Using simulations and artificial life algorithms to grow elements of construction

'In nature, shape is cheaper than material', that is a common truth for most of the plants and other living organisms, even though they may not recognize that. In all living forms, shape is more or less directly linked to the influence of force, that was acting upon the organism during its growth. Trees and bones concentrate their material where thy need strength and stiffness, locating the tissue in desired places through the process of self-organization. We can study nature to find solutions to design problems. That’s where inspiration comes from, so we pick a solution already spotted somewhere in the organic world, that closely resembles our design problem, and use it in constructive way. First, examining it, disassembling, sorting out conclusions and ideas discovered, then performing an act of 'reverse engineering' and putting it all together again, in a way that suits our design needs. Very simple ideas copied from nature, produce complexity and exhibit self-organization capabilities, when applied in bigger scale and number. Computer algorithms of simulated artificial life help us to capture them, understand well and use where needed. This investigation is going to follow the question : How can we use methods seen in nature to simulate growth of construction elements? Different ways of extracting ideas from world of biology will be presented, then several techniques of simulated emergence will be demonstrated. Specific focus will be put on topics of computational modelling of natural phenomena, and differences in developmental and non-developmental techniques. Resulting 3D models will be shown and explained

Microscopic Mechanism of the Thermal Amorphization of ZIF-4 and Melting of ZIF-zni Revealed via Molecular Dynamics and Machine Learning Techniques

We investigate the microscopic mechanism of the thermally induced ambient pressure ordered-disordered phase transitions of two zeolitic imidazolate frameworks of formula Zn(C$_3$H$_3$N$_2$)$_2$: a porous (ZIF-4) and a dense, non-porous (ZIF-zni) polymorph via a combination of data science and computer simulation approaches. Molecular dynamics simulations are carried out at the atomistic level through the nb-ZIF-FF force field that incorporates ligand-metal reactivity and relies on dummy atoms to reproduce the correct tetrahedral topology around Zn$^{2+}$ centres. The force field is capable of reproducing the structure of ZIF-4, ZIF-zni and the amorphous (ZIF$\_$a) and liquid (ZIF$\_$liq) phases that respectively result when these crystalline materials are heated. Symmetry functions computed over a database of structures of the four phases, are used as inputs to train a neural network that predicts the probabilities of belonging to each of the four phases at the local Zn$^{2+}$ level with 90$\%$ accuracy. We apply this methodology to follow the time-evolution of the amorphization of ZIF-4 and the melting of ZIF-zni along a series of molecular dynamics trajectories. We first computed the transition temperature and determined associated thermodynamic state functions. Subsequently, we studied the mechanisms. Both processes consist of two steps: (i) for ZIF-4, a low-density amorphous phase is first formed, followed by the final ZIF$\_$a phase while (ii) for ZIF-zni, a ZIF$\_$a-like phase precedes the formation of the liquid phase. These processes involve connectivity changes in the first neighbour ligands around the central Zn$^{2+}$ cations. We find that the amorphization of ZIF-4 is a non-isotropic processes and we trace back the origins of this anisotropic behaviour to density and lability of coordination bonds.Comment: 27 pages, 7 figures, 3 table

Past, state-of-the-art and future of intralogistics in relation to megatrends

Nakon kratkog pregleda istorije intralogistike, ovaj rad izučava pogled na navedene tehnologije. One su u vezi sa t.z.v. 'megatrendovima' kao što su globalizacija, urbanizacija, demografske i klimatske promene, za koje se očekuje da donesu globalne promene u nekoliko sledećih decenija i koje će najverovatnije odrediti buduću ulogu intralogistike i fokus istraživanja u ovoj oblasti.After briefly reviewing the history of intralogistics, this paper examines the outlook for the technologies concerned. This is related to the so-called 'megatrends', such as globalisation, urbanisation, demographic shifts and climate change, which are expected to bring about major global transformations over the next few decades, and which are also likely to determine the future functions of intralogistics and the focus of research in the field

Past, state-of-the-art and future of intralogistics in relation to megatrends

Nakon kratkog pregleda istorije intralogistike, ovaj rad izučava pogled na navedene tehnologije. One su u vezi sa t.z.v. 'megatrendovima' kao što su globalizacija, urbanizacija, demografske i klimatske promene, za koje se očekuje da donesu globalne promene u nekoliko sledećih decenija i koje će najverovatnije odrediti buduću ulogu intralogistike i fokus istraživanja u ovoj oblasti.After briefly reviewing the history of intralogistics, this paper examines the outlook for the technologies concerned. This is related to the so-called 'megatrends', such as globalisation, urbanisation, demographic shifts and climate change, which are expected to bring about major global transformations over the next few decades, and which are also likely to determine the future functions of intralogistics and the focus of research in the field

