Energy Efficient Error Resilient Multiplier Using Low-power Compressors

The approximate hardware design can save huge energy at the cost of errors incurred in the design. This article proposes the approximate algorithm for low-power compressors, utilized to build approximate multiplier with low energy and acceptable error profiles. This article presents two design approaches (DA1 and DA2) for higher bit size approximate multipliers. The proposed multiplier of DA1 have no propagation of carry signal from LSB to MSB, resulted in a very high-speed design. The increment in delay, power, and energy are not exponential with increment of multiplier size ( n ) for DA1 multiplier. It can be observed that the maximum combinations lie in the threshold Error Distance of 5% of the maximum value possible for any particular multiplier of size n . The proposed 4-bit DA1 multiplier consumes only 1.3 fJ of energy, which is 87.9%, 78%, 94%, 67.5%, and 58.9% less when compared to M1, M2, LxA, MxA, accurate designs respectively. The DA2 approach is recursive method, i.e., n -bit multiplier built with n/2-bit sub-multipliers. The proposed 8-bit multiplication has 92% energy savings with Mean Relative Error Distance (MRED) of 0.3 for the DA1 approach and at least 11% to 40% of energy savings with MRED of 0.08 for the DA2 approach. The proposed multipliers are employed in the image processing algorithm of DCT, and the quality is evaluated. The standard PSNR metric is 55 dB for less approximation and 35 dB for maximum approximation.

An artificial neural-network approach to identify motor hotspot for upper-limb based on electroencephalography: a proof-of-concept study

Background To apply transcranial electrical stimulation (tES) to the motor cortex, motor hotspots are generally identified using motor evoked potentials by transcranial magnetic stimulation (TMS). The objective of this study is to validate the feasibility of a novel electroencephalography (EEG)-based motor-hotspot-identification approach using a machine learning technique as a potential alternative to TMS. Methods EEG data were measured using 63 channels from thirty subjects as they performed a simple finger tapping task. Power spectral densities of the EEG data were extracted from six frequency bands (delta, theta, alpha, beta, gamma, and full) and were independently used to train and test an artificial neural network for motor hotspot identification. The 3D coordinate information of individual motor hotspots identified by TMS were quantitatively compared with those estimated by our EEG-based motor-hotspot-identification approach to assess its feasibility. Results The minimum mean error distance between the motor hotspot locations identified by TMS and our proposed motor-hotspot-identification approach was 0.22 ± 0.03 cm, demonstrating the proof-of-concept of our proposed EEG-based approach. A mean error distance of 1.32 ± 0.15 cm was measured when using only nine channels attached to the middle of the motor cortex, showing the possibility of practically using the proposed motor-hotspot-identification approach based on a relatively small number of EEG channels. Conclusion We demonstrated the feasibility of our novel EEG-based motor-hotspot-identification method. It is expected that our approach can be used as an alternative to TMS for motor hotspot identification. In particular, its usability would significantly increase when using a recently developed portable tES device integrated with an EEG device.

On Ordinary Words of Standard Reed–Solomon Codes over Finite Fields

Reed–Solomon codes are widely used to establish a reliable channel to transmit information in digital communication which has a strong error correction capability and a variety of efficient decoding algorithm. Usually we use the maximum likelihood decoding (MLD) algorithm in the decoding process of Reed–Solomon codes. MLD algorithm relies on determining the error distance of received word. Dür, Guruswami, Wan, Li, Hong, Wu, Yue and Zhu et al. got some results on the error distance. For the Reed–Solomon code [Formula: see text], the received word [Formula: see text] is called an ordinary word of [Formula: see text] if the error distance [Formula: see text] with [Formula: see text] being the Lagrange interpolation polynomial of [Formula: see text]. We introduce a new method of studying the ordinary words. In fact, we make use of the result obtained by Y.C. Xu and S.F. Hong on the decomposition of certain polynomials over the finite field to determine all the ordinary words of the standard Reed–Solomon codes over the finite field of [Formula: see text] elements. This completely answers an open problem raised by Li and Wan in [On the subset sum problem over finite fields, Finite Fields Appl. 14 (2008) 911–929].

Observation on the Curative Effect of Microsurgery in 154 Children with Strabismus and Analysis of Its Influencing Factors

Strabismus is a common ophthalmic disease in the process of child body development, in which the two eyes cannot gaze at the target at the same time, and the incidence of this disease of children is higher. In children with esotropia, exotropia, and up and down strabismus and other typical symptoms, the cause is genetic, innerve, and refractive and regulated, and not receiving timely treatment may lead to stereo vision and diplopia and other phenomena, affecting their learning and life. Surgical treatment is the main treatment for strabismus at present. Traditional orthodontic surgery is performed by doctors under the naked eye, often due to improper operation or suture error and other factors, resulting in more postoperative complications, such as more tissue damage, conjunctival congestion, and muscle suture reaction, which seriously affect the clinical effect of surgical treatment. In recent years, with the continuous development of microsurgical technology, the correction of strabismus under a microscope has been widely carried out in clinic. The operation under the microscope makes the operation more delicate and accurate, overcomes the defects of traditional surgery, and highlights the advantages of minimally invasive surgery. The purpose of this study was to investigate the effect of microsurgical techniques in the treatment of strabismus in children and to analyze the factors influencing the outcome. The results showed that microsurgical strabismus correction in the treatment of strabismus children has short operation time, less intraoperative blood loss, short hospital stay, high efficiency, and less complications, which is worthy of popularization. Age, preoperative strabismus angle, refractive error, distance stereopsis injury, near stereoscopic injury, and duration of disease were all independent influencing factors of postoperative efficacy.

