Automatic synthesis of analog layout : a survey

A review of recent research in the automatic synthesis of physical geometry for analog integrated circuits is presented. On introduction, an explanation of the difficulties involved in analog layout as opposed to digital layout is covered. Review of the literature then follows. Emphasis is placed on the exposition of general methods for addressing problems specific to analog layout, with the details of specific systems only being given when they surve to illustrate these methods well. The conclusion discusses problems remaining and offers a prediction as to how technology will evolve to solve them. It is argued that although progress has been and will continue to be made in the automation of analog IC layout, due to fundamental differences in the nature of analog IC design as opposed to digital design, it should not be expected that the level of automation of the former will reach that of the latter any time soon

Fireground location understanding by semantic linking of visual objects and building information models

This paper presents an outline for improved localization and situational awareness in fire emergency situations based on semantic technology and computer vision techniques. The novelty of our methodology lies in the semantic linking of video object recognition results from visual and thermal cameras with Building Information Models (BIM). The current limitations and possibilities of certain building information streams in the context of fire safety or fire incident management are addressed in this paper. Furthermore, our data management tools match higher-level semantic metadata descriptors of BIM and deep-learning based visual object recognition and classification networks. Based on these matches, estimations can be generated of camera, objects and event positions in the BIM model, transforming it from a static source of information into a rich, dynamic data provider. Previous work has already investigated the possibilities to link BIM and low-cost point sensors for fireground understanding, but these approaches did not take into account the benefits of video analysis and recent developments in semantics and feature learning research. Finally, the strengths of the proposed approach compared to the state-of-the-art is its (semi -)automatic workflow, generic and modular setup and multi-modal strategy, which allows to automatically create situational awareness, to improve localization and to facilitate the overall fire understanding

Co-designing smart home technology with people with dementia or Parkinson's disease

Involving users is crucial to designing technology successfully, especially for vulnerable users in health and social care, yet detailed descriptions and critical reflections on the co-design process, techniques and methods are rare. This paper introduces the PERCEPT (PERrsona-CEntred Participatory Technology) approach for the co-design process and we analyse and discuss the lessons learned for each step in this process. We applied PERCEPT in a project to develop a smart home toolset that will allow a person living with early stage dementia or Parkinson's to plan, monitor and self-manage his or her life and well-being more effectively. We present a set of personas which were co-created with people and applied throughout the project in the co-design process. The approach presented in this paper will enable researchers and designers to better engage with target user groups in co-design and point to considerations to be made at each step for vulnerable users

USING MACHINE LEARNING TO OPTIMIZE PREDICTIVE MODELS USED FOR BIG DATA ANALYTICS IN VARIOUS SPORTS EVENTS

In today’s world, data is growing in huge volume and type day by day. Historical data can hence be leveraged to predict the likelihood of the events which are to occur in the future. This process of using statistical or any other form of data to predict future outcomes is commonly termed as predictive modelling. Predictive modelling is becoming more and more important and is trending because of several reasons. But mainly, it enables businesses or individual users to gain accurate insights and allows to decide suitable actions for a profitable outcome. Machine learning techniques are generally used in order to build these predictive models. Examples of machine learning models ranges from time-series-based regression models which can be used for predicting volume of airline related traffic and linear regression-based models which can be used for predicting fuel efficiency. There are many domains which can gain competitive advantage by using predictive modelling with machine learning. Few of these domains include, but are not limited to, banking and financial services, retail, insurance, fraud detection, stock market analysis, sentimental analysis etc. In this research project, predictive analysis is used for the sports domain. It’s an upcoming domain where machine learning can help make better predictions. There are numerous sports events happening around the globe every day and the data gathered from these events can very well be used for predicting as well as improving the future events. In this project, machine learning with statistics would be used to perform quantitative and predictive analysis of dataset related to soccer. Comparisons of these models to see how effectively the models are is also presented. Also, few big data tools and techniques are used in order to optimize these predictive models and increase their accuracy to over 90%

Data-informed Building Procurement: A contractor exploration on embodied-carbon targets through Buildability and AI

