Reviewerly/exHarmony huggingface dataset:
Analysis of Benefits of the Irrigation Water Use Improvement Acceleration Program (P3-Tgai) on Improvement of Irrigation Network Infrastructure to the Regional Development at Hutagurgur Village, Regency of the Humbang Hasundutan

The research objective is to analyze the benefits of The Irrigation Water Use Improvement Acceleration Program to improve irrigation network infrastructure, increase functional land area and increase rice productivity and increase community income for regional development in Hutagurgur Village. The location of the study was carried out in Hutagurgur Village with a sample of all P3A Gurgur Indah members as recipients of the program. Research using descriptive methods with a quantitative approach. The results showed that the Irrigation Water Use Acceleration Improvement Program had a positive effect on improving irrigation infrastructure. Evidenced by the SPSS 23 program by increasing the length of the irrigation network significantly influence the increase in the area of functional land area of 8.25 Ha. The increase in functional land has a positive effect on increasing the productivity of paddy fields, which is significantly increased by 498.45 Kg/Ha/MT and in line with the average income of farmers which increased significantly by Rp.5,172,193.42Ha/MT.
PENGARUH PIJAT BAYI TERHADAP PERUBAHAN KADAR BILIRUBIN PADA NEONATUS HIPERBILIRUBINEMIA : Literature Review

Hyperbilirubinemia is the most common problem when a baby is born either at term or (preterm). Complications of hyperbilirubinemia will occur in neonatus if not treated properly. Literature review aims to decide the effect of giving the baby a massage to changes bilirubin levels in bbay hyperbilirubinemia. Literature review uses the method by searching journal articles using databases such as PubMed, Google Scholar, Willey Library, Garuda Journal, and Elsevier. After getting the article, the next step is filtering through various stages for it to be used as a literature review. The results of the search for journal articles are 220 after passing through 3 stages of filtering namely title, abstract, full-text content and the final result is obtained 8 journals. Of these 8 journals, it says that there are many benefits to the babies with hyperbilirubinemia if they given the baby a massage. Benefits such as, that it can ease defecation, provide restful sleep, and reduce bilirubin levels. Baby massage effective in neonate with hyperbilirubinemia as an intervention to do in the hospital. This baby massage is expected done a nursing intervention hyperbilirubinemia neonates.
A Novel approach for Securing Dicom Images Using Scrambling, PSO and DWT-SVD Domain Watermarking

Transmitting medical images over insecure communication channel requires a technique to provide integrity and privacy. This paper aims at proposing a novel watermarking technique to protect patient data in dicom images. Medical image is embedded with watermark logo by adopting Particle Swarm Optimization for selecting alpha parameter, Arnold image scrambling and descrambling and DWT Schur decomposition for watermark embedding.
LibGuides: LEGO® Buddies: Book Lists to Inspire Young Builders

LEGO® Buddies is a virtual program for elementary schoolers from Alamance County Public Libraries. This program meets once a month on Zoom. For more information and to join the group, contact Ms. Samantha at shunter@alamancelibraries.org.
Proof sheet of Moon Rock testing

Research School of Earth Sciences, Physical Sciences - Moon Rocks Analysis - Dr. B. W. Chappell, Mr. M. I. Vernon, Dr. W. Compston, Mrs. A. Brown, Prof. A. E. Ringwood, Dr. J. E. Lovering, Dr. S. R. Taylor, Dr. W. Compston, Mr. J. Pennington
Space Polyphony in the Poetry of Tramps

Literature is a deep sea of hollow, and no one went through it except and felt its splendor and greatness, and felt its sanctity and majesty, and between the crowding of ideas, and the exchange of words, this study came to unveil the polyphony of space in the poetry of the tramps as it is apparent because it deserves to stand on it by the multiplicity of voices in it due to the circumstances of the place, context and reference Which surrounded them and the effect of this trend of the text Tramp, so to speak. Polyphonia is a type of European music that appeared in the Romantic era as a movement of rebellion against classical music and polyphonic music that combines two or more melodies performed simultaneously by the human voice or instruments or both. This type of revolutionary music was considered a rebellion against Church music, so the authority of the Church was directed to the polyphony, similar to the criticism that Plato addressed in the laws to the music distributed on two lines, and the Catholic Church was concerned about polyphonic music due to the prevailing belief from a large number of Christian leaders, that music shakes faith and creates ambiguity in the verbal text and generates confusion instead of establishing a feeling of peace during the performance of rituals.
Pengembangan Media Pembelajaran Video Pada Patient Safety Virtual Education

