Reviewerly/exHarmony huggingface dataset:
Weighted-LDA-TVM: Using a Weighted Topic Vector Model for Measuring Short Text Similarity

Topic modeling is the core task of the similarity measurement of short texts and is widely used in the fields of information retrieval and sentiment analysis. Though latent dirichlet allocation provides an approach to model texts by mining the underlying semantic themes of texts. It often leads to a low accuracy of text similarity calculation because of the feature sparseness and poor topic focus of short texts. This paper proposes a similarity measurement method of short texts based on a new topic model, namely Weighted-LDA-TVM. Latent dirichlet allocation is adopted to capture the latent topics of short texts. The topic weights are learned by using particle swarm optimization. Finally, a text vector can be constructed based on the word embeddings of weighted topics for measuring the similarity of short texts. A group of text similarity measurement experiments were performed on biomedical literature abstracts about antidepressant drugs. The experimental results prove that the proposed model has the better distinguish ability and semantic representation ability for the similarity measurement of short texts.
Análises de Palavras-chave como Fonte de Dados para Obtenção de Conhecimento Sobre a Evolução da Ciência

EnglishServices such as digital libraries and individual registration sites are some examples of how the internet has contributed to the amount of published work, allowing users not only to access available content, but also to record their scientific output. In this context, researchers from all domains have dedicated their efforts to analyzing scientific production from different perspectives, such as: citation analysis, productivity indicators, scientific collaboration and analysis of topics based on abstracts, titles and words scientific articles. Among the works found in the literature, the analyzes generally use international repositories, which are specific to a particular area or periodical. However, because they deal with specific analyzes and use of international repositories, they can not comprehensively represent what is produced in Brazil. Thus, analyzing a data source that encompasses several types of publications, especially in national vehicles of different areas, becomes a relevant task for the understanding of Brazilian science. Therefore, a temporal analysis of the main keywords in the scientific articles of all the individuals with a doctorate completed that have the curricula registered in the Lattes Platform is proposed in this work. portuguesServicos como bibliotecas digitais e sitios para registro individual de producao cientifica sao alguns exemplos de como a internet tem contribuido na quantidade de trabalhos publicados, permitindo que usuarios nao apenas acessem conteudo disponivel, mas tambem possam registrar a sua producao cientifica. Neste contexto, pesquisadores de todos os dominios tem dedicado esforcos com intuito de analisar a producao cientifica sobre diferentes perspectivas, como: analises de citacoes, indicadores de produtividade, colaboracao cientifica e analise de topicos baseados em termos extraidos de resumos, titulos e palavras-chave de artigos cientificos. Dentre os trabalhos encontrados na literatura, geralmente as analises realizadas utilizam repositorios internacionais, que sao especificas de uma determinada area ou periodico. No entanto, por tratarem de analises especificas e utilizarem de repositorios internacionais, nao podem representar de forma abrangente o que e produzido no Brasil. Com isso, analisar fonte de dados que englobe diversos tipos de publicacoes, principalmente em veiculos nacionais de diversas areas, passa a ser uma tarefa relevante para a compreensao da ciencia brasileira. Assim sendo, e proposto neste trabalho uma analise temporal das principais palavras-chave existentes nos artigos cientificos de todos os individuos com doutorado concluido que possuem os curriculos cadastrados na Plataforma Lattes.
Mapping Light: Data Impressionism

Using a practical investigation as a sample case study, this paper outlines an initial investigation into the visualization of people’s experiences within a city space. Highlighting the shortcomings of conventional data visualization approaches, it presents an argument for the use of light as a useful metaphor for mapping and connecting emotion with place. Inspired by the impressionistic painters, and their use of light as a means to capture the sense or mood of a scene, the project advocates light as a possible way to develop a kind of ‘data impressionistic’ approach for visualizing the data-informed mood of a location. The paper outlines the on-going practical project work and prototypes, and looks forward to future opportunities and project developments during the next phases of work.
PENGEMBANGAN SISTEM DETEKSI OVER-HEIGHT VEHICLE BERDASARKAN GEOMETRI KAMERA