The construction industry has been object of criticism due to poor productivity rates, lethargic development, and irresponsible use of natural resources. It has been pointed out that segment peculiarities, such as fragmentated, project-based, and one-of-a-kind, stand as barriers for change, compromising the urgent agenda for sustainable development. Regardless of that, recent climate agreements have input unprecedent pressure on the industry with challenging decarbonization goals. Motivated by that, this thesis explores a Swedish contractor perspective on how embodied carbon targets can be addressed in the building sector through better-informed tender briefings and buildability. For that, the study follows an abductive reasoning and exploratory mixed method approach, where a broad qualitative study informs a quantitative survey.Findings reveal a clear need for better-informed decisions on tender briefings. It exposes that data in early stages is reduced and inaccurate due to undefinitions and undeveloped assessments methods that tackles limited criteria. Additionally, it is argued that information flows are difficulted by outdated practices and the fragmented reality of conventional buildings product development, in which several stakeholders co-create, negotiate, and transfer asset ownership along the way. These actors, as investigations support, usually hold opposing interests driven by short-term economic gains. Consequently, neither environmental nor societal criteria appear to be effectively informed and spoken for during early stages of decision-making, regardless the considerably high share of emissions and relevant social issues that the sector comprise. Further, it is exposed that decarbonization roadmaps proposing investments in greener materials solutions, although longed-for, might escalate building costs considerably, possibly leading to economic and social issues linked to housing prices. Therefore, it is argued the plan may turn unfeasible, especially in face of the broad implementation which is vital to attend set targets.Accordingly, seeking to compensate such economic impacts, the thesis explores opportunities to reduce waste through the promotion of Buildability principles in the earliest stages of concept design, when it can still be addressed. As such, obstacles and inflexibilities created via client requirements and tender procedures are analyzed to propose changes.However, findings show the public procurement act challenges contractors ability to influence on more buildable solutions in public tenders. And Partnering strategies, which are often seen as a remedy for that, has been reducing due to public clients fear of volatile budgets - a viewpoint which contractors oppose since Partnering is a mean for many ends. Consequently, the thesis concludes that contractors are dependent on client’s leading role and can hardly count with better informed briefings and easier to build requirements.Nonetheless, it is suggested that contractors could develop a strategy based on data-informed ‘side-offers’, as a way around the limitations framed by the public procurement dynamics. Accordingly, a roadmap for AI-applications is advocated for contractors to reduce lead-time and resources spent for the elaboration of these side-offers. For that, it recommends the use of cutting-edge technologies to process an integrated multi-criteria design, that is informed by data collected both from the product and the market (client). Ultimately, the thesis supports that through automation, contractors can gain access to the right information at the right time, and thus promote a more valuable and sustainable alternative for public clients to procure

VRBridge: a Constructivist Approach to Supporting Interaction Design and End-User Authoring in Virtual Reality

For any technology to become widely-used and accepted, it must support end-user authoring and customisation. This means making the technology accessible by enabling understanding of its design issues and reducing its technical barriers. Our interest is in enabling end-users to author dynamic virtual environments (VEs), specifically their interactions: player interactions with objects and the environment; and object interactions with each other and the environment. This thesis describes a method to create tools and design aids which enable end-users to design and implement interactions in a VE and assist them in building the requisite domain knowledge, while reducing the costs of learning a new set of skills. Our design method is based in constructivism, which is a theory that examines the acquisition and use of knowledge. It provides principles for managing complexity in knowledge acquisition: multiplicity of representations and perspectives; simplicity of basic components; encouragement of exploration; support for deep reflection; and providing users with control of their process as much as possible. We derived two main design aids from these principles: multiple, interactive and synchronised domain-specific representations of the design; and multiple forms of non-invasive and user-adaptable scaffolding. The method began with extensive research into representations and scaffolding, followed by investigation of the design strategies of experts, the needs of novices and how best to support them with software, and the requirements of the VR domain. We also conducted a classroom observation of the practices of non-programmers in VR design, to discover their specific problems with effectively conceptualising and communicating interactions in VR. Based on our findings in this research and our constructivist guidelines, we developed VRBridge, an interaction authoring tool. This contained a simple event-action interface for creating interactions using trigger-condition-action triads or Triggersets. We conducted two experimental evaluations during the design of VRBridge, to test the effectiveness of our design aids and the basic tool. The first tested the effectiveness of the Triggersets and additional representations: a Floorplan, a Sequence Diagram and Timelines. We used observation, interviews and task success to evaluate how effectively end-users could analyse and debug interactions created with VRBridge. We found that the Triggersets were effective and usable by novices to analyse an interaction design, and that the representations significantly improved end-user work and experience. The second experiment was large-scale (124 participants) and conducted over two weeks. Participants worked on authoring tasks which embodied typical interactions and complexities in the domain. We used a task exploration metric, questionnaires and computer logging to evaluate aspects of task performance: how effectively end-users could create interactions with VRBridge; how effectively they worked in the domain of VR authoring; how much enjoyment or satisfaction they experienced during the process; and how well they learned over time. This experiment tested the entire system and the effects of the scaffolding and representations. We found that all users were able to complete authoring tasks using VRBridge after very little experience with the system and domain; all users improved and felt more satisfaction over time; users with representations or scaffolding as a design aid completed the task more expertly, explored more effectively, felt more satisfaction and learned better than those without design aids; users with representations explored more effectively and felt more satisfaction than those with scaffolding; and users with both design aids learned better but did not improve in any other way over users with a single design aid. We also gained evidence about how the scaffolding, representations and basic tool were used during the evaluation. The contributions of this thesis are: an effective and efficient theory-based design method; a case study in the use of constructivism to structure a design process and deliver effective tools; a proof-of-concept prototype with which novices can create interactions in VR without traditional programming; evidence about the problems that novices face when designing interactions and dealing with unfamiliar programming concepts; empirical evidence about the relative effectiveness of additional representations and scaffolding as support for designing interactions; guidelines for supporting end-user authoring in general; and guidelines for the design of effective interaction authoring systems in general

