Evaluation Of Architecture Research Articles

Validation of Somno-Art Software, a novel approach of sleep staging, compared with polysomnography in disturbed sleep profiles.

Integrated analysis of heart rate (electrocardiogram [ECG]) and body movements (actimetry) during sleep in healthy subjects have previously been shown to generate similar evaluation of sleep architecture and continuity with Somno-Art Software compared to polysomnography (PSG), the gold standard. However, the performance of this new approach of sleep staging has not yet been evaluated on patients with disturbed sleep. Sleep staging from 458 sleep recordings from multiple studies comprising healthy and patient population (obstructive sleep apnea [OSA], insomnia, major depressive disorder [MDD]) was obtained from PSG visual scoring using the American Academy of Sleep Medicine rules and from Somno-Art Software analysis on synchronized ECG and actimetry. Inter-rater reliability (IRR), evaluated with 95% absolute agreement intra-class correlation coefficient, was rated as "excellent" (ICCAAAvg95% ≥ 0.75) or "good" (ICCAAAvg95% ≥ 0.60) for all sleep parameters assessed, except non-REM (NREM) and N3 sleep in healthy participants (ICCAAAvg95% = 0.43, ICCAAAvg95% = 0.56) and N3 sleep in OSA patients (ICCAAAvg95% = 0.59) rated as "fair" IRR. Overall sensitivity, specificity, accuracy, and Cohen's kappa coefficient of agreement (κ) on the entire sample were respectively of 93.3%, 69.5%, 87.8%, and 0.65 for wake/sleep classification and accuracy and κ were of 68.5% and 0.55 for W/N1+N2/N3/rapid eye movement (REM) classification. These performances were similar in healthy and patient population. The present results suggest that Somno-Art can be a valid sleep-staging tool in both healthy subjects and patients with OSA, insomnia, or MDD. It could complement existing non-attended techniques measuring sleep-related breathing patterns or be a useful alternative to laboratory-based PSG when this latter is not available.

First break picking with deep learning – evaluation of network architectures

ABSTRACTIn recent years, various convolutional neural network architectures have been proposed for first break picking. In this paper, we compare the standard auto‐encoder and U‐net architectures as well as versions enhanced with ResNet style skip connections. The U‐net appears to have become the standard network for segmentation, judging from the number of published articles. Still, there is some variety in neural network architectural choices. In this paper, we assess the impact of neural network depth, width and input data size, as well as some small modifications for deep networks offered by the ResNet. In general, results improve as the networks get deeper, but with diminishing returns. The more complex the data, the more benefit the deeper networks bring. We use complete shot gathers, albeit rescaled for efficiency, to train the neural networks. For shot gathers with a simple piecewise linear moveout, this approach yields results with good accuracy when gathers are resampled to 128 × 128 samples. For shot gathers with more complex first break moveout, using our approach it is advised to stay close to the original dimension of each gather for best accuracy, at the expense of increased training times. A good trade‐off between network depth, image size and training times is to use a nine‐stage U‐net with 256 sample images. Despite the advantages in other applications, the basic U‐net outperforms a U‐net with ResNet features. We show that changing the input data dimensions for trained networks does not work, despite the fact the fully convolutional networks are independent of image size. The U‐net based first break picking is not sensitive to picking errors, as in many cases the neural network predictions are better than the training data where the training data have random mispicks. This suggests a practical application; namely, to train or re‐train a pre‐trained network on a single data set after conventional first break picking with the objective of improving conventionally picked first breaks.

A performance evaluation of convolutional neural network architecture for classification of rice leaf disease

<span lang="EN-US">Plant disease is a challenge in the agricultural sector, especially for rice production. Identifying diseases in rice leaves is the first step to wipe out and treat diseases to reduce crop failure. With the rapid development of the convolutional neural network (CNN), rice leaf disease can be recognized well without the help of an expert. In this research, the performance evaluation of CNN architecture will be carried out to analyze the classification of rice leaf disease images by classifying 5932 image data which are divided into 4 disease classes. The comparison of training data, validation, and testing are 60:20:20. Adam optimization with a learning rate of 0.0009 and softmax activation was used in this study. From the experimental results, the InceptionV3 and InceptionResnetV2 architectures got the best accuracy, namely 100%, ResNet50 and DenseNet201 got 99.83%, MobileNet 99.33%, and EfficientNetB3 90.14% accuracy.</span>

Towards a Method to Operationalize Modelling, Verification, and Evaluation of Architectural Solutions in the Field of Nuclear Critical Infrastructure Engineering

ABSTRACTNuclear infrastructure development projects are increasing in complexity, involving numerous and various stakeholders. Highly constrained, they are often subject to many hazards. This has an impact on the number of desired design alternatives generated throughout the facility life cycle and their evolving assessment. In order to secure the delivery of such projects, the Évaluation for Critical Infrastructures Model‐based system Engineering (EVA‐CIME) method is proposed to implement and operate the architecture evaluation at the scales both of an organization and of projects. This article presents the elements justifying the formalization of such method and the obstacles to overcome. This method must be technically and organizationally usable by the different actors of a nuclear infrastructure development project. It is composed of 5 elements: concepts; languages; operational approach; tools and repository of knowledge and expertise. The good orchestration of these different components allows to set up an environment within the organization to carry out effective architecture evaluations with the aim of helping the architects to choose between the alternatives that they will imagine from the beginning of the project.