At this time, many Overh-Height Vehicle Detection Systems have been developed to help reduce the risk of road accidents, especially vehicles which exceeds the height limit for the bridge. In the research that the author did was Development of Detection Systems Camera Geometry Based Overh-Height Vehicle, the method developed in this study is the implementation of the camera's geometry position to detect over-height vehicle. Modifications are made by changing the tilt angle camera with a height of 2 meters, 2.5 meters and 3 meters with the choice of ROI area so that it is expected to increase the accuracy of over-height detection vehicle. The detection phase is carried out through the process of motion detection and processing image that is get RGB, RGB2Gray, thresholding, morphology is dilated with 4x4 kernel to detect objects that exceed the limit or touch the ROI line. The results obtained from this study are, data processing uses high a 2.5 meter camera is able to produce more optimal data with a total of 84 frames are saved, 84 frames are detected correctly, 2 frames are detected incorrectly and level 97.67% accuracy.  Keywords: Over-Height Vehicle, Detection System, Camera Geometry
Contribution of Blockchain Applications on the Economy in Global Logistic

After Industry 4.0 innovations in Logistics 4.0 are increasing day by day, while human intelligence adds a new one to innovations in international transportation.Nowadays, the implementation of Blockchain platforms in the supply chain in the global market is strengthening the supply chain's weak links.With the smart contracts that will accelerate the global market logistics, everything from the cargo shipment to the payment methods on the internet is transparent, making the work of the supply chain actors accountable and reliable.The aim of this research is to investigate the contribution of Blockchain to the economy in global digital commerce and logistics.
Цифровизация процессов обслуживания в библиотеках - это уже реальность

The article considers theoretical issues of digitalization in libraries, characterizes modern forms and methods of providing library and information services, ways of communication between libraries and users. It reveals qualitatively new opportunities of library and information service due to spreading digital technologies and robotics in libraries. Cases of successful implementation of library and information services digitization projects demonstrate the library readiness to move to a new level of development. The author concludes that despite the fact that digitalization significantly increases services efficiency, effects positively on their quality and, consequently, attracts new users to libraries, library information services also include processes that are impossible without human participation with qualities such as the ability to anticipation, emotional experience, intuitive forecasting. Therefore, it is necessary to be aware of the boundaries and professional needs when using digital technologies in library and information services.
Specifying Requirements through Interaction Design

When the requirements and the interaction design of a system are separated, they will most likely not fit together, and the resulting system will be less than optimal. Even if all the real needs are covered in the requirements and also implemented, errors may be induced by human-computer interaction through a bad interaction design and its resulting user interface. Such a system may even not be used at all. Alternatively, a great user interface of a system with features that are not required will not be very useful as well. This tutorial explains joint modeling of (communicative) interaction design and requirements, through discourse models and ontologies. Our discourse models are derived from results of human communication theories, cognitive science and sociology (even without employing speech or natural language). While these models were originally devised for capturing interaction design, it turned out that they can be also viewed as specifying classes of scenarios, i.e., use cases. In this sense, they can also be utilized for specifying requirements. Ontologies are used to define domain models and the domains of discourse for the interactions with software systems. User interfaces for these software systems can be generated semi-automatically from our discourse models, domain-of-discourse models and specifications of the requirements. This is especially useful when user interfaces for different devices are needed. Specific usability requirements can be dealt with in our approach through advanced customization approaches. Hence, inter-action design facilitates requirements engineering to make applications both more useful and usable.
Agent-based Simulation with Process-interaction Worldview