The advancement of educational technology necessitates the use of technologically qualified learning media. Video-based learning is one of the learning tools that can help to create an engaging and enjoyable learning environment. This study aimed to develop a video learning media product for patient safety and virtual educational learning. The research design adapts the ADDIE development paradigm, which stands for Analysis, Design, Development, and Implementation, to apply the Research and Development technique. Material and media expert validation was carried out during the development stage by testing the instrument's usability. The trial was carried out by 124 students to see how they reacted as users. According to media and material specialists, video learning medium is valid and appropriate for use in virtual patient safety courses. The average value of 3.79 for user response to video learning medium indicates that there is a high level of interest in learning through the use of video. User response to video learning media by looking at learning interest with an average value of 3.79 means that there is a good interest in learning by using video media to be used in patient safety learning in virtual education. The use of engaging learning media such as films can boost student interest in learning and help them attain skills, which is especially important in virtual patient safety training. It is envisaged that the development can be completed at the evaluation stage, but it will need to be upgraded in order to present an actual simulation that students can understand.
Smart Gloves for Deaf and Dumb Students

The main objective of this project is to reduce communication barrier between normal people and special person who are not able to make a normal conversation be it a disabled one or dumb and deaf or palsied or any foreigner etc. As human Beings communicate and know each other through thoughts and ideas. The best way to present your idea is through speech. But some people don’t have the power of speech; the only way to communicate with others is through sign language. The problem with sign language is that it is confined to the people who are also deprived of the power of speech. These people are often termed as deaf and dumb. We can say that it is limited to the same set of persons that cannot speak. So, there is a need of technology which reduces this gap through systems that converts sign language into speech.
American Sign Language Translation using Firebase

Sign language is the manual way of communication by the speech impaired people. They use hand gestures and expressions to express their thoughts. Thus it is hard for them to communicate with others. Our project provides a solution by converting the sign language to speech, helping speech impaired people to communicate with others. The Application uses the camera of the device to capture the sign and sends to a model hosted on FIREBASE and the matched sign is converted to speech by GOOGLE’S translator.
Pembelajaran Rest WEB Service Dengan Framework Springboot

Along with the rapid flow of information and communication as well as the increasing need for these two things, more and more media or information providers have emerged. The most important information for students or students' guardians is related to learning activities at school, such as information on grades, exam schedules, student attendance and others. Usually obtained when the school has announced it, and this information can be obtained only at the school. Currently, the development of programming languages ​​in Indonesia seems to be increasingly being carried out, including by educational institutions for the benefit of the teaching and learning process. In an effort to improve the efficiency of the development of programming languages ​​that contain elements of education, various alternatives and new innovations are needed in terms of making and developing programming languages ​​to be applied in the world of work for students. This is the basis for us to develop a WEB application-based information system using the SPRING framework which will be used as computer learning at SMKN 1 Depok and SMK Wira Buana 2 as a support for teaching and learning activities.
Semi-Supervised Siamese Network for Identifying Bad Data in Medical Imaging Datasets

Noisy data present in medical imaging datasets can often aid the development of robust models that are equipped to handle real-world data. However, if the bad data contains insufficient anatomical information, it can have a severe negative effect on the model's performance. We propose a novel methodology using a semi-supervised Siamese network to identify bad data. This method requires only a small pool of 'reference' medical images to be reviewed by a non-expert human to ensure the major anatomical structures are present in the Field of View. The model trains on this reference set and identifies bad data by using the Siamese network to compute the distance between the reference set and all other medical images in the dataset. This methodology achieves an Area Under the Curve (AUC) of 0.989 for identifying bad data. Code will be available at this https URL.
The content, essence and concept of the socio-pedagogical process in social pedagogy

We  will consider the different points of view of scientists on the definition of the concept of and pedagogical activity, the article examines in detail the approaches to defining the essence and content of the social and pedagogical process
Agricultural Policies, Schemes and Funding: Media Responsibilities to Achieving the Sustainable Development Goals in Nigeria

Agricultural policies and schemes are some of the measures through which the Nigerian government has attempted to address some of her challenges in the agricultural sector. Despite the MDGs/SDGs programs, Nigeria is still faced with extreme poverty, hunger, and poor education. Nigeria’s budgetary allocation is still far from meeting international recommendations of 25% by FAO. Laudable and well thought out agricultural schemes such as “Operation feed the nation”, “Green Revolution”, “River Basin Development”, “Agricultural Development Project” etc were government policies and schemes geared towards the provision of agricultural solutions. If objectives of the SDGs be realized in the country, issues of corruption, insecurity, proper education, and awareness creation etc., must be addressed by all stake holders ranging from the financial sector, the government as well as the mass media. The media are faced with challenges of news policies, brown envelops, loss of job opportunities etc., while most youths lack awareness and proper education about agricultural schemes and funding in Nigeria.
3D Point Filtering Algorithm for 3D Object Detection Based on Stereo Image Processing

