Reviewerly/exHarmony huggingface dataset:
Blockchain feasibility assessment: A quantitative approach

This article outlines the research and development of a blockchain assessment framework which enables the assessment of the technical suitability, high-level design, adoption approach, economic feasibility, and business value potential of a blockchain solution with a particular organization for a specific process. The framework is a comprehensive, high-level, and generic assessment approach that enables better decision-making regarding blockchain exploration. Blockchain is a novel technology with the potential to disrupt several industries through its possession of many desirable functional characteristics, including, but not limited to, immutability, transparency, decentralization, and secure. Cryptocurrencies and these desirable characteristics have created hype around blockchain, consequently leading to blockchain projects with minimal understanding of what the technology is capable of and beneficial for, resulting in excessively high failure rates. Attempts have been made by researchers to reduce these high failure rates by creating a better understanding of blockchain, as well as creating assessment approaches. However, these approaches tend to apply to specific narrow use cases, or the approach is not comprehensive and only considers one aspect of blockchain assessment. This emphasizes the need for a comprehensive and generic blockchain assessment approach to aid with better decision-making regarding blockchain within organizations. This article aims at addressing this need by creating a blockchain assessment framework to aids with deciding whether it is worthwhile investing more time, effort, and money into blockchain exploration. The context of the study is set in the introduction, this is then followed by a brief explanation of the blockchain technology. Thereafter, the blockchain assessment framework is presented, followed by a brief explanation of the demonstration and validation of the framework using a case study and expert analysis. The framework is most valuable during the initial stages of blockchain exploration and creates momentum for further blockchain exploration in an organization. The study concludes with the limitations and future research recommendations.
Private Sampling with Identifiable Cheaters

In this paper we study verifiable sampling from probability distributions in the context of multi-party computation. This has various applications in randomized algorithms performed collaboratively by parties not trusting each other. One example is differentially private machine learning where noise should be drawn, typically from a Laplace or Gaussian distribution, and it is desirable that no party can bias this process. In particular, we propose algorithms to draw random numbers from uniform, Laplace, Gaussian and arbitrary probability distributions, and to verify honest execution of the protocols through zero-knowledge proofs. We propose protocols that result in one party knowing the drawn number and protocols that deliver the drawn random number as a shared secret.
Fast Marching Techniques for Teaming UAV’s Applications in Complex Terrain

In this paper, we present a study on coverage missions carried out by UAV formations in 3D environments. These missions are designed to be applied in tracking and search and rescue missions, especially in the case of accidents. In this manner, the presented method focuses on the path planning stage, the objective of which is to compute a convenient trajectory to completely cover a certain area in a determined environment. The methodology followed uses a Gaussian mixture to approximate a probability of containment distribution along with the Fast Marching Square (FM2) as path planner. The Gaussians permit to define a zigzag trajectory that optimizes the path. Next, a first 2D geometric path perpendicular to the Voronoi diagram of the Gaussian distribution is calculated, obtained by skeletonization. To this path, the height above the ground is added plus the desired flight height to make it 3D. Finally, the FM2 method for formations is applied to make the path smooth and safe enough to be followed by UAVs. The simulation experiments show that the proposed method achieves good results for the zigzag path in terms of smoothness, safety and distance to cover the desired area through the formation of UAVs.
LOGICAL ANALYSIS OF SYMBOLIC CONCEPTION REPRESENTATION IN TERMINOLOGICAL SYSTEMS

Cognitive, or knowledge, agents, who are in some way aware of describing their own view of the world (based on their mental concepts), need to become concerned with the expressions of their own conceptions. My main supposition is that agents’ conceptions are mainly expressed in the form of linguistic expressions that are spoken, written, and represented based on e.g. letters, numbers, or symbols. This research especially focuses on symbolic conceptions (that are agents’ conceptions that are manifested in the form of their symbols). I attempt to logically (and using CLSYM) analyse symbolic conceptions in terminological systems. CLSYM is an assertional fragment of my developed Conception Language (CL), which is utilised as a formal-logical system for representing and explicating agents’ conceptions of the world.
Sign Language Recognition by Similarity Measure with Emotional Expression Specific to Signers