Evaluation and Analysis of Multimedia Collaborative Building Design Relying on Particle Swarm Optimization Algorithm

This article proposes improvements to the placement, organizational structure, and adaptability of the evaluation model and proposes a comprehensive evaluation model for the multiattribute scheme of the particle swarm optimization algorithm. The structure table of the multimedia building design plan evaluation index, the plan evaluation table, and the standardized model of the plan evaluation value of the common method was proposed. It also proposes the import of “with tutor” type data of particle swarm optimization algorithm as well as the self-organizing neural network evaluation model and calculation method of “no tutor” type resource import. According to the complexity of architectural design evaluation and the nonlinear relationship between related influencing factors, we have studied the principles and methods of applying system analysis, designed comprehensive evaluation models, and comprehensively evaluated architectural design schemes.

Design and Evaluation of a Tunable PUF Architecture for FPGAs

FPGA-based Physical Unclonable Functions (PUF) have emerged as a viable alternative to permanent key storage by turning effects of inaccuracies during the manufacturing process of a chip into a unique, FPGA-intrinsic secret. However, many fixed PUF designs may suffer from unsatisfactory statistical properties in terms of uniqueness, uniformity, and robustness. Moreover, a PUF signature may alter over time due to aging or changing operating conditions, rendering a PUF insecure in the worst case. As a remedy, we propose CHOICE , a novel class of FPGA-based PUF designs with tunable uniqueness and reliability characteristics. By the use of addressable shift registers available on an FPGA, we show that a wide configuration space for adjusting a device-specific PUF response is obtained without any sacrifice of randomness. In particular, we demonstrate the concept of address-tunable propagation delays, whereby we are able to increase or decrease the probability of obtaining “ 1 ”s in the PUF response. Experimental evaluations on a group of six 28 nm Xilinx Artix-7 FPGAs show that CHOICE PUFs provide a large range of configurations to allow a fine-tuning to an average uniqueness between 49% and 51%, while simultaneously achieving bit error rates below 1.5%, thus outperforming state-of-the-art PUF designs. Moreover, with only a single FPGA slice per PUF bit, CHOICE is one of the smallest PUF designs currently available for FPGAs. It is well-known that signal propagation delays are affected by temperature, as the operating temperature impacts the internal currents of transistors that ultimately make up the circuit. We therefore comprehensively investigate how temperature variations affect the PUF response and demonstrate how the tunability of CHOICE enables us to determine configurations that show a high robustness to such variations. As a case study, we present a cryptographic key generation scheme based on CHOICE PUF responses as device-intrinsic secret and investigate the design objectives resource costs, performance, and temperature robustness to show the practicability of our approach.

Architecture and Performance Evaluation of a Novel Optical Packet Switch with Input Concentrators

In this paper, we propose a novel optical packet switch (OPS) architecture with input concentrators, which employ multi-input single-output optical buffers to aggregate all the incoming traffic into a small size switching fabric. Accordingly, the physical size, the number of the needed wavelength converters, and the economic cost of the total OPS node are decreased dramatically. However, the deployment of input concentrators introduces additional packet loss and delay, except from the contention at the switch output. A Markov model is presented to study the packet loss ratio (PLR) and average packet delay given by the input concentrators. The corresponding closed form expressions are given. The model also demonstrates that the system performance can be greatly improved by increasing the buffer size when the traffic load is not larger than 0.69315. The analytical values are compared with the simulation results. All the obtained results show that the proposed model provides satisfactory approximations under different network scenarios. Moreover, the economic cost savings of the proposed OPS node at the present time and its evolution as a function of time are also discussed in detail. The proposed architecture can also be applied in a packet enhanced optical transport network (OTN).

Understanding the Impacts of Li Stripping Overpotentials at the Counter Electrode by Three-Electrode Coin Cell Measurements.

The evaluation of new materials, interfaces, and architectures for battery applications are routinely conducted in two-electrode coin cell experiments, which although convenient, can lead to misrepresentations of the processes occurring in the cell. Few three-electrode coin cell designs have been reported, but those which have involve complex cell assembly, specialized equipment, and/or cell configurations which vary drastically from the standard coin cell environment. Herein, we present a novel, facile three-electrode coin cell design which can be easily assembled with existing coin cell parts and which accurately reproduces the environment of traditional coin cells. Using this design, we systematically investigated the inaccuracies incurred in two-electrode measurements in both symmetric/asymmetric cells and half-cell experiments by galvanostatic charge/discharge, galvanostatic intermittent titration technique (GITT), electrochemical impedance spectroscopy (EIS), and cyclic voltammetry. From our investigation, we reveal that lithium metal stripping contributes larger overpotentials than its nucleation/plating processes, a phenomenon which is often misinterpreted in two-electrode cell measurements.

