Investigation of Sheltering Effect on Global Solar Radiation Data Measured by Weather Stations

In instalment of pyranometers at the weather stations for measuring global solar radiation, it often cannot avoid appearance of obstacles in their surroundings. Investigation of sheltering effect on measurement of global solar radiation is performed through introducing the shelter view factor. Evaluation of the shelter view factor is made by means of a fisheye-lens photograph together with the calculation method developed by Steyn (1980). Taitung weather station (TWS) is chosen for the study. The shelter view factor for the pyranometer installed at TWS is estimated to be 11.8%. Measurements of global solar radiation are conducted at a place where is located nearby TSW but with the condition of zero shelter view factor. Comparison of the data measured at these two sites indicates 4% - 25% deviations of global solar radiation observed in different months of 2017. It suggests a need of the correction to the sheltering effect in the measuring process of global solar radiation at the weather stations except those who are not subject to surrounding obstacles in the sky dome

Naaloss: Rethinking the objective of speech enhancement

Reducing noise interference is crucial for automatic speech recognition (ASR) in a real-world scenario. However, most single-channel speech enhancement (SE) generates "processing artifacts" that negatively affect ASR performance. Hence, in this study, we suggest a Noise- and Artifacts-aware loss function, NAaLoss, to ameliorate the influence of artifacts from a novel perspective. NAaLoss considers the loss of estimation, de-artifact, and noise ignorance, enabling the learned SE to individually model speech, artifacts, and noise. We examine two SE models (simple/advanced) learned with NAaLoss under various input scenarios (clean/noisy) using two configurations of the ASR system (with/without noise robustness). Experiments reveal that NAaLoss significantly improves the ASR performance of most setups while preserving the quality of SE toward perception and intelligibility. Furthermore, we visualize artifacts through waveforms and spectrograms, and explain their impact on ASR

Set voltage distribution stabilized by constructing an oxygen reservoir in resistive random access memory

In this letter, the instability mechanism of RRAM was investigated, and a technique was developed to stabilize the distribution of high resistance state (HRS) and better concentrate the SET voltage. In previous research, we found that an interface-type switching characteristic was observed on the I-V curve beneath the filament-type switching behavior, owing to the oxygen accumulation effect. In this letter, this interface-type switching characteristic is used to fit the natural distribution of HRS for an analysis of the instability mechanism. According to the results, the reason for the HRS distribution is the accumulation of extra oxygen ions which are left over from a lower degree of oxygen and oxygen vacancy recombination during the reset process. We propose a solution which creates an extra oxygen reservoir by changing the surface topography of the electrode to store the surplus oxygen ions from the reset process, eliminating the accumulation effect, and indeed improving stability. Please click Additional Files below to see the full abstract

On the Improvement of Wiener Attack on RSA with Small Private Exponent

RSA system is based on the hardness of the integer factorization problem (IFP). Given an RSA modulus N=pq, it is difficult to determine the prime factors p and q efficiently. One of the most famous short exponent attacks on RSA is the Wiener attack. In 1997, Verheul and van Tilborg use an exhaustive search to extend the boundary of the Wiener attack. Their result shows that the cost of exhaustive search is 2r+8 bits when extending the Weiner's boundary r bits. In this paper, we first reduce the cost of exhaustive search from 2r+8 bits to 2r+2 bits. Then, we propose a method named EPF. With EPF, the cost of exhaustive search is further reduced to 2r-6 bits when we extend Weiner's boundary r bits. It means that our result is 214 times faster than Verheul and van Tilborg's result. Besides, the security boundary is extended 7 bits

Nonlinear dynamic responses of shell structures using vector form intrinsic finite element method

In this paper, in order to compute nonlinear dynamic responses of shell structures, formulations of the internal forces of the shell element in vector form intrinsic finite element (VFIFE) method are developed. This novel shell element is named by VFIFE-DKT element. These elements are to compute internal forces from the deformations and the motion of the shell structures. The VFIFE method is a particle-based method. They have three key VFIFE processes such as the point value description, path element and convected material frame. Thus, the shell structure is represented by finite particles. Each particle is subjected to the external forces and internal forces. The particle satisfies the Newton’s Law. A fictitious reversed rigid body motion is used to remove the rigid body motion from the deformations of the element. The internal forces of the element in deformation coordinates satify the equilibrium equations. Through the numerical examples of the benchmark structures undergo extermly-large displacements, rotation and motion, the proposed procedures using the novel element demonstrates its accuracy and efficiency

Ontology-based Fuzzy Markup Language Agent for Student and Robot Co-Learning

An intelligent robot agent based on domain ontology, machine learning mechanism, and Fuzzy Markup Language (FML) for students and robot co-learning is presented in this paper. The machine-human co-learning model is established to help various students learn the mathematical concepts based on their learning ability and performance. Meanwhile, the robot acts as a teacher's assistant to co-learn with children in the class. The FML-based knowledge base and rule base are embedded in the robot so that the teachers can get feedback from the robot on whether students make progress or not. Next, we inferred students' learning performance based on learning content's difficulty and students' ability, concentration level, as well as teamwork sprit in the class. Experimental results show that learning with the robot is helpful for disadvantaged and below-basic children. Moreover, the accuracy of the intelligent FML-based agent for student learning is increased after machine learning mechanism.Comment: This paper is submitted to IEEE WCCI 2018 Conference for revie