Reviewerly/exHarmony huggingface dataset:
Evaluation of Customer Satisfaction with Public Trans-portation in Yogyakarta

Yogyakarta is one of the cities that provides public transportation facilities to support the activities of its people in traveling. However, the use of public transportation is still a little in demand in Yogyakarta, whether it's because the desired travel route is not available, the tariff is not reasonable, the driver is reckless, or the physical condition of the vehicle is no longer suitable for use. Usually, after people use public transportation, the satisfaction that has been felt will appear. Therefore, a sentiment analysis study will be conducted to determine the value of customer satisfaction on the use of public transportation in Yogyakarta. This research uses social media twitter to get data. The data will identify an opinion or problem from someone whether it tends to be positive, negative, or neutral. The author uses the SentiStrength method to classify tweet data to get a value. This study will produce a summary of customer satisfaction values ​​that can be used as a reference in increasing customer satisfaction so that people are more interested in using public transportation in Yogyakarta.
Effect of Use of Numbered Heads Together Model Assisted by Powtoon Application on Learning Outcomes Indonesian Grade IV Students

One type of reading learning that is more emphasized for students is reading comprehension in elementary school. Problems related to reading the understanding of the theory of fictional texts so that learning outcomes are very low. Therefore, teachers provide treatment to elementary school students in Tempilang district of West Bangka Belitung Islands using the numbered heads together model assisted by powtoon applications. The Number Head Together model with the help of powtoon applications is good for cognitive achievement in learning outcomes so that learning can be meaningful. This study aims to analyze the influence of the use of the number heads together model assisted by powtoon applications on learning outcomes Indonesian fourth graders. This research uses quantitative experimental methods. The research design used is a type of One Group Pretest-Posttest Design. At the end of the learning process is measured about the material comprehension test. The sample purposive sampling amounted to 120 elementary school students in Tempilang Subdistrict. Data collection techniques in the form of observation and giving test questions. Data analysis techniques in quantitative research use statistics. There are two types of statistics used for data analysis in research, namely descriptive statistics and inferential statistics. The results showed that the use of the NHT model assisted by powtoon applications to learning outcomes Indonesian fourth grade students had an influence obtained, namely tcount 2,840 &gt; ttable = 1,669. Keywords: Reading Comprehension, Learning Outcomes, Powtoon-Assisted NHT Model .
A DUAL APPROACH TO DIGITAL AUDIO SIGNAL CRYPTOGRAPHY

Nowadays, the digital audio file is considered one of the most important digital data that requires good protection because it may be confidential or of a special nature. This research paper will present an easy-to-implement method to apply the protection process to a very high degree. We will implement this method to prove its efficiency by reducing the encryption and decryption time and thus increasing the throughput of the encryption process. We will calculate the quality parameters to ensure that the quality of the speech is achieved during the encryption and decryption phases passed on the obtained experimental values of MSE and PSNR. The new addition in this research is a proposed method for protecting audio files, which is implemented by following simple, specific, and effective steps to eliminate the disadvantages and defects associated with using DES-based methods, especially in encrypting-decrypting audio files.
Design of Mobile Docking Mechanism for Unmanned Aerial Vehicles capable of Vertical Take-off and Landing

Vertical Take-off and Landing (VTOL) Unmanned Aerial Vehicles (UAVs) enjoy a great majority of the UAV market with a wide variety of applications due to their low cost and time to set up and operate. Some of these applications demand continuous drone operations with minimal to no human intervention for routine activities such as recharging and maintenance. Very recently, ground-based UAV docking stations doing recharging or battery swapping autonomously have been seen as a potential way to address the need. However, there are still some applications, such as operations from a boat or an aerial platform, where there is no conveniently available stationary or steady base on which the docking station can be installed. Developing a moving docking station offers a new set of challenges along UAV guidance/navigation for precision landing on moving target, and along docking mechanism to align and secure the UAV for subsequent operations on the dock without errors. This paper describes some of the existing docking solutions and highlights their features. . A novel docking solution is proposed specifically designed keeping the unsteady motion of the platform into consideration. The mechanism is versatile in terms of type of the VTOL UAVs it can serve and in terms of platforms it can be implemented on. Tests were carried out using an off-the-shelf UAV and the mechanism was observed to be working as expected.
Face Authentication in Chat Application using Cryptography

