance compared to other subjects in Kenya Certificate of Secondary School. The three science subjects under investigation are; Physics, Biology and Chemistry for secondary schools. The study used mixed method research design. The study had three target populations that comprised of 231 heads of departments, 231 principals and 693 teachers. The sample size of the study was determined using Krejcie and Morgan formulae of determining sample size and comprised of 23 principals, 128 HODS of science and 247 teachers who were selected through stratified random sampling. Data collection was through questionnaires and interview schedule. Analysis of data was performed through quantitative and qualitative methods. The correlation analysis was computed from HODs and science teachers’ data. The study discovered that most of them only planned for science practicals to be conducted on occasional basis by teachers in the department. Moreover, the HODs of Science ensured that the planned activities were conducted as planned. However, the HODs of Science were found not to have proper planning skills on ICT usage, acquisition of instructional material and conducting training needs assessment for teachers. The computed correlation statistics showed that there existed significant influence (p&lt;0.05) between planning skills by HODs of Science and academic performance of students in sciences in public secondary schools in Nandi County. The study recommends that HODs of Science need to be informed by Quality Assurance and Standards Officers (QASOs) that they need to be proactive and not reactive to the responsibilities under their docket. Participatory planning practices needs also to be embraced by HODs of Science for improved implementation and execution of set objectives and targets.&#x0D; Keywords: Planning, Skills, Quality, Performance, Sciences HODs