Reviewerly/exHarmony huggingface dataset:
Motivation as a Constituent Element of Human Psyche

The article examines the fundamental influence of human motivation on human inner and outer worlds. The views of Aristotle were used as the methodological basis to study the causality of the existence of things and phenomena, and as the theoretical basis Kurt Lewin's psychological field theory was used. The main ways of forming motivation, specifically, the upbringing process and assimilation to the social mechanism of livelihood (the relations of distribution, exchange and ownership) were researched. The connection between motivations, attitudes and dominance has been established. It is proved that motivations form a certain hierarchy of attitudes that are fixed in the human brain as dominants. The influence of motivation on the formation of human typology has been studied: dependent personality, mediocre personality, mature personality and a genius. It has been substantiated that a person of a dependent spiritual development is motivated by immediate needs, the intentions of their consciousness are directed to his body and relations of distribution, and the attitude is a stimulus. The life of a dependent person is focused on pleasure, the dominant is in the area of the striatum; behavior is dominated by the simplest forms of adaptation (stimulus - reaction), and language during communication reflects the bodily needs and desires for satisfaction. It has been further examined that a person of mediocre (reproductive) level of spiritual development is motivated by success, the intentions of his consciousness are directed to his ego, cognition of exchange relations, and attitude is the motive. The life of a mediocre person is built on the principle of reality, and the dominant migrates from the striatum to the prefrontal cortex. Behavior reproduces typical forms of behavior, and language reflects the desire for profit (economic, political, legal, psychological, ideological). It has been concluded that a person of a personal level of spiritual development is motivated by the needs of society, the intentions of their consciousness are aimed at mastering the laws of society, morality, holistic knowledge of relations of distribution, exchange and property, and interest is the attitude. The person's life is governed by duty, and the dominant is mainly in the prefrontal cortex. Behavior patterns of a mature person are focused on asserting the interests of society, and language reflects the interests of society, its values, goals and national security. Finally, it has been proved that a person of genius level of spiritual development is motivated by the need of finding the truth, the intentions of their consciousness are aimed at mastering the metaphysical laws of existence, and the ideal is the main attitude. The life of a genius is focused on creativity, the dominant is stably in the prefrontal cortex. In behavior, genius is focused on the establishment of ideals, and language reflects the ideals as a combination of Truth, Goodness and Beauty.
Training on Making a Water Speed ​​Detection Tool in Culverts for Early Detection of Flood Disasters in Tanjung Duren Village, DKI Jakarta

In early 2020, the Greater Jakarta area experienced severe flooding in several areas, one of which was the North Tanjung Duren Village, Grogol Petamburan District, West Jakarta. Based on BMKG data in February 2020, the Tanjung Duren Utara Urban Village area is a flood-prone area with a height of 10-30 cm and is also a densely populated settlement so that it is prone to short circuit hazards that can cause fires. One of the causes of flooding is water channels / culverts that do not flow smoothly. This activity proposes the creation of a water velocity detection device that functions as an early detection of flood disasters. The detection device is designed using a microcontroller and is connected to a sensor for detecting the speed of water flowing from the drain pipe in the culvert. Based on the results of the training provided, the community's improvement in early detection of flood disasters has increased as indicated by an increase in the post-test value of 52% compared to the pre-test value. This activity is very useful for flood-prone areas as an early detection approach.
Compression of Vehicle and Pedestrian Detection Network Based on YOLOv3 Model

