Publications

@article{Ivanov2019,

title = {A Walk Among the Data: Exploration and Anthropomorphism in Immersive Unit Visualizations},

author = {Alexander Ivanov and Kurtis Danyluk and Christian Jacob and Wesley Willett},

doi = {10.1109/MCG.2019.2898941},

year  = {2019},

date = {2019-05-01},

urldate = {2019-05-01},

journal = {IEEE Computer Graphics and Applications},

volume = {Special Issue May/June 2019},

abstract = {We examine the potential for immersive unit visualizations – interactive virtual environments populated with objects representing individual items in a dataset. Our explorations highlight how immersive unit visualizations in virtual reality can allow viewers to examine data at multiple scales,

support immersive exploration, and create affective, personal experiences with data.},

keywords = {data visualization, immersive analytics, virtual reality},

pubstate = {published},

tppubtype = {article}

}

@article{Kobsar2019,

title = {Validity of a novel method to measure vertical oscillation during running using a depth camera},

author = {D. Kobsar and S.T. Osis and Christian Jacob and Reed Ferber },

doi = {10.1016/j.jbiomech.2019.01.006},

year  = {2019},

date = {2019-03-06},

urldate = {2019-03-06},

journal = {Journal of Biomechanics},

volume = {85},

pages = {182-186},

abstract = {Recent advancements in low-cost depth cameras may provide a clinically accessible alternative to conventional three-dimensional (3D) multi-camera motion capture systems for gait analysis. However, there remains a lack of information on the validity of clinically relevant running gait parameters such as vertical oscillation (VO). The purpose of this study was to assess the validity of measures of VO during running gait using raw depth data, in comparison to a 3D multi-camera motion capture system. Sixteen healthy adults ran on a treadmill at a standard speed of 2.7 m/s. The VO of their running gait was simultaneously collected from raw depth data (Microsoft Kinect v2) and 3D marker data (Vicon multi-camera motion capture system). The agreement between the VO measures obtained from the two systems was assessed using a Bland-Altman plot with 95% limits of agreement (LOA), a Pearson’s correlation coefficient (r), and a Lin’s concordance correlation coefficient (rc). The depth data from the Kinect v2 demonstrated excellent results across all measures of validity (r = 0.97; rc = 0.97; 95% LOA = −8.0 mm – 8.7 mm), with an average absolute error and percent error of 3.7 (2.1) mm and 4.0 (2.0)%, respectively. The findings of this study have demonstrated the ability of a low cost depth camera and a novel tracking method to accurately measure VO in running gait.},

keywords = {biomechanics, gait analysis, virtual reality},

pubstate = {published},

tppubtype = {article}

}

@article{davison2019lifebrush,

title = {Lifebrush: painting, simulating, and visualizing dense biomolecular environments},

author = {Timothy Davison and Faramarz Samavati and Christian Jacob},

doi = {https://doi.org/10.1016/j.cag.2019.05.006},

year  = {2019},

date = {2019-01-01},

urldate = {2019-01-01},

journal = {Computers & Graphics},

volume = {82},

pages = {232--242},

publisher = {Elsevier},

abstract = {LifeBrush is a Cyberworld for painting dynamic molecular illustrations in virtual reality (VR) that then come to life as interactive simulations. We designed our system for the biological mesoscale, a spatial scale where molecules inside cells interact to form larger structures and execute the functions of cellular life. We bring our immersive illustrations to life in VR using agent-based modelling and simulation. Our sketch-based brushes use discrete element texture synthesis to generate molecular-agents along the brush path derived from examples in a palette. In this article we add a new tool to sculpt the geometry of the environment and the molecules. We also introduce a new history based visualization that enables the user to interactively explore and distil, from the busy and chaotic mesoscale environment, the interactions between molecules that drive cellular processes. We demonstrate our system with a mitochondrion example.},

keywords = {LINDSAY},

pubstate = {published},

tppubtype = {article}

}

@article{yuen2016eukaryo,

title = {Eukaryo: An AR and VR Application for Cell Biology.},

author = {Douglas Yuen and Markus Santoso and Stephen Cartwright and Christian Jacob},

doi = {10.1145/2927929.2927931},

year  = {2016},

date = {2016-01-01},

urldate = {2016-01-01},

journal = {International Journal of Virtual Reality},

volume = {16},

number = {1},

abstract = {Eukaryo is an interactive, 3-dimensional, simulated bio-molecular world that allows users to explore the complex environment within a biological cell. Eukaryo was developed using Unity, leveraging the capabilities and high performance of a commercial game engine. Through the use of MiddleVR, our tool can support a wide variety of interaction platforms including 3D virtual reality (VR) environments, such as head-mounted displays and large scale immersive visualization facilities.



