Normal accidents. Living with high-risk technologies

Industry 4.0, digitization, and opportunities for sustainability

Conventional farming has led to extensive use of chemicals and, in turn, to negative environmental impacts such as soil erosion, groundwater pollution and atmosphere contamination. Farming systems should be more sustainable to reach economical and social profitability as well as environmental preservation. A possible solution is to adopt precision agriculture, a win–win option for sustaining food production without degrading the environment. Precision technologies are used for gathering information about spatial and temporal differences within the field in order to match inputs to site-specific field conditions. Here we review reports on the precision N management of wheat crop. The aims are to perform an investigation both on approaches and results of site-specific N management of wheat and to analyse performance and sustainability of this agricultural practice. In this context, we analysed literature of the last 10–15 years. The major conclusions are: (a) before making N management decisions, both the measurement and understanding of soil spatial variability and the wheat N status are needed. Complementary use of different sensors has improved soil properties assessment at relatively low cost; (b) results show the usefulness of airborne images, remote and proximal sensing for predicting crop N status by responsive in-season management approaches; (c) red edge and near-infrared bands can penetrate into higher vegetation fraction of the canopy. These narrowbands better estimated grain yield, crop N and water status, with R
 2 higher than 0.70. In addition, different hyperspectral vegetation indices accounted for a high variability of 40–75 % of wheat N status; (d) various diagnostic tools and procedures have been developed in order to help wheat farmers for planning variable N rates. In-season adjustments in N fertilizer management can account for the specific climatic conditions and yield potential since less than 30 % of spatial variance could show temporal stability; (e) field studies in which sensor-based N management systems were compared with common farmer practices showed high increases in the N use efficiency of up to 368 %. These systems saved N fertilizers, from 10 % to about 80 % less N, and reduced residual N in the soil by 30–50 %, without either reducing yields or influencing grain quality; (f) precision N management based on real-time sensing and fertilization had the highest profitability of about $5–60 ha−1 compared to undifferentiated applications.

/pdf/precision-nitrogen-management-of-wheat-a-review-4ix4bsiuzz.pdf

Precision nitrogen management of wheat. A review

Characterizing ecological relationships between viruses, bacteria and protists in the ocean are critical to understanding ecosystem function, yet these relationships are infrequently investigated together We evaluated these relationships through microbial association network analysis of samples collected approximately monthly from March 2008 to January 2011 in the surface ocean (0–5 m) at the San Pedro Ocean Time series station Bacterial, T4-like myoviral and protistan communities were described by Automated Ribosomal Intergenic Spacer Analysis and terminal restriction fragment length polymorphism of the gene encoding the major capsid protein (g23) and 18S ribosomal DNA, respectively Concurrent shifts in community structure suggested similar timing of responses to environmental and biological parameters We linked T4-like myoviral, bacterial and protistan operational taxonomic units by local similarity correlations, which were then visualized as association networks Network links (correlations) potentially represent synergistic and antagonistic relationships such as viral lysis, grazing, competition or other interactions We found that virus–bacteria relationships were more cross-linked than protist–bacteria relationships, suggestive of increased taxonomic specificity in virus–bacteria relationships We also found that 80% of bacterial–protist and 74% of bacterial–viral correlations were positive, with the latter suggesting that at monthly and seasonal timescales, viruses may be following their hosts more often than controlling host abundance

https://dornsife.usc.edu/assets/sites/463/docs/SPOT_related_publications/2014_Chow.pdf

Top-down controls on bacterial community structure: microbial network analysis of bacteria, T4-like viruses and protists.

The design structure matrix (DSM), also called the dependency structure matrix, has become a widely used modeling framework across many areas of research and practice. The DSM brings advantages of simplicity and conciseness in representation, and, supported by appropriate analysis, can also highlight important patterns in system architectures (design structures), such as modules and cycles. A literature review in 2001 cited about 100 DSM papers; there have been over 1000 since. Thus, it is useful to survey the latest DSM extensions and innovations to help consolidate progress and identify promising opportunities for further research. This paper surveys the DSM literature, primarily from archival journals, and organizes the developments pertaining to building, displaying, analyzing, and applying product, process, and organization DSMs. It then addresses DSM applications in other domains, as well as recent developments with domain mapping matrices (DMMs) and multidomain matrices (MDMs). Overall, DSM methods are becoming more mainstream, especially in the areas of engineering design, engineering management, management/organization science, and systems engineering. Despite significant research contributions, however, DSM awareness seems to be spreading more slowly in the realm of project management.

