Efficient Neural Network Approximation via Bayesian Reasoning

Approximate Computing (AxC) trades off between the accuracy required by the user and the precision provided by the computing system to achieve several optimizations such as performance improvement, energy, and area reduction. Several AxC techniques have been proposed so far in the literature. They work at different abstraction levels and propose both hardware and software implementations. The standard issue of all existing approaches is the lack of a methodology to estimate the impact of a given AxC technique on the application-level accuracy. This paper proposes a probabilistic approach based on Bayesian networks to quickly estimate the impact of a given approximation technique on application-level accuracy. Moreover, we have also shown how Bayesian networks allow a backtrack analysis that automatically identifies the most sensitive components. That influence analysis dramatically reduces the space exploration for approximation techniques. Preliminary results on a simple artificial neural network shown the efficiency of the proposed approach

Changing the approach to sustainable constructions: An adaptive mix-design calibration process for earth composite materials

One major drawback of excavation earth-based composite construction materials is the variability in excavation earth characteristics from site to site. This variability can affect certain physical properties, and, in turn, the design models used to create a structure. To solve this problem, a methodology has been developed to predict the physical properties of earth-based composites for any mix-design variation, which enables a robust structural design process. This new methodology has been tested for Shot-earth, a new class of earth-based composite material made using high rates of excavation earth, aggregates, and a low rate of stabilization if needed. Shot-earth is placed using a high-speed dry-mix process. The methodology was tested by preparing small, inexpensive specimens through a process that simulates the dry-process used to fabricate Shot-earth in the field. An adaptive technique, used in conjunction with the experimental methodology, allows for the identification of the variant of possible Shot-earth mix-designs that provides optimal physical properties for a specific project. This technique is potentially applicable to any type of earth-based composite. The proposed methodology’s reliability enables a fast and cost-effective detailing of Shot-earth constructions

A low-cost approach for determining the impact of Functional Approximation

Approximate Computing (AxC) trades off between the level of accuracy required by the user and the actual precision provided by the computing system to achieve several optimizations such as performance improvement, energy, and area reduction etc.. Several AxC techniques have been proposed so far in the literature. They work at different abstraction level and propose both hardware and software implementations. The common issue of all existing approaches is the lack of a methodology to estimate the impact of a given AxC technique on the application-level accuracy. In this paper, we propose a probabilistic approach to predict the relation between component-level functional approximation and application-level accuracy. Experimental results on a set of benchmark application show that the proposed approach is able to estimate the approximation error with good accuracy and very low computation time

Structural design of reinforced earthcrete (ReC) beams

This paper presents the results of an extensive experimental campaign aimed at evaluating the feasibility of using steel-reinforced earthen materials for load-bearing structural applications, with a focus on a new category termed "shot-earth". Addressing excavated soil, a major source of construction waste, shot-earth demonstrates remarkable properties, such as notable green strength and reduced water sensitivity. The experimental program includes four-point bending tests on steel-reinforced shot-earth beams, along with pull-out tests to assess the adherence between ribbed steel bars and shot-earth. A flexural design approach, traditionally suited for reinforced concrete, is presented and validated to establish a reliable model for reinforced shot-earth elements in bending state. These findings suggest that leveraging existing models for reinforced concrete can overcome some traditional challenges associated with earth-based constructions, promoting them as a viable and ecological alternative to conventional construction materials

Identification of the agent of grapevine fleck disease

An antiserum against an Italian isolate of grapevine phloem-limited isometric virus (GPLIV) was used in an ELISA survey carried out for assessing the natural distribution of the virus and its association with fleck disease. A total of 591 vines of Vitis rupestris were checked for the presence of GPLIV. Of 150 plants with fleck symptoms, 138 (92 %) were ELISA-positive and 12 (8 %) negative. Of 441 symptomless V. rupestris, 435 (98,6 %) were ELISA-negative and 6 (1,4 %) positive for GPLIV. The virus was detected in about 30 % of 694 vines of different origin grown in Apulia (Southern Italy). The highest infection (53 %) was in a commercial vineyard of cv. Italia and the lowest (8 %) in a plot of certified and visually selected rootstocks. Fleck-infected, but not fleck-free V. rupestris contained virus particles and vesiculated inclusion bodies in phloem tissues. LN 33 plantlets derived from in vitro culture of meristem tips from ELISA-positive fleck-infected mother plants were found to be free from GPLIV, as ascertained by ELISA and thin-sectioning. These vines failed to induce fleck symptoms when grafted on V. rupestris. It is concluded that GPLIV is the agent of fleck and, therefore, it should be renamed grapevine fleck virus (GFKV)