Our model demonstrates key structures of a generic eukaryotic cell. Users are able to use multiple modes to explore the cell, its structural elements, its organelles, and some key metabolic processes. In contrast to textbook diagrams and even videos, Eukaryo immerses users directly in the biological environment giving a more effective demonstration of how cellular processes work, how compartmentalization affects cellular functions, and how the machineries of life operate.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{maia2016adaptive,

title = {Adaptive noise correction of dual-energy computed tomography images},

author = {Rafael Simon Maia and Christian Jacob and Amy K Hara and Alvin C Silva and William Pavlicek and Ross J Mitchell},

doi = {10.1007/s11548-015-1297-8},

year  = {2016},

date = {2016-01-01},

urldate = {2016-01-01},

journal = {International journal of computer assisted radiology and surgery},

volume = {11},

number = {4},

pages = {667--678},

publisher = {Springer},

abstract = {Purpose

Noise reduction in material density images is a necessary preprocessing step for the correct interpretation of dual-energy computed tomography (DECT) images. In this paper we describe a new method based on a local adaptive processing to reduce noise in DECT images



Methods

An adaptive neighborhood Wiener (ANW) filter was implemented and customized to use local characteristics of material density images. The ANW filter employs a three-level wavelet approach, combined with the application of an anisotropic diffusion filter. Material density images and virtual monochromatic images are noise corrected with two resulting noise maps.



Results

The algorithm was applied and quantitatively evaluated in a set of 36 images. From that set of images, three are shown here, and nine more are shown in the online supplementary material. Processed images had higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) than the raw material density images. The average improvements in SNR and CNR for the material density images were 56.5 and 54.75 %, respectively.



Conclusion

We developed a new DECT noise reduction algorithm. We demonstrate throughout a series of quantitative analyses that the algorithm improves the quality of material density images and virtual monochromatic images.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{hasan2016interactive,

title = {Interactive multilevel focus+ context visualization framework},

author = {Mahmudul Hasan and Faramarz F Samavati and Christian Jacob},

doi = {10.1007/s00371-015-1180-1},

year  = {2016},

date = {2016-01-01},

urldate = {2016-01-01},

journal = {The Visual Computer},

volume = {32},

number = {3},

pages = {323--334},

publisher = {Springer},

abstract = {In this article, we present the construction of an interactive multilevel focus+context visualization framework for the navigation and exploration of large-scale 2D and 3D images. The presented framework utilizes a balanced multiresolution technique supported by a balanced wavelet transform (BWT). It extends the mode of focus+context visualization, where spatially separate magnification of regions of interest (ROIs) is performed, as opposed to in-place magnification. Each resulting visualization scenario resembles a tree structure, where the root constitutes the main context, each non-root internal node plays the dual roles of both focus and context, and each leaf solely represents a focus. Our developed prototype supports interactive manipulation of the visualization hierarchy, such as addition and deletion of ROIs and desired changes in their resolutions at any level of the hierarchy on the fly. We describe the underlying data structure efficiently support such operations. Changes in the spatial locations of query windows defining the ROIs trigger on-demand reconstruction queries. We explain in detail how to efficiently process such reconstruction queries within the hierarchy of details (wavelet coefficients) contained in the BWT in order to ensure real-time feedback. As the BWT need only be constructed once in a preprocessing phase on the server-side and robust on-demand reconstruction queries require minimal data communication overhead, our presented framework is a suitable candidate for efficient web-based visualization of complex large-scale imagery. We also discuss the performance characteristics of our proposed framework from various aspects, such as time and space complexities and achieved frame rates.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{esmaeili2015prokaryo,

title = {PROKARYO: an illustrative and interactive computational model of the lactose operon in the bacterium Escherichia coli},

author = {Afshin Esmaeili and Timothy Davison and Andrew Wu and Joenel Alcantara and Christian Jacob},

doi = {10.1186/s12859-015-0720-z},

year  = {2015},

date = {2015-01-01},

urldate = {2015-01-01},

journal = {BMC bioinformatics},

volume = {16},

number = {1},

pages = {311},

publisher = {BioMed Central},

abstract = {Background

We are creating software for agent-based simulation and visualization of bio-molecular processes in bacterial and eukaryotic cells. As a first example, we have built a 3-dimensional, interactive computer model of an Escherichia coli bacterium and its associated biomolecular processes. Our illustrative model focuses on the gene regulatory processes that control the expression of genes involved in the lactose operon. Prokaryo, our agent-based cell simulator, incorporates cellular structures, such as plasma membranes and cytoplasm, as well as elements of the molecular machinery, including RNA polymerase, messenger RNA, lactose permease, and ribosomes.