Unlike LIDAR-based 3D object detection algorithms, stereo-based 3D object detection algorithms have low performance. The main reason for this problem is the low accuracy of the 3D information predicted from stereo image processing. Inaccurate 3D information distorts the 3D shape of an object. Therefore, this study aims to improve the performance of the stereo-based 3D object detection algorithms by proposing a filtering algorithm that can filter out inaccurate 3D information. The filtering algorithm uses a 3D offset, which is the distance between a 3D point on an object and the center of gravity of the object. Since the object size is limited, the 3D offset length of the points constituting the object is always smaller than the object size itself. However, there is a case where the 3D offset length of inaccurate 3D information is larger than the object size. The proposed filtering algorithm filters out inaccurate 3D information to address this issue. This study experimentally proves that the filtering algorithm is effective in enhancing the stereo-based 3D object detection performance.
Role of Feature Engineering and Classifier Selection for Machine Learning Predictions

Features play a crucial role in several computational tasks. Feature values are input to machine learning algorithms for the prediction. The prediction accuracy depends on various factors such as selection of dataset, features and machine learning classifiers. Various feature selection and reduction approaches are experimented with to obtain better accuracies and reduce the computational overheads. Feature engineering is designing new features suitable for a specific task with the help of domain knowledge. The challenges in feature engineering are presented for the computational music domain as a case study. The experiments are performed with different combinations of feature sets and machine learning classifiers to test the accuracy of the proposed model. Music emotion recognition is used as a case study for the experimentation. Experimental results for the task of music emotion recognition provide insights into the role of features and classifiers in prediction accuracy. Different machine learning classifiers provided varied results, and the choice of a classifier is also an important decision to be made in the proposed model. The engineered features designed with the help of domain experts improved the results. It emphasizes the need for feature engineering for different domains for prediction accuracy improvement. Approaches to design an optimized model with the appropriate feature set and classifier for machine learning tasks are presented.
AN EFFICIENT METHOD FOR HAND GESTURE RECOGNITION USING ROBUST FEATURES VECTOR

Integration of technology for the Fourth Industrial Revolution (IR 4.0) has increased the need for efficient methods for developing dynamic human computer interfaces and virtual environments. In this context, hand gesture recognition can play a vital role to serve as a natural mode of interactive human machine interaction. Unfixed brightness, complex backgrounds, color constraints, dependency on hand shape, rotation, and scale variance are the challenging issues which have an impact on robust performance for the existing methods as per outlined in previous researches. This research presents an efficient method for hand gesture recognition by constructing a robust features vector. The proposed method is performed in two phases, where in the first phase the features vector is constructed by selecting interest points at distinctive locations using a blob detector based on Hessian matrix approximation. After detecting the area of the hand from the features vector, edge detection is applied in the isolated hand followed by edge orientation computation. After this, templates are generated using one and two dimensional mapping to compare candidate and prototype images using adaptive threshold. The proposed research performed extensive experimentation, where a recognition accuracy rate of 98.33% was achieved by it, which is higher as compared to previous research results. Experimental results reveal the effectiveness of the proposed methodology in real time.
An Automatic Group Formation Tool for Team- Based Learning Using Fuzzy K- means Clustering Method

The purpose of this project is to study the automatic group formation process for the lecturers and display it through an interactive dashboard using fuzzy clustering (k�means) that will enhance the students grouping system. The objectives achieved are first, to study and investigate the learning styles and personality traits of students. Second, is to develop an automatic tool for group formation based on learning styles and personality types using fuzzy clustering (k- means). One’s learning styles and personality traits influences the way they learn. Grouping a bunch of students with different types of learning styles and personality types is burdensome. Having a group with students that has both right learning styles and personality types will produce valuable results for a team-based learning experience. Hence, in this project, attempt was made to create an automated system that will form a group of students consisting right type of learners with right type of personalities.
Hamiltonian simulation algorithms for near-term quantum hardware.

