Reviewerly/exHarmony huggingface dataset:
Development of Rotaly Link with Built-in Slider to improve inverted pendulum type robotic wheelchair with the ability to climb stairs

This paper proposes a new mechanism for an inverted pendulum type robotic wheelchair with the ability to climb stairs. This mechanism is developed to improve occupant safety and comfort. First, physical analysis confirmed that the proposed method met the purpose of ensuring the safety of the occupants. Next, the dimensional requirements necessary to develop the mechanism were clarified , and the mechanism was actually designed and manufactured. Finally, the operation was actually confirmed using the manufactured mechanism ,and problem were extracted
Data in Forensic Phonetics from theory to practice

What are speech data? The question is not as trivial as it may seem: every day both theoretical and applied linguistic research come up against problems deriving from bad data management. This topic is particularly thorny in interdisciplinary approaches such as the speech forensics analysis, whereby the recorded speech can be exploited as legal clues, with important repercussions on public security and citizens’ rights. The datum does not exist in nature, being it a consequence of the human analysis of a given phenomenon. In fact, data extraction is based on explicit and implicit theories implemented by the researcher within the application of specific frameworks. Researchers and professionals working on empiric data should be more aware of these underlined processes in order to avoid data misuse and, indeed, maximize results. In this paper, we will briefly address the issue of the speech data epistemology with a particular focus on the interdisciplinary required in forensics among linguistics and engineering, by discussing examples from Italian real cases. The analysis of speech for forensic purposes requires a strong interdisciplinary approach, especially for what it concerns collection, classification, treatment of acoustic data, and their following transcription and analysis. Moreover, it must be clarified what different experts (e.g., lawyers vs. linguists) mean as “datum”.
Peningkatan Motivasi Belajar Akuntansi Dasar Melalui Penerapan Teknik Think Pair Share Pada Kelompok Belajar Siswa Kelas X SMK Di Desa Dawung Kabupaten Sragen

This research aims to increase the motivation of basic accounting learning through the application of Think Pair Share technique in the learning group of grade X vocational students in Dawung Village, Sambirejo District, Sragen Regency. This type of research is Class Action Research conducted in two cycles. Each cycle consists of four stages: planning, action, observation, and reflection. The data collection in this study was conducted using observations, questionnaires, and documentation analyzed using quantitative descriptive by percentage. The results showed that based on pre-cycle observation data of 51.04%, after action in cycle I increased to 67.71% with a score increase of 16.67%. In cycle I by 67.71% increased to 87.50% in cycle II or there was a score increase of 19.79%. Based on the results of the distributed questionnaire data there was also an increase in student learning motivation scores in the pre cycle by 74.00% after the action in cycle I score increased to 77.31% with an increase in score by 3.31%. In cycle I by 77.31% increased to 82.63% in cycle II or there was a score increase of 5.32%. So it can be concluded that in the application of cooperative learning model of Think Pair Share (TPS) technique can increase the motivation of learning basic accounting subjects in the study group of students grade X vocational school in Dawung Village, Sambirejo District Sragen Regency. Therefore, teachers are encouraged to apply the cooperative learning model of Think Pair Share (TPS) technique to teaching and learning activities in the classroom.
Lecture Notes on the Application of the Functions of Semantic Categories in Translation

The aim of this paper is to shed light on the contribution of semantic categories to translation. To this end, the paper uses both a theoretical and a descriptive approach. Indeed, the theories relating to the terms category and semantic categories are presented. Then, the functions of semantic categories are described in translated sentences. Finally, the paper has found that the kernels of English sentences together with the transformations that can be derived from every clause or phrase are key aspects of sentence comprehension and stylistic differences. Equally important is the finding that translation becomes easier and more technical when the functions of semantic categories are applied in sentence construction.
A Novel Data Traceability Model Based on Blockchain and Digital Watermarking in Edge Computing

Abstract Most of the current data traceability models are centralized models, which cannot meet the traceability requirements of distributed edge nodes. Blockchain is a decentralized trust management mechanism based on the Internet. Its features that are difficult to tamper with and traceable provide a new solution to secure data traceability. However, many edge nodes have limited computing and storage resources, and cannot store large amounts of blockchain information. In order to solve the above problems, we propose a novel distributed traceability model based on digital watermarking and blockchain in edge computing. The model improves the security of the traditional traceability model by dividing the internal and external areas and electing the master nodes, reduces the storage capacity of resource-constrained nodes and solves the problem of poor scalability of the blockchain. The model can be applied to widely distributed edge node traceability scenarios, and can also trace the data in the case of watermark failure.
An introduction to concatenative programming in Factor