Results

The dynamics of cellular ’agents’ are defined by their rules of interaction, implemented as finite state machines. The agents are embedded within a 3-dimensional virtual environment with simulated physical and electrochemical properties. The hybrid model is driven by a combination of (1) mathematical equations (DEQs) to capture higher-scale phenomena and (2) agent-based rules to implement localized interactions among a small number of molecular elements. Consequently, our model is able to capture phenomena across multiple spatial scales, from changing concentration gradients to one-on-one molecular interactions.



We use the classic gene regulatory mechanism of the lactose operon to demonstrate our model’s resolution, visual presentation, and real-time interactivity. Our agent-based model expands on a sophisticated mathematical E. coli metabolism model, through which we highlight our model’s scientific validity.



Conclusion

We believe that through illustration and interactive exploratory learning a model system like Prokaryo can enhance the general understanding and perception of biomolecular processes. Our agent-DEQ hybrid modeling approach can also be of value to conceptualize, illustrate, and—eventually—validate cell experiments in the wet lab.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{hoerzer2015defining,

title = {Defining functional groups based on running kinematics using Self-Organizing Maps and Support Vector Machines},

author = {Stefan Hoerzer and Vinzenz von Tscharner and Christian Jacob and Benno M Nigg},

doi = {10.1016/j.jbiomech.2015.03.017},

year  = {2015},

date = {2015-01-01},

urldate = {2015-01-01},

journal = {Journal of biomechanics},

volume = {48},

number = {10},

pages = {2072--2079},

publisher = {Elsevier},

abstract = {A functional group is a collection of individuals who react in a similar way to a specific intervention/product such as a sport shoe. Matching footwear features to a functional group can possibly enhance footwear-related comfort, improve running performance, and decrease the risk of movement-related injuries. To match footwear features to a functional group, one has to first define the different groups using their distinctive movement patterns. Therefore, the main objective of this study was to propose and apply a methodological approach to define functional groups with different movement patterns using Self-Organizing Maps and Support Vector Machines. Further study objectives were to identify differences in age, gender and footwear-related comfort preferences between the functional groups. Kinematic data and subjective comfort preferences of 88 subjects (16–76 years; 45 m/43 f) were analysed. Eight functional groups with distinctive movement patterns were defined. The findings revealed that most of the groups differed in age or gender. Certain functional groups differed in their comfort preferences and, therefore, had group-specific footwear requirements to enhance footwear-related comfort. Some of the groups, which had group-specific footwear requirements, did not show any differences in age or gender. This is important because when defining functional groups simply using common grouping criteria like age or gender, certain functional groups with group-specific movement patterns and footwear requirements might not be detected. This emphasises the power of the proposed pattern recognition approach to automatically define groups by their distinctive movement patterns in order to be able to address their group-specific product requirements.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{maia2015algorithm,

title = {An algorithm for noise correction of dual-energy computed tomography material density images},

author = {Rafael Simon Maia and Christian Jacob and Amy K Hara and Alvin C Silva and William Pavlicek and Mitchell J Ross},

doi = {10.1007/s11548-014-1006-z},

year  = {2015},

date = {2015-01-01},

urldate = {2015-01-01},

journal = {International journal of computer assisted radiology and surgery},

volume = {10},

number = {1},

pages = {87--100},

publisher = {Springer},

abstract = {Purpose

Dual-energy computed tomography (DECT) images can undergo a two-material decomposition process which results in two images containing material density information. Material density images obtained by that process result in images with increased pixel noise. Noise reduction in those images is desirable in order to improve image quality.



Methods

A noise reduction algorithm for material density images was developed and tested. A three-level wavelet approach combined with the application of an anisotropic diffusion filter was used. During each level, the resulting noise maps are further processed, until the original resolution is reached and the final noise maps obtained. Our method works in image space and, therefore, can be applied to any type of material density images obtained from any DECT vendor. A quantitative evaluation of the noise-reduced images using the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and 2D noise power spectrum was done to quantify the improvements.