After analyzing the agent-based simulation (ABS), we realize that most researchers focus on the agent-based modeling, but only a few researchers pay attention to the simulation.The reason is that the agentbased model (ABM) can run directly in a real-time manner by communication among agents and the running of the ABM is already one kind of simulation.However, the ABS is less efficient when being used into a non-real-time system even though it can be speeded up by giving a timescale.So, to speed up the ABS, we introduce a process-interaction worldview (PIW) originated in the discrete event simulation to the ABS.A method for combining the agent-based simulation and the PIW is proposed.The method is validated by applying in a simple queue system and compared with the normal ABS with a timescale.
Knowledge Reuse of Learning Agent Based on Factor Information of Behavioral Rules

In this study, we attempt to extract knowledge by collecting results from multiple environments using an autonomous learning agent. A common factor of the environment is extracted by applying non-negative matrix factorization to the set of learning results of the reinforcement learning agent. In transfer learning of knowledge management of agents, as the number of experienced tasks increases, the knowledge database becomes larger and the cost of knowledge selection increases. By the proposed approach, an agent that can adapt to multiple environments can be developed without increasing cost of knowledge selection.
Analisis Kesulitan Belajar Siswa Pada Mata Pelajaran Aplikasi Pengolah Angka (Spreadsheet) Ditinjau Dari Aspek Kognitif Dan Media Pembelajaran Siswa Jurusan Akuntansi Kelas X SMK N 1 Boyolali

The purpose of this study was to determine: 1) the effect of students 'cognitive aspects on Spreadsheet learning difficulties, 2) the influence of learning media on Spreadsheet learning difficulties, 3) the influence of students' cognitive aspects and learning media on Spreadsheet learning difficulties. This research uses an associative quantitative method. The population in this study was the tenth grade students of the Accounting Department at SMK Negeri 1 Boyolali, totaling 108 students. The sampling technique uses Proportional Random Sampling with 84 respondents. The data analysis technique used is multiple linear regression test, F test, t test, R2 test, and relative and effective contributions. The conclusions that can be drawn from this study are: (1) the cognitive aspects of students have a significant effect on learning difficulties. This is proven based on the regression analysis that obtains the value of t> ttable that is 2.508> 1.989 with the probability value Sig. i.e. 0.014 ttable is 3.111> 1.989 with a significance value of 0.003 ftable, namely 19.816> 3.111 with a significance value of 0.000 <0.05. (4) Variable X1 gives a relative contribution of 43.3% and an effective contribution of 14.24%, variable X2 gives a relative contribution of 56.6% and an effective contribution of 18.62%. (5) R2 calculation results obtained 0.329 means 32.9% of the learning difficulties Spreadsheets are influenced by the cognitive aspects of students and learning media, the remaining 67.1% is influenced by variables outside the study.
ANALISIS KINERJA VEHICLE TO INFRASTRUCTURE (V2I) UNTUK PENERAPANINTELLIGENT TRANSPORTATION SYSTEM(ITS)

Number of vehicle user is increasing in Politeknik Negeri Medan now. The increase is not proportional with road and parking lots availab ility . As a result of these conditions ,  campus becomes jammed and c rowded . S olution to overcome of this condition is implementing of Intelligent Transportation System (ITS). ITS is a smart system for transportation that can give efficiency, comfort and safety for vehicle drivers. One of kind communication in ITS systems is communication between vehicles to infrastructure (V2I). The infrastructure is here as roads and parking lots. To reach the goals, analysis of V2I device performance is needed. V2I device consists of OBU (Onboard Unit), RSU (Roadside Unit) and communication among them using DSRC communication technology. According to power level measurement, height positions of RSU is 6 m and the longest distance RSU toward OBU is 400 m, obtained power is -90,38 dBm. This value is still in device sensitivity of -91,5 dBm. This research is an initiation study as a basis to build integrated ITS system.
The Effect of Rational Based Beliefs and Awareness on Employee Compliance with Information Security Procedures: Case Study of a Financial Firm [Abstract]