Through technology, it is essential to seamlessly bridge the divide between diverse speaking communities (including the signer (the sign language speaker) community). In order to realize communication that successfully conveys emotions, it is necessary to recognize not only verbal information but also non-verbal information. In the case of signers, there are two main types of behavior: verbal behavior and emotional behavior. This paper presents a sign language recognition method by similarity measure with emotional expression specific to signers. We focus on recognizing the sign language conveying verbal information itself and on recognizing emotional expression. Our method recognizes sign language by time-series similarity measure on a small amount of model data, and at the same time, recognizes emotion expression specific to signers. Our method extracts time-series features of the body, arms, and hands from sign language videos and recognizes them by measuring the similarity of the time-series features. In addition, it recognizes the emotional expressions specific to signers from the time-series features of their faces.
Badminton stroke classification based on accelerometer data: from individual to generalized models

Activity recognition models based on wearable devices are becoming increasingly popular. However, models that are trained and tested on the same players show a large bias and are not generalizable to previously unseen players. In this paper, we tackle the badminton stroke recognition problem from this perspective, comparing the performance of individual and generalized models based on an accelerometer and a gyroscope, and identifying which components of the solution can maximize the performance of generalized models. First, we describe a simple convolutional neural network trained to classify 7 types of stroke. Second, the model is extended in a hybrid way to identify two additional classes (movement and rest). Third, data augmentation is applied on the training set. Fourth, transfer learning is applied to use data from the test player to fine-tune the generalized model and attempt to reach the performance of an individual model. These models are evaluated on a dataset collected from amateur players, both in a controlled environment and in a match simulation. The results showed a large difference between the performance of individual and generalized models; however, the latter could be improved by increasing the number of players in the training set, by data augmentation, and by transfer learning, highlighting the necessity of larger datasets in this field.
Underwater target maneuver detection algorithm based on width learning

For underwater target tracking in the process of data sample size less problems, combining with the characteristics of the sample quantity required width of lower learning network this paper proposes a new mobile detection algorithm, existing maneuver detector algorithm in the test statistic to construct the network characteristic vector, training, through the network to network of incremental learning method reduces the detection delay. Simulation results show that the algorithm can calculate more accurate network weight coefficients after training with a given simulated track, and can give the possibility of the target in maneuver mode and non-maneuver mode in real time during tracking, which greatly improves the real-time performance of maneuver detectionn high-velocity projectile penetration into underwater targets.
A Non-technical Introduction to Machine Learning

Abstract This chapter provides an introduction to machine learning for a non-technical readership. Machine learning is an approach to artificial intelligence. The chapter thus starts with a brief history of artificial intelligence in order to put machine learning into this broader scientific context. We then describe the main general concepts of machine learning. Readers with a background in computer science may skip this chapter.
Dekomposisi bahan organik pada sedimen di Tukad Mati dan Tukad Badung, Bali

The sediment properties of Mati and Badung River, Bali were observed in this study. This study was aimed to know the relation between carbon, nitrogen and total bacterial number in the sediment of those rivers. This study was carried out in Mati and Badung River located in Southern part of Bali, Indonesia. Total carbon (TC), total nitrogen (TN), and total bacterial number of the sediment were observed in this study. Slow stirring method was used to estimate the total bacterial number in sediment, based on their environmental DNA intensity after agarose gel electrophoresis. TC of sediment was analyzed by using total carbon analyzer after combustion at 900oC, while TN was analyzed by using indophenol blue method after digested using Kjeldahl at 420oC for 1.5 hours. The result showed that TC of sediment in the Mati and Badung River were 6,100 and 7,000 mg/kg, respectively. TN of sediment in the Mati and Badung River were 380 and 440 mg/kg, respectively. The pH and electrical conductivity (EC) of sediment in the Mati River were 6,88 dan 0,10 µs/cm, while in the Badung River were 6,80 dan 0,11 µs/cm. Total bacterial number in the Mati river was lower (4.8 × 108 cell /g) than that in the Badung river (3.8 × 108 cell/g). The high value of R2 between total bacterial and TC (0.91), and between total bacterial number and TN (0.83), indicating the high influence of bacteria on the decomposition of organic materials in the sediment.
THE EFFECT OF SCRAMBLE METHOD ON STUDENTS’ ACHIEVEMENT IN LEARNING VOCABULARY