Data plays a vital role in the world of computer network. There are many platforms to share data between a group of devices or individual or a group of peoples. Every person in the community needs him Information to keep safe from a third party. Here we have created a simple chat application with face authentication that can be used once to view end-to-end encryption authentication and shared message. This takes credentials to register and requires Face snap to authenticate the user. There are face snaps. Trained using the KNN Classifier. These face snaps are classified using the Haar cascade classifier algorithm for detection. User's face can be identified and logged in only if the user matches the credentials and can send messages. The receiving user is identified and the message is viewed.
Sentimental Analysis on YouTube Scrapped Data

In today’s world social media plays an important in every one’s life in which YouTube plays a vital role. In YouTube anyone can get the required information by specifying the search keyword. One can watch videos and give our opinion based on the content present in that video .YouTube is also a platform which can exhibit our own ideas and show case our talent by which people are getting many employment opportunities. Web scrapping is one of the techniques to scrape the information present in web pages. There are many techniques to scrape YouTube information like using Google API, Selenium python, pafy python, etc. In the proposed work we are scrapping the YouTube video information using paying generating the audience response based on the scrapped information.
Understanding the Effects of Ant Algorithms on Path Planning with Gain-Ant Colony Optimization

With the advent of more automated and unmanned systems, there is an increasing need for path planners. Intelligent path planners play an important role in the navigation of automated systems. In this work, the performance of an enhanced gain-ant colony optimization has been tested with the most popularly used ant algorithms – Ant system, Ant colony system and Min-Max ant system in the application of path planning. The pheromone update mechanism of traditional ant metaheuristic is enhanced with a local optimization mechanism and simulated with popular ant algorithms for an efficient choice of update rule. Evaluation is done using performance measures like path length and computation time taken. The results are statistically verified and analyzed. Path planned by proposed algorithm was found to be 3.25% shorter than existing algorithms.
STUDENT’S PERCEPTIONS TOWARDS THE QUALITY OF LIBRARY SERVICE AT THE COLLEGE OF PHARMACY MUHAMMADIYAH TANGERANG DURING THE PANDEMIC COVID-19

The purpose of this study was to determine students' perceptions towards the quality of library service at the College of Pharmacy Muhammadiyah Tangerang during the pandemic Covid-19. The research is a descriptive study with a quantitative approach. Assessment of the LSQA scale is used in this study to assess the quality of library services which include library infrastructure, library collections, library staff and library services. The research sample was 100 students using random sampling technique. The technique of data collection used was questionnaire distribution. While the technique of data analysis used is descriptive statistics with data processing using SPSS version 25. The steps in data analysis techniques are data presentation (table), measurement of central symptoms (mean, median and mode), calculating standard deviation, discussion and drawing conclusions. The results showed that the quality of library services at the College of Pharmacy Muhammadiyah Tangerang was very good with a score of 42%. Students' perceptions of library infrastructure have a score of 53%, library collections and library employees with each score of 44% and are considered very good by students. Meanwhile, students' perceptions of library services were considered good enough by students with a value of 44%. So that library services at the College of Pharmacy Muhammadiyah Tangerang need to be improved through service accuracy, service speed, IT support in the library and students can access information in the library easily.
PB1800: DEEPDECON: A DEEP-LEARNING METHOD FOR DETECTING MINIMAL RESIDUAL DISEASE OF ACUTE MYELOID LEUKEMIA

Background: Acute myeloid leukemia (AML) is a heterogeneous disease that the myeloid lineages of hematopoietic progenitor cells (blasts) lose the ability of normal differentiation and build up in the bone marrow. The ability to identify minimal residual disease (MRD) below the morphology-based 5% blast threshold has significant impact in clinical outcome. Flow cytometry and real-time quantitative polymerase chain reaction [qPCR]) are the most common methods for MRD detection while next-generation sequencing (NGS) is emerging as a more sensitive method. Aims: Here, we report DeepDecon, a deep neural network model that utilizes NGS RNAseq data to detect MRD of AML. Methods: DeepDecon makes use of the non-linear transformation among the latent layers and learns to extract high-order representations of the input gene expression. Meanwhile, DeepDecon doesn’t need to select a subset of genes. The neural network will optimize and assign different weights to all genes to minimize the prediction error. A challenging issue with deep learning models is the need for large data sets of diverse examples for model training to obtain robust and good performance. With single-cell RNAseq data, we digitally create a large number of bulk RNAseq samples with known AML fraction for model training. Results: When applied to clinical data TARGET-AML from GDC Data Portal (https://portal.gdc. cancer.gov/), DeepDecon demonstrated better performance than other machine learning algorithms, including MuSic, NNLS, Bisque, RNA-Sieve, and Scaden, for detecting MRD of AML. Summary/Conclusion: Deepdecon can be applied to clinical NGS data for accurate and sensitive detection of MRD in AML treatment. It will significantly improve the clinical outcomes of current AML therapy.
Alarmism vs Eschatology: Conceptual Analysis (On Material of Ukrainian Discourse)