The commonly used object detection algorithm based on convolutional neural network is difficult to meet the real-time requirement on embedded platform due to its large size of model, large amount of calculation, and long inference time. It is necessary to use model compression to reduce the amount of network calculation and increase the speed of network inference. This paper conducts compression of vehicle and pedestrian detection network by pruning and removing redundant parameters. The vehicle and pedestrian detection network is trained based on YOLOv3 model by using K-means++ to cluster the anchor boxes. The detection accuracy is improved by changing the proportion of categorical losses and regression losses for each category in the loss function because of the unbalanced number of targets in the dataset. A layer and channel pruning algorithm is proposed by combining global channel pruning thresholds and L1 norm, which can reduce the time cost of the network layer transfer process and the amount of computation. Network layer fusion based on TensorRT is performed and inference is performed using half-precision floating-point to improve the speed of inference. Results show that the vehicle and pedestrian detection compression network pruned 84% channels and 15 Shortcut modules can reduce the size by 32% and the amount of calculation by 17%. While the network inference time can be decreased to 21 ms, which is 1.48 times faster than the network pruned 84% channels.
Marketplace Application Feasibility Analysis with Android-Based Black Box Testing

Indonesia is an agricultural country.Where has a very wide agricultural land.According to BPS data for 2022, Indonesia has an agricultural area of 10.6 million ha.With such a large land area, of course, Indonesia has a diversity of crops in the agricultural sector.A lot of yields make farmers and farmer groups sometimes have problems in marketing their products.So that many farmers do not benefit from the harvest.The use of information technology is expected to be able to overcome the problems faced by farmers in marketing their crops.One of them is by using the marketplace.By using this marketplace application it is expected to increase profits from the harvest.The existence of this marketplace platform can be used as an alternative for agricultural entrepreneurs and collectors or middlemen as their business media, then this marketplace platform can introduce business activities online.Black box testing is testing carried out to observe the results of applications that are ready to be made to test input and output functionality, so that they can function properly without knowing the code structure and testing can be applied to unit, integration, system and acceptance testing.Based on the test results using the black box testing method, there are 7 test models namely the register page, login, main, edit profile, store registration, add products and checkout with a total of 50 users, the results obtained are 93% of successful users and unsuccessful users.The results of unsuccessful use of black box testing occur due to network interference or inappropriate input from the user.Then it can be concluded that this marketplace application is suitable for use as a means of transaction.
Understanding High-grade Mineralization in the Khoemacau Zone 5 Cu-Ag Deposit, Kalahari Copperbelt, NW Botswana, using μXRF Techniques

The Zone 5 Cu-Ag deposit is the most consistently (for ～4.2 km) mineralized deposit in the Khoemacau district in northwestern Botswana, with an underground mineable resource of ～100 Mt grading 2 % Cu and 21 g/t Ag. The deposit consists of a redox-buffered metal-zoned ore body hosted preferentially by chemically reduced meta-sediments overlying oxidized hematite-bearing arkosic sandstone. Ore-grade mineralization is typically hosted in variably deformed quartz-calcite veins, along metamorphic cleavage, along bedding, in shear fabric, and in folds. Geochemical assay data established during exploration indicates widespread signifi cant concentrations of Ag, correlating positively with Cu. In this study, we apply a Bruker M4 TORNADO micro-X-ray fluorescence (μXRF) scanner for multi-element mapping in selected highgrade drill core samples, with particular focus on Ag partitioning. Collection of μXRF data was followed by microscopic and SEM-EDS observations to validate results. The μXRF data coupled with petrographic results indicate: i) μXRF multi-elemental mapping on the Zone 5 drill core samples was very eff ective and can be applied as a fi rst order geochemical analytical tool for characterizing mineralization and targeting important sections of the core, ii) silicification contributed to cleavage formation, which later became important ore trap site, and iii) Ag is closely associated with Cu and Fe. SEM-EDS results show that native silver and stromeyerite in part co-precipitated with hematite post Cu-(Fe)-sulfi de deposition.
A SURVEY OF ENGINEERING FRAMEWORK TECHNOLOGY WITH APPLICATIONS TO COMPUTER AIDED ENGINEERING