Results

The noise reduction algorithm was applied to a set of images resulting in images with higher SNR and CNR than the raw density images obtained by the decomposition process. The average improvement in terms of SNR gain was about 49 % while CNR gain was about 52 %. The difference between the raw and filtered regions of interest mean values was far from reaching statistical significance (minimum  p>0.89 , average  p>0.97).



Conclusion

We have demonstrated through a series of quantitative analyses that our novel noise reduction algorithm improves the image quality of DECT material density images.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{bhalla2014staging,

title = {Staging the self-assembly process: Inspiration from biological development},

author = {Navneet Bhalla and Peter J Bentley and Peter Vize and Christian Jacob},

doi = {10.1162/artl_a_00095},

year  = {2014},

date = {2014-01-01},

urldate = {2014-01-01},

journal = {Artificial life},

volume = {20},

number = {1},

pages = {29--53},

publisher = {MIT Press},

abstract = {One of the practical challenges facing the creation of self-assembling systems is being able to exploit a limited set of fixed components and their bonding mechanisms. The method of staging divides the self-assembly process into time intervals, during which components can be added to, or removed from, an environment at each interval. Staging addresses the challenge of using components that lack plasticity by encoding the construction of a target structure in the staging algorithm itself and not exclusively in the design of the components. Previous staging strategies do not consider the interplay between component physical features (morphological information). In this work we use morphological information to stage the self-assembly process, during which components can only be added to their environment at each time interval, to demonstrate our concept. Four experiments are presented, which use heterogeneous, passive, mechanical components that are fabricated using 3D printing. Two orbital shaking environments are used to provide energy to the components and to investigate the role of morphological information with component movement in either two or three spatial dimensions. The benefit of our staging strategy is shown by reducing assembly errors and exploiting bonding mechanisms with rotational properties. As well, a doglike target structure is used to demonstrate in theory how component information used at an earlier time interval can be reused at a later time interval, inspired by the use of a body plan in biological development. We propose that a staged body plan is one method toward scaling self-assembling systems with many interacting components. The experiments and body plan example demonstrate, as proof of concept, that staging enables the self-assembly of more complex morphologies not otherwise possible.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{shirazi2014adaptive,

title = {Adaptive agent abstractions to speed up spatial agent-based simulations},

author = {Abbas Sarraf Shirazi and Timothy Davison and Sebastian von Mammen and Jörg Denzinger and Christian Jacob},

doi = {10.1016/j.simpat.2013.09.001},

year  = {2014},

date = {2014-01-01},

urldate = {2014-01-01},

journal = {Simulation Modelling Practice and Theory},

volume = {40},

pages = {144--160},

publisher = {Elsevier},

abstract = {Simulating fine-grained agent-based models requires extensive computational resources. In this article, we present an approach that reduces the number of agents by adaptively abstracting groups of spatial agents into meta-agents that subsume individual behaviours and physical forms. Particularly, groups of agents that have been clustering together for a sufficiently long period of time are detected by observer agents and then abstracted into a single meta-agent. Observers periodically test meta-agents to ensure their validity, as the dynamics of the simulation may change to a point where the individual agents do not form a cluster any more. An invalid meta-agent is removed from the simulation and subsequently, its subsumed individual agents will be put back in the simulation. The same mechanism can be applied on meta-agents thus creating adaptive abstraction hierarchies during the course of a simulation. Experimental results on the simulation of the blood coagulation process show that the proposed abstraction mechanism results in the same system behaviour while speeding up the simulation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{sarpe2013simulating,

title = {Simulating the decentralized processes of the human immune system in a virtual anatomy model},

author = {Vladimir Sarpe and Christian Jacob},

doi = {10.1186/1471-2105-14-s6-s2},

year  = {2013},

date = {2013-01-01},

urldate = {2013-01-01},

journal = {BMC bioinformatics},

volume = {14},

number = {6},

pages = {S2},

publisher = {BioMed Central},

abstract = {Background

Many physiological processes within the human body can be perceived and modeled as large systems of interacting particles or swarming agents. The complex processes of the human immune system prove to be challenging to capture and illustrate without proper reference to the spacial distribution of immune-related organs and systems. Our work focuses on physical aspects of immune system processes, which we implement through swarms of agents. This is our first prototype for integrating different immune processes into one comprehensive virtual physiology simulation.