Algorithmic techniques for physical design : macro placement and under-the-cell routing

With the increase of chip component density and new manufacturability constraints imposed by modern technology nodes, the role of algorithms for electronic design automation is key to the successful implementation of integrated circuits. Two of the critical steps in the physical design flows are macro placement and ensuring all design rules are honored after timing closure. This thesis proposes contributions to help in these stages, easing time-consuming manual steps and helping physical design engineers to obtain better layouts in reduced turnaround time. The first contribution is under-the-cell routing, a proposal to systematically connect standard cell components via lateral pins in the lower metal layers. The aim is to reduce congestion in the upper metal layers caused by extra metal and vias, decreasing the number of design rule violations. To allow cells to connect by abutment, a standard cell library is enriched with instances containing lateral pins in a pre-selected sharing track. Algorithms are proposed to maximize the numbers of connections via lateral connection by mapping placed cell instances to layouts with lateral pins, and proposing local placement modifications to increase the opportunities for such connections. Experimental results show a significant decrease in the number of pins, vias, and in number of design rule violations, with negligible impact on wirelength and timing. The second contribution, done in collaboration with eSilicon (a leading ASIC design company), is the creation of HiDaP, a macro placement tool for modern industrial designs. The proposed approach follows a multilevel scheme to floorplan hierarchical blocks, composed of macros and standard cells. By exploiting RTL information available in the netlist, the dataflow affinity between these blocks is modeled and minimized to find a macro placement with good wirelength and timing properties. The approach is further extended to allow additional engineer input, such as preferred macro locations, and also spectral and force methods to guide the floorplanning search. Experimental results show that the layouts generated by HiDaP outperforms those obtained by a state-of-the-art EDA physical design software, with similar wirelength and better timing when compared to manually designed tape-out ready macro placements. Layouts obtained by HiDaP have successfully been brought to near timing closure with one to two rounds of small modifications by physical design engineers. HiDaP has been fully integrated in the design flows of the company and its development remains an ongoing effort.A causa de l'increment de la densitat de components en els xip i les noves restriccions de disseny imposades pels últims nodes de fabricació, el rol de l'algorísmia en l'automatització del disseny electrònic ha esdevingut clau per poder implementar circuits integrats. Dos dels passos crucials en el procés de disseny físic és el placement de macros i assegurar la correcció de les regles de disseny un cop les restriccions de timing del circuit són satisfetes. Aquesta tesi proposa contribucions per ajudar en aquests dos reptes, facilitant laboriosos passos manuals en el procés i ajudant als enginyers de disseny físic a obtenir millors resultats en menys temps. La primera contribució és el routing "under-the-cell", una proposta per connectar cel·les estàndard usant pins laterals en les capes de metall inferior de manera sistemàtica. L'objectiu és reduir la congestió en les capes de metall superior causades per l'ús de metall i vies, i així disminuir el nombre de violacions de regles de disseny. Per permetre la connexió lateral de cel·les, estenem una llibreria de cel·les estàndard amb dissenys que incorporen connexions laterals. També proposem modificacions locals al placement per permetre explotar aquest tipus de connexions més sovint. Els resultats experimentals mostren una reducció significativa en el nombre de pins, vies i nombre de violacions de regles de disseny, amb un impacte negligible en wirelength i timing. La segona contribució, desenvolupada en col·laboració amb eSilicon (una empresa capdavantera en disseny ASIC), és el desenvolupament de HiDaP, una eina de macro placement per a dissenys industrials actuals. La proposta segueix un procés multinivell per fer el floorplan de blocks jeràrquics, formats per macros i cel·les estàndard. Mitjançant la informació RTL disponible en la netlist, l'afinitat de dataflow entre els mòduls es modela i minimitza per trobar macro placements amb bones propietats de wirelength i timing. La proposta també incorpora la possibilitat de rebre input addicional de l'enginyer, com ara suggeriments de les posicions de les macros. Finalment, també usa mètodes espectrals i de forçes per guiar la cerca de floorplans. Els resultats experimentals mostren que els dissenys generats amb HiDaP són millors que els obtinguts per eines comercials capdavanteres de EDA. Els resultats també mostren que els dissenys presentats poden obtenir un wirelength similar i millor timing que macro placements obtinguts manualment, usats per fabricació. Alguns dissenys obtinguts per HiDaP s'han dut fins a timing-closure en una o dues rondes de modificacions incrementals per part d'enginyers de disseny físic. L'eina s'ha integrat en el procés de disseny de eSilicon i el seu desenvolupament continua més enllà de les aportacions a aquesta tesi