This paper surveys engineering framework technology and its potential benefits to collaborative engineering, with a particular focus on computer aided engineering (CAE). A framework is a software infrastructure that enables engineering tools to interoperate (work together). Representative research and development efforts are overviewed, and their contributions to the key technologies are identified. While industry examples to date have been mostly pilot projects, it appears this field is developing rapidly and moving towards mainstream usage in the near future. Hence, this survey recommends becoming more acquainted with framework technology, and it identifies guidelines established by the National Industrial Information Infrastructure Protocols Consortium (NIIIP) as a suggested starting point.<br> An HTML version of this survey is available online that links to associated documents on the World Wide Web. Thus, as a secondary effect, this paper demonstrates how the Web can be used as a research tool.
Study on Wiping Operation to Accelerate Human Activities on Hidden Object Game

An aesthetical image composition and mysterious stories are the main components of a hidden object game (HOG) to make it enjoyable. In an HOG, players find objects hidden in an image and inquired by a list. As far as we know, there have been insufficient studies to explore game elements such as the efficiency of game effects on an HOG to accelerate human activities. In this paper, we propose "wiping operation" to accelerate human activities for an HOG. In an HOG that we developed, first, an original image is transformed into a triangulated image. Then, during game play, the quickness of the wiping action by a player makes the level of detail of the triangulation finer and rougher. We did an experiment to investigate the performance of the wiping operation. Each player in the experiment wore a brain activity sensor to obtain a brain activity value during game play and answered a questionnaire after game play. We show the experimental results by the questionnaire and brain activity value to verify the effectiveness of the wiping operation.
Research on Object Tracking Technology Based on Region Proposal Siamese Network

Most of the existing trackers have high performance and good effect, but it is difficult to have fast speed and can not meet the real-time requirements. Therefore, the development of target tracking system with high accuracy and good robustness has become an urgent task for researchers. This paper proposes to add an Region Proposal Network (RPN) module based on the structure of the traditional Siamese Network (SiamFC), calculate the template and branch of the Siamese sub network in advance in the reasoning stage, and decompose the tracking task into task nodes that are detected first and then matched for real-time online tracking. The experimental results on VOT2015, VOT2018 and OTB2015 data sets show that compared with other trackers, the model based on SiamRPN proposed in this paper shows better performance in achieving the dual goals of high accuracy and low robustness.
Character strengths in weight maintenance: perceptions after a weight loss program

This study aimed to analyze which factors can favor or hinder healthy habits and the character forces associated with weight maintenance, in adults who underwent a weight loss program at a Contemporary Health and Wellness Center. This is a qualitative, cross-sectional, exploratory, and descriptive study. Seven people conducted semi-structured interviews, analyzed using the Thematic Analysis by Braun and Clarke. The results show that learning and discipline are extremely important for maintaining the habits learned in the program. Situations such as work, family, and aging can generate negative emotions and interfere with life satisfaction, making health habits more difficult. The forces of self-regulation, persistence, love of learning, humor, and appreciation of beauty can present favorable returns to weight maintenance. The development of character strengths can be extremely important for the maintenance of body weight after carrying out a weight loss program.
EgoLocate: Real-time Motion Capture, Localization, and Mapping with Sparse Body-mounted Sensors

Human and environment sensing are two important topics in Computer Vision and Graphics. Human motion is often captured by inertial sensors, while the environment is mostly reconstructed using cameras. We integrate the two techniques together in EgoLocate, a system that simultaneously performs human motion capture (mocap), localization, and mapping in real time from sparse body-mounted sensors, including 6 inertial measurement units (IMUs) and a monocular phone camera. On one hand, inertial mocap suffers from large translation drift due to the lack of the global positioning signal. EgoLocate leverages image-based simultaneous localization and mapping (SLAM) techniques to locate the human in the reconstructed scene. On the other hand, SLAM often fails when the visual feature is poor. EgoLocate involves inertial mocap to provide a strong prior for the camera motion. Experiments show that localization, a key challenge for both two fields, is largely improved by our technique, compared with the state of the art of the two fields. Our codes are available for research at https://xinyu-yi.github.io/EgoLocate/.
Can Fair Federated Learning Reduce the need for Personalisation?