/pdf/design-structure-matrix-extensions-and-innovations-a-survey-23bfwcuu85.pdf

Design Structure Matrix Extensions and Innovations: A Survey and New Opportunities

Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) technologies, which has widespread usage in industry, is also regarded as an ideal solution for automated agriculture because it fulfils the accuracy, reliability and availability requirements of industrial and agricultural applications. Agriculture applications use position, velocity and heading information for automated vehicle guidance and control to enhance the yield and quality of the crop, and in order to vary the application of fertilizer and herbicides according to soil heterogeneity at sub-field level. A loosely coupled GPS/INS integration algorithm known as "AhrsKf" is introduced for automated agriculture vehicle guidance and control utilizing MEMS inertial sensors and GPS. The AhrsKf can produce high-frequency attitude solutions for the vehicle's guidance and control system, by using inputs from a single survey grade L1/L2 antenna, eliminating the need for the previous two antenna solutions. Given its agricultural application, the AhrsKf has been implemented with some specific design features to improve the accuracy of the attitude solution including, temperature compensation of the inertial sensors, and the aid of plough lines of farm lands. To evaluate the AhrsKf solution, two benchmarking tests have been conducted by using a three-antenna GPS system and NovAtel's SPAN-CPT. The results have demonstrated that the AhrsKf solution is stable and can correctly track the movement of the farming vehicle.

Attitude determination by integration of MEMS inertial sensors and GPS for autonomous agriculture applications

Vehicular communication technologies are on their way to be recognized as staples of modern societies. One important challenge to safety-related applications of vehicular communication is provision of semi-precise positioning. Cooperative positioning is proposed for that purpose, and of course from research point of view is very attractive. From the practical point of view the attractiveness of cooperative positioning lies in its independence from any major additional infrastructure other than the vehicular communication systems. This paper introduces a new positioning algorithm for localization of mobile networks, in general, that applies directly to vehicular networks. The algorithm is based on the well known multidimensional algorithm and shows impressive performance compared to its counterparts in the vehicular positioning literature.

A modified multidimensional scaling with embedded particle filter algorithm for cooperative positioning of vehicular networks

Modular analysis using the Design Structure Matrix (DSM) identifies the interactions between groups of components, and clusters them into modules in order to achieve competitive advantages in the product design processes. In this paper, a hybrid approach, based on multidimensional scaling (MDS) and clustering methods, is applied to component DSM for product architecting. The motivation is to facilitate better modularizations that enhance different product attributes in various product lifecycle stages. An experimental framework is developed to evaluate the performance of MDS clustering. Three MDS methods and four ubiquitous clustering methods are compared to reveal the most suitable for DSMs. The experimental results with several examples demonstrate that the effectiveness of MDS clustering, and show the superiority of non-metric MDS, SMACOF (Scaling by MAjorizing a Complicated Function) and hierarchical/cosine methods. These methods are capable of partitioning the product architecture into a set ...

Product modular analysis with design structure matrix using a hybrid approach based on MDS and clustering

In this work, we are motivated by the observation that previous considerations of appropriate complexity measures have not directly addressed the fundamental issue that the complexity of any particular matter or thing has a significant subjective component in which the degree of complexity depends on available frames of reference. Any attempt to remove subjectivity from a suitable measure therefore fails to address a very significant aspect of complexity. Conversely, there has been justifiable apprehension toward purely subjective complexity measures, simply because they are not verifiable if the frame of reference being applied is in itself both complex and subjective. We address this issue by introducing the concept of subjective simplicity—although a justifiable and verifiable value of subjective complexity may be difficult to assign directly, it is possible to identify in a given context what is “simple” and, from that reference, determine subjective complexity as distance from simple. We then propose a generalized complexity measure that is applicable to any domain, and provide some examples of how the framework can be applied to engineered systems. © 2016 Wiley Periodicals, Inc. Complexity, 2016

A general framework for measuring system complexity

Modularity is a natural instrument and a ubiquitous practice for the engineering of human-made systems. However, modularization remains more of an art than a science; to the extent that the notion of optimal modularity is rarely used in engineering design. We prove that optimal modularity exists (at least for construction)—and is achieved through balanced modularization as structural symmetry in the distribution of the sizes of modules. We show that system construction cost is highly sensitive to both the number of modules and the modularization structure. However, this sensitivity has an inverse relationship with process capability and is minimal for highly capable construction processes with small process uncertainties. Conclusions are reached by a Bayesian estimation technique for a relatively simple construction model originally introduced by Herbert Simon for the hypothetical production of a linear structure, taking into account errors that may occur in the work associated with the production of the links between the nodes in the structure for varied numbers of modules. © 2015 Wiley Periodicals, Inc. Complexity, 2015

Mahmoud Efatmaneshnik

Papers

Attitude determination by integration of MEMS inertial sensors and GPS for autonomous agriculture applications

A modified multidimensional scaling with embedded particle filter algorithm for cooperative positioning of vehicular networks

Product modular analysis with design structure matrix using a hybrid approach based on MDS and clustering

A general framework for measuring system complexity

On optimal modularity for system construction