COREA: Delay- and Energy-Efficient Approximate Adder Using Effective Carry Speculation

This paper presents a delay- and energy-efficient approximate adder design exploiting an effective carry speculation scheme with error reduction. The proposed scheme reduces the delay and improves the energy efficiency without any significant accuracy degradation by effectively adding the predicted carry input using the OR operation. Additionally, the error reduction technique improves the overall computation accuracy at the expense of a few logic gates. As a result, the proposed adder achieves 3.84- and 7.79-times greater energy and energy-delay product (EDP) efficiencies than the traditional adder when implemented in 65-nm CMOS technology. In particular, when jointly analyzed with hardware accuracy, our design attains 69% and 70% reductions of the energy- and EDP-normalized mean error distance (NMED) products, respectively, compared to the other approximate adders under consideration. Furthermore, the proposed adder’s efficacy over the existing adders is demonstrated by adopting it in a machine learning application.

Improving the Quality Degradation of Dynamically Configurable Approximate Multipliers via Data Correlation

In the last few years, dynamically configurable approximate multipliers have been explored to tune the energy-quality trade-off in error-tolerant applications at runtime. Typically, the multiplier accuracy is adjusted by adding a constant correction factor equal to the multiplier mean error to the result, which is found offline assuming a predetermined input distribution. This paper describes a simple approach to update the correction term at runtime, thus adapting it to the actual incoming inputs. It takes advantage of the spatial and/or temporal correlation typically shown by input data in error-tolerant applications, such as image and video processing. When applied to a typical case study implemented with a commercial UTBB FDSOI 28 nm technology, the proposed approach shows an energy reduction of up to 34% at iso-quality and a quality improvement of up to +9 dB, −4× and +35% at iso-energy, in terms of peak-to-noise ratio (PSNR), normalized error distance (NED) and structural similarity index metric (SSIM) respectively, compared to the traditional technique based on a constant correction factor.

Effect of Non-canonical Spatial Symmetry on Subitizing

Subitizing refers to ability of people to accurately and effortlessly enumerate a small number of items, with a capacity around four elements. Previous research showed that “canonical” organizations, such as familiar layouts on a dice, can readily improve subitizing performance of people. However, almost all canonical shapes found in the world are also highly symmetrical; therefore, it is unclear whether previously reported facilitative effect of canonical organization is really due to canonicality, or simply driven by spatial symmetry. Here, we investigated the possible effect of symmetry on subitizing by using symmetrical, yet non-canonical, shape structures. These symmetrical layouts were compared with highly controlled random patterns (Experiment 1), as well as fully random and canonical patterns (Experiment 2). Our results showed that symmetry facilitates subitizing performance, but only at set size of 6, suggesting that the effect is insufficient to improve performance of people in the lower or upper range. This was also true, although weaker, in reaction time (RT), error distance measures, and Weber Fractions. On the other hand, canonical layouts produced faster and more accurate subitizing performances across multiple set sizes. We conclude that, although previous findings mixed symmetry in their canonical shapes, their findings on shape canonicality cannot be explained by symmetry alone. We also propose that our symmetrical and canonical results are best explained by the “groupitizing” and pattern recognition accounts, respectively.

An artificial Neural-Network Approach for Motor Hotspot Identification Based on Electroencephalography: A Proof-of-Concept Study

Background: To apply transcranial electrical stimulation (tES) to the motor cortex, motor hotspots are generally identified using motor evoked potentials by transcranial magnetic stimulation (TMS). The objective of this study is to validate the feasibility of a novel electroencephalography (EEG)-based motor-hotspot-identification approach using a machine learning technique as a potential alternative to TMS. Methods: EEG data were measured using 63 channels from thirty subjects as they performed a simple finger tapping task. Power spectral densities of the EEG data were extracted from six frequency bands (delta, theta, alpha, beta, gamma, and full) and were independently used to train and test an artificial neural network for motor hotspot identification. The 3D coordinate information of individual motor hotspots identified by TMS were quantitatively compared with those estimated by our EEG-based motor-hotspot-identification approach to assess its feasibility. Results: The minimum mean error distance between the motor hotspot locations identified by TMS and our proposed motor-hotspot-identification approach was 0.22 & 0.03 cm, demonstrating the proof-of-concept of our proposed EEG-based approach. A mean error distance of 1.32 & 0.15 cm was measured when using only nine channels attached to the middle of the motor cortex, showing the possibility of practically using the proposed motor-hotspot-identification approach based on a relatively small number of EEG channels. Conclusion: We demonstrated the feasibility of our novel EEG-based motor-hotspot-identification method. It is expected that our approach can be used as an alternative to TMS for motor hotspot identification. In particular, its usability would significantly increase when using a recently developed portable tES device integrated with an EEG device.