The quantum circuit model is the de-facto way of designing quantum algorithms. Yet any level of abstraction away from the underlying hardware incurs overhead. In this work, we develop quantum algorithms for Hamiltonian simulation one level below” the circuit model, exploiting the underlying control over qubit interactions available in most quantum hardware and deriving analytic circuit identities for synthesising multi-qubit evolutions from two-qubit interactions. We then analyse the impact of these techniques under the standard error model where errors occur per gate, and an error model with a constant error rate per unit time. To quantify the benefits of this approach, we apply it to time-dynamics simulation of the 2D spin Fermi-Hubbard model. Combined with new error bounds for Trotter product formulas tailored to the non-asymptotic regime and an analysis of error propagation, we find that e.g. for a 5 × 5 Fermi-Hubbard lattice we reduce the circuit depth from 1, 243, 586 using the best previous fermion encoding and error bounds in the literature, to 3, 209 in the per-gate error model, or the circuit-depth-equivalent to 259 in the per-time error model. This brings Hamiltonian simulation, previously beyond reach of current hardware for non-trivial examples, significantly closer to being feasible in the NISQ era. The way quantum simulation algorithms are translated into specific hardware implementations often translates into additional overhead. Here, the authors improve the efficiency of Hamiltonian simulation using a method that allows efficient synthesis of multi-qubit evolutions from two-qubit interactions.
Modern nomads: education on the way

The study is based on the scientific idea of the need to organize the education of children of the indigenous peoples of the North, Siberia and the Far East of Russia, leading a nomadic lifestyle with their parents.Globalization processes taking place in the world pose new challenges for the peoples of Russia.Accordingly, the study and analysis of the practice of education of indigenous children in the places of their natural residence and habitual economic activity in Russia becomes relevant.The authors, taking into account the historical background, present the results of a study on the study of the current state of the education system for children of indigenous small peoples of the North, Siberia and the Far East, leading a nomadic lifestyle with their parents, which has a certain specificity; identifying the main trends and scenarios for modeling nomadic education in Russia.As a result of the study, methodological recommendations were prepared for organizing the education of children leading a nomadic lifestyle with their parents.
Bachelor Graduation Project Tracheo-esophageal speech enhancement: Input and filter

Every year an unfortunate part of the population lose their larynx, often due to the consequences of cancer. The laryngectomy removes the possibility to speak. Fortunately several speech reinstatement techniques have been found. However, all current speech reinstatement techniques do not produce a lot of volume. As a result the laryngectomised person will have difficulties speaking in busy environments, up to the point were the condition can lead to isolation because of the inability to communicate. Moreover with the current methods it costs a lot of energy to speak, the produced speech is less stable and the fundamental frequency has become lower. In this thesis a device is designed to improve the speech produced by a laryngectomised person realtime. The speech is recorded with an electret microphone. The resulting signal is prepared to be quantified to then be processed by a digital signal processing unit. Then the signal is adaptively filtered using the dynamically determined fundamental frequency. By tracking the fundamental frequency some instability from the voice is removed. The fundamental frequency will be determined using the cepstrum, a technique separating the fundamental regency of a voice from the high frequency components added by the oral and nasal cavities during speech. In another thesis a system is designed to amplify the signal to make sure that speaking takes less energy \cite{shiftgroep}. Furthermore a suitable power source is determined for the system. As the system is designed for Tracheo-Esophageal Speech Signal Amplification, the system will be referred to as TESSA.
RANCANG BANGUN APLIKASI SISTEM REGISTRASI DAN PENJADWALAN SERTIFIKASI BERBASIS WEB MENGGUNAKAN METODE ALGORITMA FISHER YATES SHUFFLE (STUDI KASUS: LABORATORIUM ITCC STT-PLN)

The International International Technology Certification Center (ITCC) is one of the implementing agencies for certification at the STTPLN academic community to support certification activities in the IT field. In the process of registration and scheduling, it still takes more than one week. Because it still uses the manual method of scheduling certification groups. Therefore, to overcome these weaknesses, a web-based registration and scheduling application is designed. The method used in the development of this system is the Fisher Yates Shuffle method with the testing method using Black Box Testing.
Solid waste classification using pyramid scene parsing network segmentation and combined features

Solid waste problem become a serious issue for the countries around the world since the amount of generated solid waste increase annually. As an effort to reduce and reuse of solid waste, a classification of solid waste image is needed to support automatic waste sorting. In the image classification task, image segmentation and feature extraction play important roles. This research applies recent deep leaning-based segmentation, namely pyramid scene parsing network (PSPNet). We also use various combination of image feature extraction (color, texture, and shape) to search for the best combination of features. As a comparison, we also perform experiment without using segmentation to see the effect of PSPNet. Then, support vector machine (SVM) is applied in the end as classification algorithm. Based on the result of experiment, it can be concluded that generally applying segmentation provide better source for feature extraction, especially in color and shape feature, hence increase the accuracy of classifier. It is also observed that the most important feature in this problem is color feature. However, the accuracy of classifier increase if additional features are introduced. The highest accuracy of 76.49% is achieved when PSPNet segmentation is applied and all combination of features are used.