We provide an overview of Factor---a stack-based and concatenative programming language like FORTH. Factor incorporates the core concepts of the object-oriented (e.g., classes, polymorphism) and fu...
Stenographic transcriptions of reminiscences of the executives and employees of Moscow Automobile Factory as a source on socio-psychological aspects of the history of its establishment (1915-1924)

This research is dedicated to stenographic transcriptions of reminiscences of the executives and employees of the Moscow Automobile Factory named after I. A. Likhachev (AMO ZIL). The goal consists in determination of information capacity of stenographic transcription of reminiscences as a source for studying the socio-psychological aspects of the history of industrial enterprises. The author examines the following aspects: reflection in stenographic transcriptions of the views of company&amp;rsquo;s executives and technician engineers upon the industrial process; &amp;nbsp;different aspects of economic culture of the company; socio-psychological image of employees and their relation to development of the company, local and nationwide sociopolitical processes, technological difficulties; perception of collective environment by the staff members; working and living conditions. In the course of study, the author applied socio-psychological and illustrative methods based on the comprehensive analysis of sources. As a result, the author determines high informational vale of stenographic transcriptions of reminiscences, demonstrate possibilities its implementation in studying socio-psychological aspects of the history of industrial enterprises, namely economic culture, mentality of technical officers and staff members, atmosphere inside the collective, motivation and incentive system for employees, role of interpersonal relations in establishment and functionality of the company, views of executives and technician engineers on the industrial process, etc. Previously unstudied archival materials were introduced into the scientific discourse.
Deictic motion in Hakhun Tangsa

This paper provides a detailed description of how deictic motion events are encoded in a Tangsa variety called Hakhun, spoken in Arunachal Pradesh and Assam in India, and in Sagaing Region in Myanmar.Deictic motion events in Hakhun are encoded by a set of two motion verbs, their serial or versatile verb counterparts, and a set of two ventive particles.Impersonal deictic motion events are encoded by the motion verbs alone, which orient the motion with reference to a center of interest.Motion events with an SAP figure or ground are simultaneously encoded by the motion verbs and ventive particles.These motion events evoke two frames of reference: a home base and the speech-act location.The motion verbs anchor the motion with reference to the home base of the figure, and the ventives (or their absence) anchor the motion with reference to the location of the speaker, the addressee, or the speech-act.When the motion verbs are concatenated with other verbs, they specify motion associated with the action denoted by the other verb(s).
Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach

Text segmentation is a prerequisite in many real-world text-related tasks, e.g., text style transfer, and scene text removal. However, facing the lack of high-quality datasets and dedicated investigations, this critical prerequisite has been left as an assumption in many works, and has been largely overlooked by current research. To bridge this gap, we proposed TextSeg, a large-scale fine-annotated text dataset with six types of annotations: word- and character-wise bounding polygons, masks and transcriptions. We also introduce Text Refinement Network (TexRNet), a novel text segmentation approach that adapts to the unique properties of text, e.g. non-convex boundary, diverse texture, etc., which often impose burdens on traditional segmentation models. In our TexRNet, we propose text specific network designs to address such challenges, including key features pooling and attention-based similarity checking. We also introduce trimap and discriminator losses that show significant improvement on text segmentation. Extensive experiments are carried out on both our TextSeg dataset and other existing datasets. We demonstrate that TexRNet consistently improves text segmentation performance by nearly 2% compared to other state-of-the-art segmentation methods. Our dataset and code will be made available at https://github.com/SHI-Labs/Rethinking-Text-Segmentation.
Generative Classifiers as a Basis for Trustworthy Image Classification

With the maturing of deep learning systems, trustworthiness is becoming increasingly important for model assessment. We understand trustworthiness as the combination of explainability and robustness. Generative classifiers (GCs) are a promising class of models that are said to naturally accomplish these qualities. However, this has mostly been demonstrated on simple datasets such as MNIST and CIFAR in the past. In this work, we firstly develop an architecture and training scheme that allows GCs to operate on a more relevant level of complexity for practical computer vision, namely the ImageNet challenge. Secondly, we demonstrate the immense potential of GCs for trustworthy image classification. Explainability and some aspects of robustness are vastly improved compared to feed-forward models, even when the GCs are just applied naively. While not all trustworthiness problems are solved completely, we observe that GCs are a highly promising basis for further algorithms and modifications. We release our trained model for download in the hope that it serves as a starting point for other generative classification tasks, in much the same way as pretrained ResNet architectures do for discriminative classification.
Augment Machine Intelligence with Multimodal Information

