34 research outputs found
An improved model of experimentally induced ocular hypertension in the rabbit
No full textA model of experimentally induced ocular hypertension for the evaluation of antiglaucoma drugs in the unanesthetized rabbit is described. It is based on the intravenous infusion of suitable amounts of 5 per cent glucose solution, and advantageously substitutes the oral water load. The method is sensitive to drugs acting both on the outflow facility (2 per cent pilocarpine) and an aqueous humor formation (10 per cent guanethidine)
Development of Animation-Based Teaching Material on Explanation Text on XI Grade Students at MAN 2 Aceh Tenggara
No full textThe problem of the research was the effectiveness and feseabilty of animation-based teaching material on explanation text on grade XI students at MAN 2 Aceh Tenggara. This effectiviness was carried out by teachers and students. The product feasibility test was tested by a team of experts, namely lecturers and teachers of bahasa Indonesia. The objective of the research was to develop animation-based teaching material to find out the effectiveness of animation based teaching material, and to find out the feasibility test of animation-based teaching material on explanation text. This research used R&D method. The subjects of research were XI grades students of MAN 2 Aceh Tenggara. This research used non-test and test instruments. The result of the research indicated that the pre-test value was at a “fairly good” category and after using animation on post-test was at a “very good” category. Thus, the development of animation-based teaching material on explanation text is appropriate to be applied.
Keywords: development, teaching material, explanation text, animation
Abstrak
Permasalahan dalam penelitian ini adalah tingkat efektivitas dan kelayakan pengembangan materi ajar teks eksplanasi berbasis animasi pada siswa kelas XI MAN 2 Aceh Tenggara tahun pembelajaran 2018/2019. Uji efektivitas tersebut dilakukan oleh guru dan siswa sedangkan uji kelayakan produk diuji oleh tim ahli yaitu dosen dan guru bahasa Indonesia. Tujuan penelitian ini adalah untuk mengembangkan proses bahan ajar berbasis animasi, untuk mengetahui efektivitas bahan ajar berbasis animasi, dan untuk mengetahui uji kelayakan bahan ajar berbasis animasi pada materi ajar teks eksplanasi. Penelitian ini menggunakan metode R&D. Subjek penelitian ini adalah seluruh siswa kelas XI MAN 2 Aceh Tenggara. Penelitian ini menggunakan instrumen nontes dan tes. Hasil penelitian ini menjelaskan bahwa pengembangan materi ajar teks eksplanasi berbasis animasi menunjukkan bahwa nilai pre-tes berada pada kategori cukup baik dan setelah dilakukan inovasi pembaharuan menggunakan animasi berada pada kategori sangat baik. Dengan demikian pengembangan materi ajar teks eksplanasi berbasis animasi layak digunakan dalam pengembangan bahan ajar.
Kata kunci: pengembangan, materi ajar, teks eksplanasi, animas
Author retrospective for "Software trace cache"
No full textIn superscalar processors, capable of issuing and executing multiple instructions per cycle, fetch performance represents an upper bound to the overall processor performance. Unless there is some form of instruction re-use mechanism, you cannot execute instructions faster than you can fetch them.
Instruction Level Parallelism, represented by wide issue out oforder superscalar processors, was the trending topic during the end of the 90's and early 2000's. It is indeed the most promising way to continue improving processor performance in a way that does not impact application development, unlike current multicore architectures which require parallelizing the applications (a process that is still far from being automated in the general case). Widening superscalar processor issue was the promise of neverending improvements to single thread performance, as identified by Yale N. Patt et al. in the 1997 special issue of IEEE Computer about "Billion transistor processors" [1].
However, instruction fetch performance is limited by the control flow of the program. The basic fetch stage implementation can read instructions from a single cache line, starting from the current fetch address and up to the next control flow instruction. That is one basic block per cycle at most.
Given that the typical basic block size in SPEC integer benchmarks is 4-6 instructions, fetch performance was limited to those same 4-6 instructions per cycle, making 8-wide and 16-wide superscalar processors impractical. It became imperative to find mechanisms to fetch more than 8 instructions per cycle, and that meant fetching more than one basic block per cycle
Author retrospective for "Software trace cache"
No full textIn superscalar processors, capable of issuing and executing multiple instructions per cycle, fetch performance represents an upper bound to the overall processor performance. Unless there is some form of instruction re-use mechanism, you cannot execute instructions faster than you can fetch them.
