FPGA-based implementation of classification techniques: A survey

Recently, a number of classification techniques have been introduced. However, processing large dataset in a reasonable time has become a major challenge. This made classification task more complex and expensive in calculation. Thus, the need for solutions to overcome these constraints such as field programmable gate arrays (FPGAs). In this paper, we give an overview of the various classification techniques. Then, we present the existing FPGA based implementation of these classification methods. After that, we investigate the confronted challenges and the optimizations strategies. Finally, we highlight the hardware accelerator architectures and tools for hardware design suggested to improve the FPGA implementation of classification methods.     

小型核桃脱壳分选一体机的设计

核桃不仅营养价值极高,而且核桃壳的药用价值也非常高,国内小企业和家庭在核桃硬壳脱壳加工环节,一般采用人工破壳取仁的方式,这种方式劳动强度大,人工成本高且不卫生;针对这个问题设计了一款小型的硬壳脱壳,壳仁分离分选的机器来提高生产效率,减少成本,提高收入。     

Residual attention-based tracking-by-detection network with attention-driven data augmentation

Tracking-by-detection (TBD) is a significant framework for visual object tracking. However, current trackers are usually updated online based on random sampling with a probability distribution. The performance of the learning-based TBD trackers is limited by the lack of discriminative features, especially when the background is full of semantic distractors. We propose an attention-driven data augmentation method, in which a residual attention mechanism is integrated into the TBD tracking network as supplementary references to identify discriminative image features. A mask generating network is used to simulate changes in target appearances to obtain positive samples, where attention information and image features are combined to identify discriminative features. In addition, we propose a method for mining hard negative samples, which searches for semantic distractors with the response of the attention module. The experiments on the OTB2015, UAV123, and LaSOT benchmarks show that this method achieves competitive performance in terms of accuracy and robustness.     

Structural Aspects and Prediction of Calmodulin-Binding Proteins

Calmodulin (CaM) is an important intracellular protein that binds Ca²⁺ and functions as a critical second messenger involved in numerous biological activities through extensive interactions with proteins and peptides. CaM’s ability to adapt to binding targets with different structures is related to the flexible central helix separating the N- and C-terminal lobes, which allows for conformational changes between extended and collapsed forms of the protein. CaM-binding targets are most often identified using prediction algorithms that utilize sequence and structural data to predict regions of peptides and proteins that can interact with CaM. In this review, we provide an overview of different CaM-binding proteins, the motifs through which they interact with CaM, and shared properties that make them good binding partners for CaM. Additionally, we discuss the historical and current methods for predicting CaM binding, and the similarities and differences between these methods and their relative success at prediction. As new CaM-binding proteins are identified and classified, we will gain a broader understanding of the biological processes regulated through changes in Ca²⁺ concentration through interactions with CaM.     

Vulnerable objects detection for autonomous driving: A review

Object detection performed by Autonomous Vehicles (AV)s is a crucial operation that comes ahead of various autonomous driving tasks, such as object tracking, trajectories estimation, and collision avoidance. Dynamic road elements (pedestrians, cyclists, vehicles) impose a greater challenge due to their continuously changing location and behaviour. This paper presents a comprehensive review of the state-of-the-art object detection technologies focusing on both the sensory systems and algorithms used. It begins with a brief introduction on the autonomous driving operations and challenges. Then, different sensory systems employed on existing AVs are elaborated while illustrating their advantages, limitations and applications. Also, sensory systems employed by different research are reviewed. Moreover, due to the significant role Deep Neural Networks (DNN)s are playing in object detection tasks, different DNN-based networks are also highlighted. Afterwards, previous research on dynamic objects detection performed by AVs are reviewed in tabular forms. Finally, a conclusion summarizes the outcomes of the review and suggests future work towards the development of vehicles with higher automation levels.     