Results

Using agent-based methodology and a 3-dimensional modeling and visualization environment (LINDSAY Composer), we present an agent-based simulation of the decentralized processes in the human immune system. The agents in our model - such as immune cells, viruses and cytokines - interact through simulated physics in two different, compartmentalized and decentralized 3-dimensional environments namely, (1) within the tissue and (2) inside a lymph node. While the two environments are separated and perform their computations asynchronously, an abstract form of communication is allowed in order to replicate the exchange, transportation and interaction of immune system agents between these sites. The distribution of simulated processes, that can communicate across multiple, local CPUs or through a network of machines, provides a starting point to build decentralized systems that replicate larger-scale processes within the human body, thus creating integrated simulations with other physiological systems, such as the circulatory, endocrine, or nervous system. Ultimately, this system integration across scales is our goal for the LINDSAY Virtual Human project.



Conclusions

Our current immune system simulations extend our previous work on agent-based simulations by introducing advanced visualizations within the context of a virtual human anatomy model. We also demonstrate how to distribute a collection of connected simulations over a network of computers. As a future endeavour, we plan to use parameter tuning techniques on our model to further enhance its biological credibility. We consider these in silico experiments and their associated modeling and optimization techniques as essential components in further enhancing our capabilities of simulating a whole-body, decentralized immune system, to be used both for medical education and research as well as for virtual studies in immunoinformatics.},

keywords = {immune system, LINDSAY},

pubstate = {published},

tppubtype = {article}

}

@article{tworek2013lindsay,

title = {The LINDSAY Virtual Human Project: An immersive approach to anatomy and physiology},

author = {Janet K Tworek and Heather Jamniczky and Christian Jacob and Benedikt Hallgrimsson and Bruce Wright},

doi = {10.1002/ase.1301},

year  = {2013},

date = {2013-01-01},

urldate = {2013-01-01},

journal = {Anatomical sciences education},

volume = {6},

number = {1},

pages = {19--28},

publisher = {Wiley Online Library},

abstract = {The increasing number of digital anatomy teaching software packages challenges anatomy educators on how to best integrate these tools for teaching and learning. Realistically, there exists a complex interplay of design, implementation, politics, and learning needs in the development and integration of software for education, each of which may be further amplified by the somewhat siloed roles of programmers, faculty, and students. LINDSAY Presenter is newly designed software that permits faculty and students to model and manipulate three-dimensional anatomy presentations and images, while including embedded quizzes, links, and text-based content. A validated tool measuring impact across pedagogy, resources, interactivity, freedom, granularity, and factors outside the immediate learning event was used in conjunction with observation, field notes, and focus groups to critically examine the impact of attitudes and perceptions of all stakeholders in the early implementation of LINDSAY Presenter before and after a three-week trial period with the software. Results demonstrate that external, personal media usage, along with students' awareness of the need to apply anatomy to clinical professional situations drove expectations of LINDSAY Presenter. A focus on the software over learning, which can be expected during initial orientation, surprisingly remained after three weeks of use. The time-intensive investment required to create learning content is a detractor from user-generated content and may reflect the consumption nature of other forms of digital learning. Early excitement over new technologies needs to be tempered with clear understanding of what learning is afforded, and how these constructively support future application and integration into professional practice.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{sarraf2013abstraction,

title = {Abstraction of agent interaction processes: Towards large-scale multi-agent models},

author = {Abbas Sarraf Shirazi and Sebastian von Mammen and Christian Jacob},

doi = {10.1177/0037549712470733},

year  = {2013},

date = {2013-01-01},

urldate = {2013-01-01},

journal = {Simulation},

volume = {89},

number = {4},

pages = {524--538},

publisher = {SAGE Publications Sage UK: London, England},

abstract = {The typically large numbers of interactions in agent-based simulations come at considerable computational costs. In this article, we present an approach to reduce the number of interactions based on behavioural patterns that recur during runtime. We employ machine learning techniques to abstract the behaviour of groups of agents to cut down computational complexity while preserving the inherent flexibility of agent-based models. The learned abstractions, which subsume the underlying model agents’ interactions, are constantly tested for their validity: after all, the dynamics of a system may change over time to such an extent that previously learned patterns would not reoccur. An invalid abstraction is, therefore, removed again from the system. The creation and removal of abstractions continues throughout the course of a simulation in order to ensure an adequate adaptation to the system dynamics. Experimental results on biological agent-based simulations show that our proposed approach can successfully reduce the computational complexity during the simulation while maintaining the freedom of arbitrary interactions},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{von2012optimization,