Instruction Level Parallelism, represented by wide issue out oforder superscalar processors, was the trending topic during the end of the 90's and early 2000's. It is indeed the most promising way to continue improving processor performance in a way that does not impact application development, unlike current multicore architectures which require parallelizing the applications (a process that is still far from being automated in the general case). Widening superscalar processor issue was the promise of neverending improvements to single thread performance, as identified by Yale N. Patt et al. in the 1997 special issue of IEEE Computer about "Billion transistor processors" [1].
However, instruction fetch performance is limited by the control flow of the program. The basic fetch stage implementation can read instructions from a single cache line, starting from the current fetch address and up to the next control flow instruction. That is one basic block per cycle at most.
Given that the typical basic block size in SPEC integer benchmarks is 4-6 instructions, fetch performance was limited to those same 4-6 instructions per cycle, making 8-wide and 16-wide superscalar processors impractical. It became imperative to find mechanisms to fetch more than 8 instructions per cycle, and that meant fetching more than one basic block per cycle.Postprint (published version
Conflitos de uso do solo na gestão ambiental de bacias hidrográficas: BH Urubici
No full textDissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Engenharia Ambiental
Applying deep learning image enhancement methods to improve person re-identification
No full textPerson re-identification has gained significant attention in recent years due to its numerous practical applications in video surveillance. However, while artificial intelligence and deep learning methods have enabled substantial progress in particular aspects of this domain, putting together those individual advances to generate practical systems remains a computer vision challenge. Existing methods are typically designed assuming the target person’s images are captured under uniform, stable conditions with similar lighting levels, but this assumption may not hold in real-world scenarios, such as outdoor monitoring over 24 h, as image quality can vary considerably throughout day and night. In this paper, we propose a framework that incorporates image enhancement techniques to improve the performance of a person re-identification model. The proposed approach achieves a significant improvement in a demanding re-identification dataset, raising the mAP from 9.0% using a zero-shot baseline to 65.8% through the combined use of low-light image enhancement methods and noise reduction.111,8156,0Q1Q2SCIE11,
Towards facial expression robustness in multi-scale wild environments
No full textFacial expressions are dynamic processes that evolve over temporal segments, including onset, apex, offset, and neutral. However, previous works on automatic facial expression analysis have mainly focused on the recognition of discrete emotions, neglecting the continuous nature of these processes. Additionally, facial images captured from videos in the wild often have varying resolutions due to fixed-lens cameras. To address these problems, our objective is to develop a robust facial expression recognition classifier that provides good performance in such challenging environments. We evaluated several state-of-the-art models on labeled and unlabeled collections and analyzed their performance at different scales. To improve performance, we filtered the probabilities provided by each classifier and demonstrated that this improves decision-making consistency by more than 10%, leading to accuracy improvement. Finally, we combined the models’ backbones into a temporal-sequence classifier, leveraging this consistency-performance trade-off and achieving an additional improvement of 9.6%.195184110,606Q210,0
Towards Bi-Hemispheric Emotion Mapping Through EEG: A Dual-Stream Neural Network Approach
No full textEmotion classification through EEG signals plays
a significant role in psychology, neuroscience, and humancomputer interaction. This paper addresses the challenge of
mapping human emotions using EEG data in the Mapping
Human Emotions through EEG Signals FG24 competition. Subjects mimic the facial expressions of an avatar, displaying fear,
joy, anger, sadness, disgust, and surprise in a VR setting. EEG
data is captured using a multi-channel sensor system to discern
brain activity patterns. We propose a novel two-stream neural
network employing a Bi-Hemispheric approach for emotion
inference, surpassing baseline methods and enhancing emotion
recognition accuracy. Additionally, we conduct a temporal analysis revealing that specific signal intervals at the beginning and
end of the emotion stimulus sequence contribute significantly
to improve accuracy. Leveraging insights gained from this
temporal analysis, our approach offers enhanced performance
in capturing subtle variations in the states of emotions.
A large-scale analysis of athletes’ cumulative race time in running events
No full textAction recognition models and cumulative race time (CRT) are practical tools in sports analytics, providing insights into athlete performance, training, and strategy. Measuring CRT allows for identifying areas for improvement, such as specific sections of a racecourse or the effectiveness of different strategies. Human action recognition (HAR) algorithms can help to optimize performance, with machine learning and artificial intelligence providing real-time feedback to athletes. This paper presents a comparative study of HAR algorithms for CRT regression, examining two important factors: the frame rate and the regressor selection. Our results indicate that our proposal exhibits outstanding performance for short input footage, achieving a mean absolute error of 11 min when estimating CRT for runners that have been on the course for durations ranging from 8 to 20 h.292282100,606Q210,0