Humans interact with other humans or the world through information from various channels including vision, audio, language, haptics, etc. To simulate intelligence, machines require similar abilities to process and combine information from different channels to acquire better situation awareness, better communication ability, and better decision-making ability. In this talk, we describe three projects. In the first study, we enable a robot to utilize both vision and audio information to achieve better user understanding [1]. Then we use incremental language generation to improve the robot's communication with a human. In the second study, we utilize multimodal history tracking to optimize policy planning in task-oriented visual dialogs. In the third project, we tackle the well-known trade-off between dialog response relevance and policy effectiveness in visual dialog generation. We propose a new machine learning procedure that alternates from supervised learning and reinforcement learning to optimum language generation and policy planning jointly in visual dialogs [2]. We will also cover some recent ongoing work on image synthesis through dialogs.
An Interpretation of Algorithm Results for Narrative Blood Chemistry Laboratory: A Systematic Review

The laboratory is one of the places to analyse disease and further provide input on improving treatment for certain types of disease through assessment. Blood sugar test is a significant test to determine a patient's health problems. Blood test results are still being introduced as a manual report containing a table of contractions and their qualities and units, which will then be read and shown to patients by specialists and medical personnel. Unfortunately, most of the specialists and their assistants had mixed translations in reading the report. Therefore, to assist specialist doctors and health nurses in obtaining similar data, this study proposes a Natural Language Generation (NLG) approach by applying Bigram's calculations to produce an understanding of the side effects of fasting and non-fasting blood sugar tests. The means of exploration are information extraction, understanding information, compilation of archives, micro planning and recognition, as well as the reporting period. This framework converts the mathematical arrangement of the test results into printed information in Indonesian which becomes the account understanding in the research facility reports on the consequences of fasting and non-fasting blood science tests. The results in this framework are reports as word archives. The test results of this examination indicate that the level of ease of account understanding of the test results obtained by specialists reaches 90%.
Joint Representation of Temporal Image Sequences and Object Motion for Video Object Detection

In this paper, we propose a new video object detector (VoD) method referred to as temporal feature aggregation and motion-aware VoD (TM-VoD), which produces a joint representation of temporal image sequences and object motion. The proposed TM-VoD aggregates visual feature maps extracted by convolutional neural networks applying the temporal attention gating and spatial feature alignment. This temporal feature aggregation is performed in two stages in a hierarchical fashion. In the first stage, the visual feature maps are fused at a pixel level via gated attention model. In the second stage, the proposed method aggregates the features after aligning the object features using temporal box offset calibration and weights them according to the cosine similarity measure. The proposed TM-VoD also finds the representation of the motion of objects in two successive steps. The pixel-level motion features are first computed based on the incremental changes between the adjacent visual feature maps. Then, box-level motion features are obtained from both the region of interest (RoI)-aligned pixel-level motion features and the sequential changes of the box coordinates. Finally, all these features are concatenated to produce a joint representation of the objects for VoD. The experiments conducted on the ImageNet VID dataset demonstrate that the proposed method outperforms existing VoD methods and achieves a performance comparable to that of state-of-the-art VoDs.
An assessment of Project-Based Learning towards Applied Health Informatics Teaching in an Undergraduate Class

This study aims to report and evaluate teaching based on Project-Based Learning towards an undergraduate subject of Applied Health Informatics. As an evaluation method, the development of mobile health applications was proposed. The research was conducted in a class with 21 students, who were evaluated qualitatively by two surveys. The students reported a positive impact of the discipline on their training and improvement in computational thinking abilities. Overall, the students created six m-health applications, and they achieved a new technology perception. Moreover, 15 students (71.4%) said to be more motivated to learn new technologies and 16 (76.2%) reported to be able to develop new applications.
The Philippines’ cybersecurity strategy : Strengthening partnerships to enhance cybersecurity capability

Bangladesh’s cybersecurity policies became well-known internationally in 2016 when the country’s central bank was the subject of one of the largest digital bank heists to date. This chapter contends that there is no alternative to promoting cooperation at both the regional and international level to ensure cybersecurity for Bangladesh. Bangladesh adopted its National Cyber Security Strategy in 2014 to face cyber threats, risks, and challenges to its national security. Bangladesh accepts the generally accepted understanding regarding the applicability of international law to cyberspace. Due to the easy accessibility of smartphones and the internet to the general public in the country, there is an increasing level of cybercrime in Bangladesh. Cybercrime has wider societal implications for Bangladesh. It is expected that after five or ten years, Bangladesh will be cited as one of the cyber secured countries in the world since the country is highly committed to secure its cyber space, which is manifested through the steps taken by the country.
PatchmatchNet: Learned Multi-View Patchmatch Stereo