title = {Optimization of swarm-based simulations},

author = {Sebastian von Mammen and Abbas Sarraf Shirazi and Vladimir Sarpe and Christian Jacob},

doi = {10.5402/2012/365791},

year  = {2012},

date = {2012-01-01},

urldate = {2012-01-01},

journal = {ISRN Artificial Intelligence},

volume = {2012},

publisher = {Hindawi Publishing Corporation},

abstract = {In computational swarms, large numbers of reactive agents are simulated. The swarm individuals may coordinate their movements in a “search space” to create efficient routes, to occupy niches, or to find the highest peaks. From a more general perspective though, swarms are a means of representation and computation to bridge the gap between local, individual interactions, and global, emergent phenomena. Computational swarms bear great advantages over other numeric methods, for instance, regarding their extensibility, potential for real-time interaction, dynamic interaction topologies, close translation between natural science theory and the computational model, and the integration of multiscale and multiphysics aspects. However, the more comprehensive a swarm-based model becomes, the more demanding its configuration and the more costly its computation become. In this paper, we present an approach to effectively configure and efficiently compute swarm-based simulations by means of heuristic, population-based optimization techniques. We emphasize the commonalities of several of our recent studies that shed light on top-down model optimization and bottom-up abstraction techniques, culminating in a postulation of a general concept of self-organized optimization in swarm-based simulations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{bhalla2012programming,

title = {Programming and evolving physical self-assembling systems in three dimensions},

author = {Navneet Bhalla and Peter J Bentley and Peter D Vize and Christian Jacob},

doi = {10.1007/s11047-011-9293-6},

year  = {2012},

date = {2012-01-01},

urldate = {2012-01-01},

journal = {Natural Computing},

volume = {11},

number = {3},

pages = {475--498},

publisher = {Springer},

abstract = {Being able to engineer a set of components and their corresponding environmental conditions such that target entities emerge as the result of self-assembly remains an elusive goal. In particular, understanding how to exploit physical properties to create self-assembling systems in three dimensions (in terms of component movement) with symmetric and asymmetric features is extremely challenging. Furthermore, primarily top-down design methodologies have been used to create physical self-assembling systems. As the sophistication of these systems increases, it will be more challenging to use top-down design due to self-assembly being an algorithmically NP-complete problem. In this work, we first present a nature-inspired approach to demonstrate how physically encoded information can be used to program and direct the self-assembly process in three dimensions. Second, we extend our nature-inspired approach by incorporating evolutionary computing, to couple bottom-up construction (self-assembly) with bottom-up design (evolution). To demonstrate our design approach, we present eight proof-of-concept experiments where virtual component sets either defined (programmed) or generated (evolved) during the design process have their specifications translated and fabricated using rapid prototyping. The resulting mechanical components are placed in a jar of fluid on an orbital shaker, their environment. The energy and physical properties of the environment, along with the physical properties of the components (including complementary shapes and magnetic-bit patterns, created using permanent magnets to attract and repel components) are used to engineer the self-assembly process to create emergent target structures with three-dimensional symmetric and asymmetric features. The successful results demonstrate how physically encoded information can be used with programming and evolving physical self-assembling systems in three dimensions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{von2011artistic,

title = {Artistic exploration of the worlds of digital developmental swarms},

author = {Sebastian von Mammen and Thomas Wißmeier and Joyce Wong and Christian Jacob},

doi = {10.1162/leon_a_00087},

year  = {2011},

date = {2011-01-01},

urldate = {2011-01-01},

journal = {Leonardo},

volume = {44},

number = {1},

pages = {5--13},

publisher = {MIT Press},

abstract = {This paper presents artwork that was inspired by a computational model called Swarm Grammars. In this work, the “liveliness” of swarms is combined with the generative capabilities of more established developmental representations. Three of the authors followed their individual artistic approaches to explore the creativity and dynamics of Swarm Grammar structures. One chose to breed structures interactively to compose virtual spaces. The second explores the movement and construction dynamics of interactive swarms. The third artist translated developmental processes of Swarm Grammars into interactions of paint particles driven by friction and gravity.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}