The objective of this research was to find out the significant effect of the scramble method on students’ achievement in learning vocabulary. The experimental design was used as the research design. The population of this research was taken from the eighth-grade students of SMP Al Washliyah 8 Medan. There were 7 parallel classes with a total number of 231 students. Each class consisted of 33 students. The sample was taken by applying cluster random sampling with the lottery technique. Class VIII1 consisting of 33 students was selected as the experimental group and class VIII3 consisting of 33 students was selected as a control group. The total sample was 66 students. The experimental group was taught by applying the scrambling method, while the control group was taught by applying the conventional method. Multiple-choice tests containing vocabularies were used as the instrument for collecting the data. The mean score of the experimental and control groups were then compared and calculated. The value of both groups then was tested using the t-test formula. It was obtained that that tobserved value was higher than ttable value (7.25 1.66) at a level of significance =0.05 with a degree of freedom df=58. Based on the determined hypothesis, it meant that Ha was accepted and Ho was successfully rejected. Thus, it was concluded that there was a significant effect of the scramble method on students’ achievement in learning vocabulary.
Design and Implementation of a flexible Multi-purpose Cryptographic System on low cost FPGA

The design of cryptographic hardware that supports multiple cryptographic primitives is common in literature. In this work, a new design is presented consisting of a multi-purpose cryptographic system featuring both 128-bit pipelined AES-CORE (Advanced Encryption Standard) for high-speed symmetric encryption and a Keccak hash core on a low-cost FPGA. The KECCAK-CORE’s security and performance parameters are tunable in the sense that capacity, bitrate, and the number of rounds can be user-defined. Such flexibility enables the core to suit a large range of security requirements. The structure of Keccak’s sponge construction is exploited to enable different modes of operation. An example application outlined in this work is Pseudo Random Number Generation (PRNG). With few adjustments, the KECCAK-CORE was also operated as a post-processing unit for True Random Number Generation (TRNG) that uses the analog Lorenz chaotic circuit as a physical entropy source. The multi-purpose design was implemented in VHDL targeting an IntelFPGA Cyclone-V FPGA. For AES symmetric encryption, a maximum throughput of 31.1Gbps was achieved and a logic usage of 25146LEs (23% of the FPGA) in the case of the pipelined variant of AES-CORE. For the KECCAK-CORE, maximum throughput figures of 5.81, 8.4, and 11Gbps were achieved for the three SHA-3 variants 512, 384, and 256-bit respectively, with an area usage of 8947LEs (8%). The system as a whole occupies an area of 26909LEs (26%). The random sequences generated by the system operating in PRNG and TRNG post- processing modes successfully passed the National Institute of Standards and Technology (NIST) statistical test suite (NIST SP 800-22). The information entropy analysis performed on the post-processed TRNG sequences indicates an average of 0.935.
Representing affect information in word embeddings

A growing body of research in natural language processing (NLP) and natural language understanding (NLU) is investigating human-like knowledge learned or encoded in the word embeddings from large language models. This is a step towards understanding what knowledge language models capture that resembles human understanding of language and communication. Here, we investigated whether and how the affect meaning of a word (i.e., valence, arousal, dominance) is encoded in word embeddings pre-trained in large neural networks. We used the human-labeled dataset (Mohammad 2018) as the ground truth and performed various correlational and classification tests on four types of word embeddings. The embeddings varied in being static or contextualized, and how much affect specific information was prioritized during the pre-training and fine-tuning phase. Our analyses show that word embedding from the vanilla BERT model (Devlin et al. 2019) did not saliently encode the affect information of English words. Only when the BERT model was fine-tuned on emotion related tasks or contained extra contextualized information from emotion-rich contexts could the corresponding embedding encode more relevant affect information.
Face Recognition Based Attendance System

Abstract: Out of the most common uses for image processing is face identification, which is important in the technological field. Recognizing faces is a hot issue for verification, especially in student attendance competitions. A face recognition attendance system uses high-definition surveillance and other computer technologies to identify students using face biostatistics. The developing system aims to digitize the outdated method of calling names and maintaining pen-and-paper attendance records. The existing procedures for recording attendance are cumbersome and time-consuming. Manual recording allows for easy manipulation of maintenance records. Traditional attendance systems and current biometric technologies are subject to proxies. As a result, this study is proposed to address all of these issues.
The Constructivist Principle of Learning by Being in Physics Teaching