Federated Learning (FL) enables training ML models on edge clients without sharing data. However, the federated model's performance on local data varies, disincentivising the participation of clients who benefit little from FL. Fair FL reduces accuracy disparity by focusing on clients with higher losses while personalisation locally fine-tunes the model. Personalisation provides a participation incentive when an FL model underperforms relative to one trained locally. For situations where the federated model provides a lower accuracy than a model trained entirely locally by a client, personalisation improves the accuracy of the pre-trained federated weights to be similar to or exceed those of the local client model. This paper evaluates two Fair FL (FFL) algorithms as starting points for personalisation. Our results show that FFL provides no benefit to relative performance in a language task and may double the number of underperforming clients for an image task. Instead, we propose Personalisation-aware Federated Learning (PaFL) as a paradigm that pre-emptively uses personalisation losses during training. Our technique shows a 50% reduction in the number of underperforming clients for the language task while lowering the number of underperforming clients in the image task instead of doubling it. Thus, evidence indicates that it may allow a broader set of devices to benefit from FL and represents a promising avenue for future experimentation and theoretical analysis.
New Equivalences Between Interpolation and SVMs: Kernels and Structured Features

The support vector machine (SVM) is a supervised learning algorithm that finds a maximum-margin linear classifier, often after mapping the data to a high-dimensional feature space via the kernel trick. Recent work has demonstrated that in certain sufficiently overparameterized settings, the SVM decision function coincides exactly with the minimum-norm label interpolant. This phenomenon of support vector proliferation (SVP) is especially interesting because it allows us to understand SVM performance by leveraging recent analyses of harmless interpolation in linear and kernel models. However, previous work on SVP has made restrictive assumptions on the data/feature distribution and spectrum. In this paper, we present a new and flexible analysis framework for proving SVP in an arbitrary reproducing kernel Hilbert space with a flexible class of generative models for the labels. We present conditions for SVP for features in the families of general bounded orthonormal systems (e.g. Fourier features) and independent sub-Gaussian features. In both cases, we show that SVP occurs in many interesting settings not covered by prior work, and we leverage these results to prove novel generalization results for kernel SVM classification.
PROTOTIPE ALAT PENGHITUNG HARGA PADA PRINT-OUT ENGAN SENSOR WARNA TCS3200 SERTA SISTEM PENYIMPANAN DATA LOGGER

Research has been carried out aiming (i) to create a system and design a tool to calculate and add up the price of color and non-color printing, (ii) to determine the RGB frequency in determining a color, (iii) to find out the latest usage data in the Data Recorder program. The tool is designed to be able to calculate the type of concrete automatically, using the TCS3200 color sensor as a determinant of the type of mold with a 20x4 LCD display. The system uses the RTC DS1302 digital clock module, the SD Card Module for data storage as a function of the data logger program. The method applied in this research is the calculation method. This study uses international color measurement data as a frequency reference for the color sensor reading process, for the data logger program process using a PLX-DAQ (Parallax Data Acqusitions) program is an add-on to the parallax microcontroller data acquisition for Microsoft Excel. Making it easier to be able to unify tools in real time, by providing a color sensor calibration system program and storing data on an SD card (Data Logger) the results will be obtained, namely being able to distinguish color and colorless automatically with a tool success rate of 93.4% given a distance of 5 cm to the concrete paper.
RetroMAE-2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models