Microstructure and electromagnetic properties of LiFe5O8 ferrite ceramics prepared from wet- and dry-milled powders

The effect of dry and wet ball milling of LiFe₅O₈ ferrite powder on the microstructure and electromagnetic properties of ferrite ceramics was studied using XRD analysis, scanning electron microscopy, dilatometry, thermogravimetry, calorimetry, and measurement of specific magnetization and electrical resistance. The sintering temperature was 1050 °C; the sintering time was 2 h. It was found that ferrite fabricated from dry-milled powder exhibits an ordered α-LiFe₅O₈ phase with bulk density of 91%. Its saturation magnetization and Curie temperature are 55 emu/g and 628°С, respectively. Specific electrical resistance is 4?10⁶ Ω cm. Wet milling in isopropyl alcohol causes formation of a disordered β-LiFe₅O₈ phase. Ceramics produced by this method shows higher bulk density (97%) and low porosity, and an order of magnitude lower resistivity. Its saturation magnetization and Curie temperature are 51 emu/g and 607°С, respectively.     

High dielectric constant of NiFe2O4–LaFeO3 nanocomposite: Interfacial conduction and dielectric loss

Materials exhibiting colossal dielectric constant are the most sought-after materials due to their variety of applications in various electronics industries. NiFe₂O₄ and LaFeO₃ belonging to the spinel and perovskite structures, respectively, were coupled into a nanocomposite by adapting a one-pot sol-gel synthesis. The ratio of NiFe₂O₄:LaFeO₃ was varied and the synthesized materials were studied for their dielectric behaviors. Interestingly, among the samples studied, the nanocomposite with the ratio of 1:2 of NiFe₂O₄–LaFeO₃ exhibited a high dielectric constant value of 10390 at a frequency of 1 kHz with a several-fold increase in conductivity. The high conductivity resulted in a high dielectric loss. The origin of such a high dielectric constant and loss have been attributed to the Maxwell-Wagner type space charge polarization arising from the microstructure that consists of large and continuous grain boundaries, and the conducting phase at the interface, respectively.     

Technology enhanced learning of quantitative critical thinking

A Quantitative Critical Thinking (QCT) software tool was developed in this study to facilitate students’ learning of quantitative critical thinking via repeated practice by chemical engineering students reading a core module called fluid-solid systems. The software tool generated detailed calculation steps to typical engineering design problems encountered in this module that contained weaknesses, flaws or even errors. Students utilized the software tool to practice identifying these weaknesses, flaws or errors in the design solutions and then present a better or correct design by applying the concepts and knowledge acquired in the module. Since the QCT software tool was built upon an existing design software tool that was able to generate the correct, detailed design calculation steps to design problems, students were able to check their own design calculations against those presented by the software tool during this second learning step, thereby engaging in and learning quantitative critical thinking via a repeated practice approach. The software tool was successful in enhancing the performance of second-year undergraduate students in solving a question that required quantitative critical thinking in the final examination of the module. The average percentage scores achieved by students for the question who reported higher frequencies of usage of the software were generally higher than those who reported lower frequencies of usage or did not utilize the software tool throughout the semester.     

煤矿锚杆机除尘马达改进

针对煤矿进口锚杆机除尘马达频繁出现故障的情况,通过排查除尘装置的安装方式和监测马达工作时的压力状态,查找故障原因,并制定解决方案。通过马达外接单向阀,可满足马达进油口最低安全压力限制的要求,解决了马达频繁损坏的问题,保障了设备工作的稳定性,提高了工作效率。     

Synthesis,Anticancer Activity,Structure-Activity Relationship and Mechanistic Investigations of Falcarindiol Analogues

Forty samples of optically active falcarindiol analogues are synthesized by using the easily available C2 symmetric (R)- and (S)-1,1’-binaphth-2-ol (BINOL) in combination with Ti(OⁱPr)₄, Zn powder and EtI. Their anticancer activities on Hccc-9810, HepG2, MDA-MB-231, Hela, MG-63 and H460 cells are assayed to elucidate their structure-activity relationships. These results showed that the falcarindiol analogue (3R,8S)- 2 i with the terminal double bond has the most potent anti-proliferation effect on Hccc-9810 cells with IC₅₀ value of 0.46 μM. The falcarindiol analogue (3R,8S)- 2 i can induce obvious Hccc-9810 cell apoptosis in a concentration-dependent manner by Hoechst staining and flow cytometry analysis. The proposed mechanism suggests that the falcarindiol analogue (3R,8S)- 2 i increases LDH release and MDA content, and reduces the levels of SOD activity, which lead to the accumulation of oxidative stress and induce apoptosis in Hccc-9810 cells.