We present PatchmatchNet, a novel and learnable cascade formulation of Patchmatch for high-resolution multi-view stereo. With high computation speed and low memory requirement, PatchmatchNet can process higher resolution imagery and is more suited to run on resource limited devices than competitors that employ 3D cost volume regularization. For the first time we introduce an iterative multi-scale Patchmatch in an end-to-end trainable architecture and improve the Patchmatch core algorithm with a novel and learned adaptive propagation and evaluation scheme for each iteration. Extensive experiments show a very competitive performance and generalization for our method on DTU, Tanks & Temples and ETH3D, but at a significantly higher efficiency than all existing top-performing models: at least two and a half times faster than state-of-the-art methods with twice less memory usage.
Measuring the Impact of Using Library Resources The Context of Secondary Students’ Academic Achievement

This study aims to explore the effect of libraries resources, in the light of the history and background, on the student’s academic performance. The reviewed literature states that students using library resources have greater efficiency and knowledge as compared to the students who do not use the libraries. Over the past twenty years, investigators all over the world have collected a significant amount of evidence pointing out the well-developed schools’ library results in better academic performance of students. By reviewing deeply analysis the review of the literature that effective libraries of any academic institution has deep effects on pupil academic performance and due to these effects, the student can improve their ability to get better academic results. Many numbers of investigations analysis these matters adopting qualitative and quantitative method has been used. Most research studies show the point of views that libraries have a good effect and impact on a pupil school’s performance.
An Inspired Algorithm for Solving Competitive Travelling Salesmen Problem

Competitive travelling salesman problem (CTSP) is a combinatorial optimization problem in whichnumber of salesmen compete among themselves to fined optimal solution with larger benefit and shortest path.Despite the importance of this problem and its many applications in real life, a few algorithms have been proposedto address this problem. Consequently, the need to either improve the existing algorithms or utilize a new algorithmis still necessary. In the last decades, the nature inspired algorithms, which are seek inspiration from nature andbiology phenomena, have been the goal of numerous studies in the most scientific fields, especially in operatingresearch and artificial intelligence. The swarm intelligence describe as an active research area in the developmentsof new algorithms inspired by nature. One of the recent swarm intelligence algorithms is salp swarm algorithm(SSA). This algorithm is characterized as being simple and flexible, so it motivates scholars to conduct severalmodifications to improve its performance. But, as any population based metaheuristics, SSA suffers from the slowconvergence due to its weak ability to exploit the search space. Thus, this paper proposes enhancing SSA to handleCTSP by utilizing its strong exploring ability and enhancing its exploitation ability. This enhancement achieves viahybridizing the SSA with a single-based meta-heuristics (SBHs) which have strong exploitation ability. In thishybridization, the SSA will be responsible for exploration and the SBH will be responsible for exploitation. Theadopted algorithms are applied on CTSP benchmark to test their validity. Results demonstrated that preserving thebalance between exploration and exploitation during the search have significant impact on the SSA efficiency. Thus,we concluded that the proposed hybridization managed to improve the effectiveness of SSA in getting good qualitysolutions.
Physiological and psychological basis of aesthetics

This essay will be devoted to the presentation of the aesthetic principles of painting, plastics and architecture. All these arts converge with each other mainly in the fact that they are the essence of visual art, that is, their works are perceived by the organ of vision and their aesthetic effects are given together with visual impressions. In the first issue, dedicated to the aesthetic principles of music, the general principles of grace and beauty were established and explained. We consider it not superfluous to formulate them again in a condensed form.
Motionless Haptic Interface using Kinesthetic Illusion Induced by Tendon Vibration (II)

In the present virtual reality systems, because users must move their physical body, there are problems in safety, cost and accessibility. In order to solve these problems, we have proposed a system that creates sense of movement without physical movement of user’s body using kinesthetic illusion induced by tendon vibration. In this paper, we conducted a psychological experiment to evaluate operability, body ownership and agency when using the proposed system. The results suggested that the use of tendon vibration may contribute to the improvement of body ownership, although it was not statistically significant. Also, there was a possibility that agency was lowered by tendon vibration.