Real-time object tracking is an important step of many modern image processing applications. The efficient hardware design of real-time object tracker must achieve the desired accuracy while satisfying the frame rate requirements for a variety of image sizes. The existing methods of visual tracking employ sophisticated algorithms and challenge the capabilities of most embedded architectures. Discriminative scale space tracking is one algorithm that is capable of demonstrating good performance with affordable complexity. It has a high degree of parallelism which can be exploited for efficient implementation of reconfigurable hardware architectures. This paper proposes a real-time implementation of the discriminative scale-space tracker on FPGA for the major blocks. A careful design exploration of core mathematical operations of the tracking algorithm is performed to improve their hardware utilization and timing performance. Among the core functional units optimized in this work, the discrete Fourier transform achieves a computational time improvement of 92% relative to existing works, QR factorization achieves a 2.3$$\times$$ × reduction in resource utilization, and singular value decomposition yields a 3.8$$\times$$ × improvement in processing time. The proposed data path architecture is designed using Vivado HLS tool set and implemented for Zync Zed Board (xc7z020clg484-1). For an input image size of 320 $$\times$$ × 240, the proposed architecture achieves a mean 25.38 fps.
In the modern age, the use of video has become fundamental in communication and this has led to its use through an increasing number of devices. The higher resolution required for images and videos leads to more memory space and more efficient data compression, obtained by improving video coding techniques. For this reason, the Alliance for Open Media (AOMedia) developed a new open-source and royalty-free codec, named AOMedia Video 1 (AV1). This work focuses on the Wiener filter, a specific loop restoration tool of the AV1 video coding format, which features a significant amount of computational complexity. A new hardware architecture implementing the separable symmetric normalized Wiener filter is presented. Furthermore, the paper details possible optimizations starting from the basic architecture. These optimizations allow the Wiener filter to achieve a 100× reduction in processing time, compared to existing works, and 5× improvement in megasamples per second.
This research aims to study students’ High Order Thinking Skills (HOTS) in Primary Teacher Education Department of Universitas Negeri Semarang (UNNES) viewed from their Self-Regulated Learning (SRL). The research method in this research is a mixed method of a sequential explanatory model. This research was conducted in the Department of Primary Teacher Education at UNNES for students of class 2020 in the Basic Mathematical Concept course. Data collection techniques using questionnaires, documentation, interviews. Analysis of quantitative data in the form of validity and reliability of the instrument was followed by descriptive analysis. Qualitative data analysis was performed by triangulation and descriptive statistical analysis. Analysis of quantitative data found two categories of the level of SRL, namely medium and high levels. The results of the analysis of student answers were obtained: (1) Students with moderate SRL category interpret the questions into Mathematical language, and the way they identified the problem is less communicative, while the students with high SRL category interpret the questions into Mathematical language communicatively; (2) Based on students’ ability to evaluate, students with moderate SRL category have not been fluent yet, while the students with high SRL category have been fluent in evaluating, and (3) Based on their creativity, students with moderate SRL still need more practices, while students with high SRL category have been fluent. The conclusion of this study is the ability to interpret problems and the habit of examining problem-solving carried out into the differences between the two categories.
<p><span lang="EN-US">Reconstructing geometrical concepts requires a spatial thinking process, so the spatial thinking process will be correct and complete. The phenomena of cognitive style differences cause different perceptions and thinking activities to solve geometric problems. This qualitative-explorative research describes the spatial thinking process of students with field-dependent cognitive styles in reconstructing the concept of spatial geometry based on the theory of Action-Process-Object-Schema (APOS). The research subjects were 27 students and obtained five students with field-dependent cognitive styles. The researchers used a purposive sampling technique from the subjects with a certain consideration. The researchers selected a student that met the three elements of spatial thinking and the five indicators of spatial ability. This research collected the data with interviews, documentation, and group embedded figure test (GEFT). The analyzing techniques used data collection, data reduction, data presentation, and concluding. The spatial thinking process of the field-dependent students had a spatial category with three indications: i) Inaccuracy in the elements of representational thinking; ii) The inaccuracy of spatial perception indicators; and iii) Not using de-encapsulation mental mechanisms.</span></p>
Penelitian ini bertujuan untuk mengetahui dan mendeskripsikan kemampuan pemecahan masalah matematis pada pembelajaran bernuansa etnomatematika. Metode yang digunakan dalam penelitian adalah systematic literature review. Hasil seleksi artikel dari 20 artikel yang terbit dari tahun 2017-2021 didapatkan 9 artikel nasional dan internasional bereputasi tentang kemampuan pemecahan masalah matematis dalam pembelajaran bernuansa etnomatematika. Hasil identifikasi dan analisis artikel ditemukan bahwa pembelajaran matematika bernuansa etnomatematika menjadi salah satu alternatif pembelajaran matematika untuk meningkatkan kemampuan pemecahan masalah matematis siswa. Pembelajaran bernuansa etnomatematika memberikan kesempatan kepada siswa untuk berdiskusi tentang materi yang dipelajari kemudian dikaitkan dengan pengalaman kebiasaan budaya siswa yang pernah dialami siswa sehingga siswa dapat memahami, mengolah, dan menggunakan ide-ide dan konsep matematika terkait pengalaman siswa untuk memecahkan permasalahan matematika yang berkaitan dengan aktivitas sehari-hari siswa secara inovatif dan mandiri. Penggunaan model pembelajaran dalam pembelajaran matematika bernuansa etnomatematika dapat disesuaikan dengan materi, permasalahan serta situasi tempat penelitian.
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