The doctoral research abstracts. Vol:7 2015 / Institute of Graduate Studies, UiTM

Foreword: The Seventh Issue of The Doctoral Research Abstracts captures the novelty of 65 doctorates receiving their scrolls in UiTM’s 82nd Convocation in the field of Science and Technology, Business and Administration, and Social Science and Humanities. To the recipients I would like to say that you have most certainly done UiTM proud by journeying through the scholastic path with its endless challenges and impediments, and persevering right till the very end. This convocation should not be regarded as the end of your highest scholarly achievement and contribution to the body of knowledge but rather as the beginning of embarking into high impact innovative research for the community and country from knowledge gained during this academic journey. As alumni of UiTM, we will always hold you dear to our hearts. A new ‘handshake’ is about to take place between you and UiTM as joint collaborators in future research undertakings. I envisioned a strong research pact between you as our alumni and UiTM in breaking the frontier of knowledge through research. I wish you all the best in your endeavour and may I offer my congratulations to all the graduands. ‘UiTM sentiasa dihati ku’ / Tan Sri Dato’ Sri Prof Ir Dr Sahol Hamid Abu Bakar , FASc, PEng Vice Chancellor Universiti Teknologi MAR

Social Insect-Inspired Adaptive Hardware

Modern VLSI transistor densities allow large systems to be implemented within a single chip. As technologies get smaller, fundamental limits of silicon devices are reached resulting in lower design yields and post-deployment failures. Many-core systems provide a platform for leveraging the computing resource on offer by deep sub-micron technologies and also offer high-level capabilities for mitigating the issues with small feature sizes. However, designing for many-core systems that can adapt to in-field failures and operation variability requires an extremely large multi-objective optimisation space. When a many-core reaches the size supported by the densities of modern technologies (thousands of processing cores), finding design solutions in this problem space becomes extremely difficult. Many biological systems show properties that are adaptive and scalable. This thesis proposes a self-optimising and adaptive, yet scalable, design approach for many-core based on the emergent behaviours of social-insect colonies. In these colonies there are many thousands of individuals with low intelligence who contribute, without any centralised control, to complete a wide range of tasks to build and maintain the colony. The experiments presented translate biological models of social-insect intelligence into simple embedded intelligence circuits. These circuits sense low-level system events and use this manage the parameters of the many-core's Network-on-Chip (NoC) during runtime. Centurion, a 128-node many-core, was created to investigate these models at large scale in hardware. The results show that, by monitoring a small number of signals within each NoC router, task allocation emerges from the social-insect intelligence models that can self-configure to support representative applications. It is demonstrated that emergent task allocation supports fault tolerance with no extra hardware overhead. The response-threshold decision making circuitry uses a negligible amount of hardware resources relative to the size of the many-core and is an ideal technology for implementing embedded intelligence for system runtime management of large-complexity single-chip systems

Simulating social relations in multi-agent systems

Open distributed systems are comprised of a large number of heterogeneous nodes with disparate requirements and objectives, a number of which may not conform to the system specification. This thesis argues that activity in such systems can be regulated by using distributed mechanisms inspired by social science theories regarding similarity /kinship, trust, reputation, recommendation and economics. This makes it possible to create scalable and robust agent societies which can adapt to overcome structural impediments and provide inherent defence against malicious and incompetent action, without detriment to system functionality and performance. In particular this thesis describes: • an agent based simulation and animation platform (PreSage), which offers the agent developer and society designer a suite of powerful tools for creating, simulating and visualising agent societies from both a local and global perspective. • a social information dissemination system (SID) based on principles of self organisation which personalises recommendation and directs information dissemination. • a computational socio-cognitive and economic framework (CScEF) which integrates and extends socio-cognitive theories of trust, reputation and recommendation with basic economic theory. • results from two simulation studies investigating the performance of SID and the CScEF. The results show the production of a generic, reusable and scalable platform for developing and animating agent societies, and its contribution to the community as an open source tool. Secondly specific results, regarding the application of SID and CScEF, show that revealing outcomes of using socio-technical mechanisms to condition agent interactions can be demonstrated and identified by using Presage.Open Acces

Modelling continuous sequential behaviour to enhance training and generalization in neural networks