The article studies and conceptualises alarmism and eschatology in the modern Ukrainian discourse. The approach to understanding the concept developed by G. Frege (“Fregean Thoughts”) was used as the theoretical basis for conceptualising these categories. The research interest of the paper is caused by the identification of the content of the conceptual levels of alarmism and eschatology. The results make it possible to define alarmism as a worldview sensation of an intuitive level that historically emerged from empiricism, reflecting the readiness to overcome the current global challenges. Eschatology arises as a doctrine that accepts the finiteness of individual and universal beings. The conceptualization of alarmism and eschatology allows us to conclude that, although both categories act as a means of characterizing the state of modern global society that has lost its intentions for its development, eschatology is looking for ways to reconcile with the inevitable approaching of “end of history”; the alarmism tries to mobilize the efforts of the global society to overcome the acute challenges of our time, gives one or another problem the status of serious.
Redesign and Analysis of Cargo Containers for Delivery Drone Applications

Drone or octocopter drone is a new generation innovation that can perform operations like surveillance, media, etc. with ease setup and cost-efficient. The delivery drone is the upcoming evolution in the field of engineering. The design of cargo containers attached to drones affects the parameters like the speed, efficiency, dynamics, and controls. The present work proposes a modified elliptical-shaped design instead of a regular rectangular cargo container. For lightweight and durability, carbon fiber as a material is also proposed. The shape was analyzed through computational fluid dynamics technique by using Ansys. The results of the study showed that the new ellipse shape design of cargo container is more practical to use in high-speed operation and results in increased efficiency of the system like drone.
UAV image signal transmission based on Eigenvector Analysis

Flight control signals of unmanned aerial vehicles (UAVs) are generally communicated by frequency hopping (FH) in spread spectrum mode. The detection method based on the back-end signal processing can not be widely used in frequency hopping signal detection and identification under different parameters, and has no practical value in engineering. In view of the above problems, this paper proposes a UAV communication technology based on image signal transmission, whose core content is sliding shift cyclic autocorrelation. The technology extracts the periodic characteristics of the internal cyclic prefix of OFDM signal, and establishes the characteristic database of multiple UAVs and Wi-Fi in advance. Compared with the traditional method, the recognition rate of the proposed method is 6. 74% higher than that of other methods, and the blind detection algorithm is 3. 1% better than that of other methods. It is verified that the proposed method can effectively prevent and solve the problems of frequency offset, system instruction update and surrounding electromagnetic interference. It contributes to the improvement of UAV signal transmission speed and performance.
OJT AtTRACK – On the Job Trainee Remote Attendance Monitoring System using Face Recognition System

The checking and monitoring of On-the-Job Trainee’s Attendance (OJT) faced several problems in the end of the OJT coordinators and the home institution. Some of the problems are checking the attendance of the OJT validation and verification of students’ attendance, tracking the students’ real-time OJT progress and generating up to date reports. It becomes even very alarming when the OJT Coordinators lost track the students’ OJT progress. This study sought to investigate and implement a solution using technology innovation mainly the internet of things to make checking of attendance and monitoring of progress effective and convenient. Using the Agile: Scrum methodology of software engineering, the researchers conducted a series of stakeholder’s meetings with the OJT coordinators to collect user stories. After the collection, the researchers developed a schedule of activities, staffing, hardware and software requirements in order to carry out all the tasks needed to deliver the fully functional product. To keep track the progress of the project, the Scrum master conducted a daily standup meeting with the team in order to express the points that might hinder the pace of the development. The team leader also communicates daily with the clients to give them a comprehensive update. Findings revealed that the current manual system used to check the OJT attendance and track OJT progress which is prone to fraud and tampering which causes record irregularities. Thus, there is a need to develop an internet of things based (IOT) based hardware and software application that checks the attendance and view reports in real-time. By this means, frauds on attendances and records were eliminated as the attendance system is secured. Keywords: Face Recognition, Internet of Things, Microcomputing, OpenCV, CoVid Response
An analysis of tasks of 5th and 6th grade English textbooks for the 2015 Revised National Curriculum in terms of core competency development