To better support information retrieval tasks such as web search and open-domain question answering, growing effort is made to develop retrieval-oriented language models, e.g., RetroMAE and many others. Most of the existing works focus on improving the semantic representation capability for the contextualized embedding of the [CLS] token. However, recent study shows that the ordinary tokens besides [CLS] may provide extra information, which help to produce a better representation effect. As such, it's necessary to extend the current methods where all contextualized embeddings can be jointly pre-trained for the retrieval tasks. In this work, we propose a novel pre-training method called Duplex Masked Auto-Encoder, a.k.a. DupMAE. It is designed to improve the quality of semantic representation where all contextualized embeddings of the pre-trained model can be leveraged. It takes advantage of two complementary auto-encoding tasks: one reconstructs the input sentence on top of the [CLS] embedding; the other one predicts the bag-of-words feature of the input sentence based on the ordinary tokens' embeddings. The two tasks are jointly conducted to train a unified encoder, where the whole contextualized embeddings are aggregated in a compact way to produce the final semantic representation. DupMAE is simple but empirically competitive: it substantially improves the pre-trained model's representation capability and transferability, where superior retrieval performances can be achieved on popular benchmarks, like MS MARCO and BEIR.
The Valuation and Investment Risk of Cryptocurrency: Evidence from Bitcoin and Ethereum

From gold standard currencies to fiat money secured by government credit, to today's cryptocurrencies, the basic form of money and mankind's perception of its value has shifted dramatically. This paper will demonstrate the value and risk assessment of the two cryptocurrencies with the highest market share, i.e., Bitcoin and Ethereum. Although the current technology of cryptocurrencies is not perfect, it will improve over time and their value will increase due to the high demand for them. This aim of the study to give first-time investors an understanding of the valuation and risks of cryptocurrencies, rather than treating them as simple financial assets for investment. According to the analysis, the value and risk of Bitcoin depend deeply on many characteristics that were initially built into it. It also has an impact on the value of other virtual currencies at the same time. On the other hand, Ether is a much more open platform, so its value and risk depend more on the various applications and contracts built into a blockchain than Bitcoin. These results shed the light on guiding the further exploration of solving the safety problem of cryptocurrencies from different perspectives.
Rekonstruksi Butir Soal dalam Penilaian Keterampilan pada KD 3.7 dan KD 4.7 Teks Hikayat

One of the literary expressions taught in the Education Unit Level Curriculum in Senior High Schools is Hikayat Text. Saga Text Learning is one of the basic competencies that is integrated into the Indonesian language curriculum at Senior High Schools (SMK/SMA). Hikayat text is to express inner experiences about life through the medium of written language in which the words are coherent and intact. For students, Hikayat Text is not just a requirement to get grades from the teacher, but the process of expressing ideas in the form of words. Therefore, to achieve competence, students must be able to determine the values ​​of the Hikayat Text. The purpose of the research is to reconstruct the items in the saga text KD 3.7 and 4.7 learning tools found in Taruna Bhakti Vocational School, Islamic Vocational School 1 Ambawa, and SMKN 1 Banggai. The research method used is descriptive qualitative. Qualitative data analysis includes content validity and constructs validity. The instrument used is the author acts as a data collector and data analyzer. Qualitative analysis instruments include content validity and construct validity analysis. A qualitative analysis of the items was conducted to determine the content validity and construct validity. In addition, qualitative analysis can be studied by covering the material domain, construction domain, and language domain. Reconstruction of questions is done by examining questions that are not in accordance with content validity or construct validity. The results of the analysis of the three RPP 3.7 and 4.7, namely RPP SMK Taruna Bhakti at KD 3.7 have 100% material aspects for construction aspects 96% cultural/language aspects 100% and analysis on RPP SMK Taruna Bhakti KD 4.7 there are material aspects 100% are appropriate, for Aspects construction 100% It is suitable for language/cultural aspects 100% is appropriate. RPP 2 SMK Islam Sudirman 1 Ambawa at KD 3.7 and KD 4.7 has 100% appropriate material aspects, 99% of construction aspects are not appropriate and 100% cultural/language aspects are appropriate. RPP 3 SMKN 1 Banggai at KD 3.7 and KD 4.7 has 100% appropriate material aspects, 97% of construction aspects are not appropriate and 100% of cultural/language aspects are appropriate.