A detailed characteristic of teaching and learning approaches used within the new concept of Learning by Being (LBB) is given. The evolution of educational paradigms from Learning by Doing (LBD) and Learning by Understanding (LBU) toward LBB is analyzed. The basic idea of LBB is students’ ownership on cognitive goals, or the assumption of learning objectives, in other words – intrinsic motivation of students. Along with LBB, the author proposes the term of guided self-scaffolding. Both terms tend to accentuate high level of student’s intrinsic motivation. The article examines the school physics lab as an example of constructivist learning environment and analyzes several didactic approaches as inquiry-based learning, problem-based learning, project-based learning, case studies, and just in time teaching from constructivist point of view. The author enumerates the basic principles for the organization of school physics lab in a constructivist manner: provision of opportunities for students’ own thinking, giving students a certain freedom degree in identifying solution through verbalization of the problem, necessity for teacher to know a priori concepts of students, students’ effort as a mandatory condition to achieve students’ interest. The concept of “big scientific ideas” is in the core of this organization. The author emphasizes that conceptual understanding in school physics lab, which is inseparable from learning by being, is achieved through the overlapping of several learning and teaching approaches which form the core of LBB concept. Keywords: constructivist pedagogy, educational paradigms, learning by being, ownership of cognitive goals, school physics lab
Improving student activities and learning outcomes through implementation of pop-up book media in discovery learning

One of the crucial things in achieving maximum learning outcomes is using learning media that can facilitate active student learning. Therefore this study aims to examine the use of Pop-up book media in discovery learning to improve student learning processes and outcomes. The approach is qualitative, with a classroom action research type. The research subjects were 12 grade IV students at SDN 105 Pinrang. This research was conducted in 2 cycles. Observation techniques, tests, and documentation obtained data. This study focuses on the learning process (student activities) and student learning outcomes. The results showed that the learning process (student activities) using Pop-up book media in discovery learning in cycles I and II improved. In line with the improvement in the learning process, student learning outcomes also increased from having sufficient qualifications in cycle I to be well qualified in cycle II. This study concludes that using pop-up book media in discovery learning can improve the process (student activities). The learning process becomes more lively because two-way communication is established, students active participation makes learning more meaningful and powerful. The learning syntax in discovery learning can facilitate students using pop-up book media because it can stimulate students to be active in learning. Students are encouraged to identify material in the media, and the use of pop-up book media in learning discovery learning changes teacher-oriented learning to student-oriented. This positively impacts student learning outcomes, which increase as the learning process increases.
Project-Based Learning Method in Japanese Language Learning

Learning Japanese at State Polytechnics of Bali and Hasanuddin University has similarities to one of the subjects studied by students, called the Japanese Language for Tourism. It takes students’ critical thinking and attracts students’ interest in this learning. For this lesson, the use of Project-Based Learning is a suitable learning model for students to hone and develop their creativity in introducing Indonesian tourism using Japanese. The aim of this research was to increase the critical thinking and creativity of the students by using the Project-Based Learning method in Japanese for tourism lessons. The design of this research was an analysis study. In this research, the writer wanted to find the use of the Project Based Learning method in Japanese language classes. In this research, the writer used a qualitative method. The inductive process of data analysis started by gathering information through observations, interviews, documentation, and triangulations. The result showed that there are several projects like videos and brochures produced by students in Japanese language classes using the PBL Method as developed by The George Lucas Educational Foundation, such as: (1) Start with the Essential Question; (2) Design a Plan for the Project; (3) Create a Schedule; (4) Monitor the Students and the Progress of the Project; (5) Assess the Outcome; (6) Evaluate the Experience.
Agricultural Land Dryness Distribution Using the Normalized Difference Drought Index (NDDI) Algorithm on Landsat 8 Imagery in Eromoko, Indonesia

The study area, Eromoko, has agricultural land covering 79.76% of the area, which experiences drought every year, causing a decrease in crop yields. Information on agricultural land dryness is needed to reduce the impact of dryness conditions on the agricultural sector. The effect of drought can be minimized using the transformation of the Normalized Difference Drought Index (NDDI) algorithm on Landsat 8 Imagery because it is considered capable of being used for land drought analysis that is accurate and efficient in time and cost. This study created a model for estimating soil moisture with actual soil moisture as the dependent variable and NDDI as the independent variable in several agricultural land uses in Eromoko. The results showed that the estimation model could estimate soil moisture with accuracy in plantations at 85.31%, irrigated paddy fields at 75.99%, rainfed paddy fields at 76.62%, and moors at 88.48%. The dryness category in the study area is 3,314.82 ha (35% of the total area). The variability of land use greatly affects the drying conditions. Dryness conditions can be reduced by controlling the dryness factors. Mitigation efforts to maintain soil moisture include irrigation planning based on the estimation model, applying bio-mulch and organic mulch, organic fertilization, and meeting water requirements in the harvesting period.