Aim/Purpose: This paper examines the behavior of financial firm employees with regard to information security procedures instituted within their organization. Furthermore, the effect of information security awareness and its importance within a firm is examined. Background: The study focuses on employees' attitude toward compliance with information security policies (ISP), combined with various norms and personal abilities. Methodology: A self-reported questionnaire was distributed among 202 employees of a large financial institution. Contribution: As far as we know, this is the first paper to thoroughly examine employees' awareness of information system procedures, among financial organizations in Israel and also the first to develop operative recommendations for these organizations aimed at increasing ISP compliance behavior. Findings: Our results indicate that employees' attitudes, normative beliefs and personal capabilities to comply with firm's ISP, have positive effects on the firm's ISP compliance. Also, employees' general awareness of IS, as well as awareness to ISP within the firm, positively affect employees' ISP compliance. Impact on Society: This study offers another level of understanding of employee behavior with regard to information security in organizations and comprises a significant contribution to the growing knowledge in this area. The research results form an important basis for IS policymakers, culture designers, managers, and those directly responsible for IS in the organization. Future Research: Future work should sample employees from other financial institutions and also institutions from other fields and also should apply qualitative analysis to explore other pillars of behavioral patterns related to the subject matter.
Research and implementation of real-time fog and haze video image restoration system based on FPGA

针对雾、霾等恶劣气象条件下, 视频监控等户外视频设备对视频图像实时复原的需要, 提出一种快速图像复原算法的FPGA实现方法, 通过适当降低算法复杂度达到了降低时间开销和硬件实现复杂度的目的。通过将一帧视频分解成3×3小窗口进行运算, 以窗口中心像素的流水计算替代一帧视频像素计算, 使每个像素在3个时钟周期内完成全部运算, 确保了系统能够实时复原, 降低了复原模块对硬件的开销。实验证明:FPGA处理结果和MATLAB处理的结果相符, 可以在保证除雾效果的前提下, 实时处理分辨率为640×480视频并以29帧/s速度流畅显示。
Accelerating the Smith-Waterman Algorithm Using the Bitwise Parallel Bulk Computation Technique on the GPU

The bulk execution of a sequential algorithm is to execute it for many different inputs in turn or at the same time. It is known that the bulk execution of an oblivious sequential algorithm can be implemented to run efficiently on a GPU. The bulk execution supports fine grained bitwise parallelism, allowing it to achieve high acceleration over a straightforward sequential computation. The main contribution of this work is to present a Bitwise Parallel Bulk Computation (BPBC) to accelerate the Smith-Waterman Algorithm (SWA) using the affine gap penalty. Thus, our idea is to convert this computation into a circuit simulation using the BPBC technique to compute multiple instances simultaneously. The proposed BPBC technique for the SWA has been implemented on the GPU and CPU. Experimental results show that the proposed BPBC for the SWA accelerates the computation by over 646 times as compared to a single CPU implementation and by 6.9 times as compared to a multi-core CPU implementation with 160 threads.
Face Image Matching Based on Improved Triplet Network

On the basis of the Triplet Network, there are many limitations in using the Euclidean distance for similarity determination. This paper proposes an image preprocessing method NR (New Robinson), a lightweight My-net model and an NTn (New Triplet network) model of image relative dispersion DF (Dispersion Function) combination. In this paper, the characteristics of NR (New Robinson) are used to reduce the model size of CNN, and DF (Dispersion Function) is used instead of the traditional Euclidean distance algorithm to determine the similarity and reduce the generality of Euclidean distance. Experiments on two data sets VGG_FACE2 and CACD2000 show that the accuracy of NTn model is improved by 10.7% and 16.0% compared with traditional model; the size of model is reduced from 19.6 MB to 3.2 MB; DF decays faster than Euclidean distance on Loss trend map, and the oscillation degree is more stable. As can be seen from the results, NTn has more advantages in accuracy and model size than Triplet network model.
Self-Calibration Method and Pose Domain Determination of a Light-Pen in a 3D Vision Coordinate Measurement System