This thesis is a conceptual and empirical approach to embody modelling of continuous sequential behaviour in neural learning. The aim is to enhance the feasibility of training and capacity for generalisation. By examining the sequential aspects of the passing of time in a neural network, it is suggested that an alteration to the usual goal weight condition may be made to model these aspects. The notion of a goal weight path is introduced, with a path-based backpropagation (PBP) framework being proposed. Two models using PBP have been investigated in the thesis. One is called Feedforward Continuous BackPropagation (FCBP) which is a generalization of conventional BackPropagation; the other is called Recurrent Continuous BackPropagation (RCBP) which provides a neural dynamic system for I/O associations. Both models make use of the continuity underlying analogue-binary associations and analogue-analogue associations within a fixed neural network topology. A graphical simulator cbptool for Sun workstations has been designed and implemented for supporting the research. The capabilities of FCBP and RCBP have been explored through experiments. The results for FCBP and RCBP confirm the modelling theory. The fundamental alteration made on conventional backpropagation brings substantial improvement in training and generalization to enhance the power of backpropagation

Performance improvement for mobile ad hoc cognitive packets network

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonIn this thesis, focusing on the quality of service (QoS) improvement using per-packet power control algorithm in Ad Hoc Cognitive Packet Networks (AHCPN). A power control mechanism creates as a network-assisted function of ad hoc cognitive packet-based routing and aims at reducing both energy consumption in nodes and QoS requirements. The suggested models facilitate transmission power adjustments while also taking into account the effects on network performance. The thesis concentrate on three main contributions. Firstly, a power control algorithm, namely the adaptive Distributed Power management algorithm (DISPOW) was adopted. Performance of DISPOW was compared to existing mechanisms and the results showed 27, 13, 9, and 40 percent improvements in terms of Delay, Throughput, Packet Loss, and Energy Consumption respectively. Secondly, the DISPOW algorithm was enhanced, namely a Link Expiration Time Aware Distributed Power management algorithm (LETPOW). This approach periodically checks connectivity, transmission power, interference level, routing overhead and Node Mobility in AHCPN. The results show that LETPOW algorithm improves the performance of system. Results show further improvement from DISPOW by 30,25,30,42 percent in terms of delay, packet loss ratio , path lengths and energy consumption respectively. Finally,Hybrid Power Control Algorithm (HLPCA) has presented is a combination of Link Expiration Time Aware Distributed Power management algorithm (LETPOW) and Load Power Control Algorithm (LOADPOW); deal with cross-layer power control applied for transmitting information across the various intermediate layers. LOADPOW emphasis on the concept of transmission Power, Received Signal Strength Indication (RSSI), and the suitable distance between the receiver and the sender. The proposed algorithm outperforms DISPOW and LETPOW by 31,15,35,34,44 percent in terms of Delay, Throughput, Packet Loss,path length and Energy Consumption respectively. From this work, it can be concluded that optimized power control algorithm applied to Ad-hoc cognitive packet network results in significant improvement in terms of energy consumption and QoS

Development of efficient data management and analytics tools for Intelligent sanitation network design.

Williams, Leon - Associate SupervisorAccording to the World Health Organisation, billions of people lack access to basic sanitation facilities and services, resulting in estimated 2.9 million cases of diseases and 95,000 deaths each year. This is because poor planning, design, maintenance, and access in traditional sanitation networks. Nowadays, intelligent sanitation systems leveraging the Internet of Things (IoT) technology can provide efficient and sustainable services, incorporating sensors, hardware, software, and wireless communication. Furthermore, advanced data analytics tools combined with the intelligent sanitation systems can provide a deeper insight into operations, make informed decisions, and enhance user experience, thereby improving sanitation services. The thesis provides a comprehensive review of literature on intelligent sanitation systems from both academic and industrial perspectives, with the objective of identifying recent advances, research gaps, opportunities, and challenges. Existing solutions for intelligent sanitation are fragmented and immature due to a lack of a unified framework and tool. To address these issues, the thesis introduces a generalised Sanitation-IoT (San-IoT) framework to manage sanitation facilities and a standardised Sanitation-IoT-Data Analytics (San-IoT-DA) tool to analyse sanitation data. The framework and tool can serve as a foundation for future research and development in intelligent sanitation systems. The San-IoT framework can enhance the connectivity, operability, and management of IoT-based sanitation networks. The San-IoT-DA tool is designed to standardise the collection, analysis, and management of sanitation data for providing efficient data processing and improving decision making. The feasibility of the proposed framework and tool was evaluated on a case study of the Cranfield intelligent toilet. The San-IoT framework has the potential to enable system monitoring and control, user health monitoring, user behaviour analysis, improve water usage efficiency, reduce energy consumption, and facilitate decision-making among global stakeholders. The San-IoT-DA tool can detect patterns, identify trends, predict outcomes, and detect anomalies. The thesis offers valuable insights to practitioners, academics, engineers, policymakers, and other stakeholders on leveraging IoT and data analytics to improve the efficiency, accessibility, and sustainability of the sanitation industry.PhD in Desig