The purpose of this study is to examine the tasks in the 5th and 6th grade of the 2015 elementary English textbooks in terms of task design standard and core competency development, investigating the effectiveness and improvement of textbook tasks. For these purposes, in this study, a task analysis checklist reflecting four competencies and their sub-factors was developed to analyze 397 tasks of 5 types, 10 English textbooks for fifth and sixth graders. As a result, it was confirmed that the distribution of tasks and the number of tasks among the five textbooks were relatively evenly arranged except for one textbook. It was also found that the selected tasks for each textbook included all four core competencies, but knowledge information processing competency was found to be very low in all textbooks compared to the other three competencies. As a result of the analysis of the distribution of sub-factors by core competency, it was found that all four competency task activities were concentrated on specific sub-factor activities, indicating that there was an imbalance between the sub-factors of competency.
Migration of Relational Database to Document Oriented Database

Relational databases that came into existence a long time ago have many advantages and disadvantages. To get rid of this limitation in relational databases NoSQL databases were introduced that mainly focus on high operations speed and flexibility in storing the data. To store large volumes of semi-structured data over distributed nodes without a predefined schema and query and aggregate the data very quickly, a document-oriented database can be used which is a type of NoSQL database. Some organizations that are currently dealing with relational databases would sometimes wish to migrate from relational to document-oriented databases. Hence there is a need for integrating the relational databases into NoSQL databases.
Redefining Online Reading Behaviour among Malaysian Young Adults

The reading trend among young adults has changed from reading printed materials to reading online. These led to significant changes in their reading habits, attitudes, and interests, This study was undertaken to investigate the online reading experiences of young adults in Malaysia.A mixed-method explanatory approach was adopted and data were analyzed using Drouilard's (2009) framework to identify their reading experiences. The results showed some critical implications such as factors identified as motivation to read intrinsically and types of reading materials. It is hoped that more research regarding the multidimensionality of reading among Malaysian young adults are conducted in the future. Keywords: reading experiences; reading habits; reading interests; habits, attitudes; young adults eISSN: 2398-4287 © 2022. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning &amp; Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v7i20.3379
Artificial Intelligence in Surveillance Camera

Artificial intelligence have played a great role in our daily life. AI have now been implemented in almost all the fields nowadays. It’s been decade since AI have taken over the cyber world. AI have been implemented traffic cameras to sense the violation of traffic of rules. The functionality of these camera is very limited. Many other nations have implemented these technologies according to their specification so that they can customize according to their need. These technologies have their own advantages and disadvantages. We need to calibrate these advantages so that we can use this AI technology. Recent incidents in India by applying these cameras have given many errors in the camera, that’s because it has not implemented in the correct manner. We need technologies that are specifically designed to match the conditions. Suppose if it is raining then we need to calibrate these cameras according to those conditions. The applications of the AI cameras and its uses are discussed.
Wavelet and Statistical Analysis of Milk Products, Fruits and Vegetables Intake in India

Milk products, fruits and vegetables intake are the main components of a healthy diet and have vitamins, proteins, minerals, fats and many more which help in fulfillment of daily energy need and protection from many diseases and disorders. Milk products, fruits and vegetables intake index decide the true development of any country, because healthy people can live happy and longer life and can play inportant role in the development of society and country. Wavelet transforms is a powerful and efficient tool which captures the localized time frequency information of the signal and suitable for analysing non-stationary and transient signals. The approximation represents average behaviour or trend of the signal, while detail represents differential behaviour of the signal corresponding to each level of decomposition. Milk products, fruits and vegetables data of India from Jan. 2013 to Aug. 2021 are taken as raw data. Wavelet transforms of this data is performed by software dyadwaves using Haar wavelet, decomposition level-5. Approximation is the slowest part of data and corresponds to the maximum scale value describes the trend of the signal. The statistical analysis of given data is also performed through skewness, kurtosis, standard deviation and correlation coefficients. The wavelet analytical results are strongly consistent with statistical analytical results of the milk products, fruits and vegetables intake.
Implementing Blockchain Technology in the IoT

The Internet of Things is a type of technology in which devices are connected to a network. Since all devices are connected to a single network, the is at risk of a cyberattack if the network is not protected. By deploying blockchain technology in any IoT system, you can secure your system and reduce its vulnerability to cyberattacks. While using an IoT platform based on blockchain technology 6 has valuable advantages, it is worth considering various alternatives between blockchain technologies. They all have their own limitations and are not suitable for all usage scenarios. This review lists some of the shortcomings of blockchain technology in this regard. In the course of this investigation of this review paper, we encountered various shortcomings of IoT that can be overcome by adopting different types of blockchain technology in -specific IoT systems. When adopting blockchain technology for a particular IoT system, you need to be able to perform systematic analysis to suit your needs and obtain the blockchain capabilities that are appropriate for that particular scenario.