Light pens for 3D vision coordinate measurement systems are increasingly widely used due to their advantages, such as their small size, convenience of being carried, and widespread applicability. The posture of the light pen is an important factor that affects accuracy. The pose domain of the pen needs to be given so that the measurement system has a suitable measurement range to obtain more qualified parameters. The advantage of the self-calibration method is that the entire self-calibration process can be completed at the measurement site with no auxiliary equipment. After the system camera calibration was completed, we took several pictures of the same measurement point with different poses to obtain the conversion matrix of the picture and subsequently used spherical fitting, the generalized inverse method of least squares, and the principle of position invariance in the pose domain range. The combined stylus tip center self-calibration method calculates the actual position of the light pen probe. The experimental results verify the effectiveness of the method; the measurement accuracy of the system can satisfy basic industrial measurement requirements.
A Safety-Space-Based Approach to Inspection Path Planning for the Sheet Metal Assemblies

Abstract The inspection path planning of sheet metal assemblies plays an important role in the measurement efficiency of large free-form surfaces. In the path generation of a 5-axis coordinate measurement machine (CMM), large calculation of collision detection and obstacle avoidance are needed in the traditional computer-aided inspection planning methods. Owing to structure complexity of large free-form surfaces, the planning procedures for collision detection and automatic collision-free trajectory generation is time-consuming and low-efficiency. To address this problem, a safety-space-based modeling approach is proposed to generate a feasible collision-free path for a large number of key measurement points. At first, based on the decomposition of the dynamic motion trajectory of the probe and discretizing of the inspected object, a continuous envelope space, i.e., safety space is constructed for candidate path generation of the probe. In the proposed planning strategy, the work of collision detection and avoidance are eliminated. Then, a heuristic optimization algorithm is used to generate the feasible trajectory in the constructed safety space for all the measurement points. At last, an inspection path planning case of a car door assembly was used to illustrate the procedure of the proposed method.
Research on Probability Distribution of Short-Term Photovoltaic Output Forecast Error Based on Numerical Characteristic Clustering

The forecast error characteristic analysis of short-term photovoltaic power generation can provide a reliable reference for power system optimal dispatching. In this paper, the total in-day error level was stratified by fuzzy C-means algorithm. Then the historical PV output data based on the numerical characteristics of point prediction output were classified. A General Gauss Mixed Model was proposed to fit the forecast error distribution of various photovoltaic output forecast error distribution. The impact of meteorological factors together with numerical characteristics on the forecast error was taken into full consideration in this analysis method. The predicted point output with high volatility can be accurately captured, and the reliable confidence interval is given. The proposed method is independent of the point prediction algorithm and has strong applicability. The General Gauss Mixed Model can meet the peak diversity, bias, and multimodal properties of the error distribution, and the fitting effect is superior to the normal distribution, the Laplace distribution, and the t Location-Scale distribution model. The error model has a flexible shape, a concise expression, and high practical value for engineering.
Contributed Session II: Two-dimensional shape perception is based on a salience map

A salience map is a dynamic topographical map that combines information from individual feature maps into a real-number measure of conspicuity (salience). Originally, Koch and Ullman (1985) used salience to predict the priority of locations in visual search. The defining characteristic of a salience map is substance indifference--computations made on the map contents are independent of the features that produced the salience values because the features are not represented in the map. Salience maps have been proposed for computations other than search or processing priority: attention-based motion perception (Lu and Sperling, 1995), isoluminant red-green grating motion (Lu, Lesmes, Sperling centroid computation (Sun, Chubb, Wright, Sperling, 2018) and frontal-plane distance perception (Gan, Sun, Sperling, 2021). Here we demonstrate the well-known fact that simple shapes, such as letters and numbers, can be recognized not only when they are painted black or white but also when the are defined by outlines, or filled with different textures than the background, or filled with colors that are isoluminant with the background. Substance indifference means 2D shape perception is a computation performed in large part on a salience map. We further demonstrate that luminance is not necessary for accurate shape perception, that isoluminant text is easily readable, and so-called luminance artifacts are irrelevant, i.e., salience is sufficient for accurate 2D shape perception.