Autopopulus: A Novel Framework for Autoencoder Imputation on Large Clinical Datasets.

The adoption of electronic health records (EHRs) has made patient data increasingly accessible, precipitating the development of various clinical decision support systems and data-driven models to help physicians. However, missing data are common in EHR-derived datasets, which can introduce significant uncertainty, if not invalidating the use of a predictive model. Machine learning (ML)-based imputation methods have shown promise in various domains for the task of estimating values and reducing uncertainty to the point that a predictive model can be employed. We introduce Autopopulus, a novel framework that enables the design and evaluation of various autoencoder architectures for efficient imputation on large datasets. Autopopulus implements existing autoencoder methods as well as a new technique that outputs a range of estimated values (rather than point estimates), and demonstrates a workflow that helps users make an informed decision on an appropriate imputation method. To further illustrate Autopopulus' utility, we use it to identify not only which imputation methods can most accurately impute on a large clinical dataset, but to also identify the imputation methods that enable downstream predictive models to achieve the best performance for prediction of chronic kidney disease (CKD) progression.

Identifying Drug-Resistant Tuberculosis in Chest Radiographs: Evaluation of CNN Architectures and Training Strategies.

Tuberculosis (TB) is a serious infectious disease that mainly affects the lungs. Drug resistance to the disease makes it more challenging to control. Early diagnosis of drug resistance can help with decision making resulting in appropriate and successful treatment. Chest X-rays (CXRs) have been pivotal to identifying tuberculosis and are widely available. In this work, we utilize CXRs to distinguish between drug-resistant and drug-sensitive tuberculosis. We incorporate Convolutional Neural Network (CNN) based models to discriminate the two types of TB, and employ standard and deep learning based data augmentation methods to improve the classification. Using labeled data from NIAID TB Portals and additional non-labeled sources, we were able to achieve an Area Under the ROC Curve (AUC) of up to 85% using a pretrained InceptionV3 network.

EVALUATION OF LOCAL IDENTITY IN KATAMAMA HOTEL BUILDING EXPRESSION IN SEMINYAK, BALI

Abstract- The times have created an identity crisis that has led to the fading of cultural diversity. This has caused many buildings in Indonesia today that have acted on behalf of or made the building have a local identity to reflect culture. The local identity used should not only be in the physical part of the building, but also have concepts and meanings applied. One of the local identity can be reflected through the expression of the building. A good building expression is a building that can pay attention to the local identity of the local culture in the building.
 This study aims to determine the local identity contained in the object of study, related to the expressions observed by observers. The object of study needs to be examined and studied further about the concept of Tri Angga used, and the representation of Bali that is reflected through the building, so that it can be known whether the object of study displays local Balinese identity or not. This evaluation discusses the conclusions of local identity in the case study building expressions and what should be done so that the local identity of Bali is more felt in the object of research.
 The theory used to support this research is the evaluation of architecture, local identity, architectural expression, identity and expression of Balinese architecture. The expression theory uses the Building Quality Theory by Kevin Lynch in 1960. The aspects of expression theory are chosen according to the explanations relevant to the object of study, form simplicity, visual scope, directional differentiation, and dominance. The method used in this study uses qualitative methods with descriptive, analytic, and interpretative approaches.
 The results of the study were to evaluate the local identity contained in the Katamama Hotel building expressions, which were assessed based on the theory of building quality. Local identity in the research object is in the aspect of dominance / dominance. The identity used is only found in the Bali brick material used in the scope of the building. Katamama Hotel does not use Balinese concepts, which rights are a characteristic or identity of Balinese architecture. The quality of buildings such as visual scope in the shape of the building is the main expression to be displayed. The brick material with gaps obtained from the brick structure makes a visual impression that can be felt by visitors, and is in accordance with the concept designed by the architect of the building by paying attention to lighting and shadows. While the quality of directional differentiation and form simplicity in buildings, both the shape of the building and the arrangement of the space become an aspect that is less attention to the Katamama Hotel.
 The benefit of this research is to provide an in-depth understanding of local identity and the importance of maintaining local wisdom, educating the public about the expression and its relation to local architectural identity with examples of real objects, so that physical and non-physical elements can be seen, enriching knowledge, especially culture local archipelago, as well as adding theoretical study studies on local expression and identity, as well as their relation to national identity.
 
 Key words: Evaluation, local identity, expression, Bali

Evaluation of Sleep Architecture using 24-hour Polysomnography in Patients Recovering from Critical Illness in an Intensive Care Unit and High Dependency Unit: a Longitudinal, Prospective, and Observational Study.

Background and objectiveThe sleep architecture of critically ill patients being treated in Intensive Care Units (ICU) and High Dependency Units (HDU) is frequently unsettled and inadequate both qualitatively and quantitatively. The study aimed to investigate and elucidate factors influencing sleep architecture and quality in ICU and HDU in a limited resource setting with financial constraints, lacking human resources and technology for routine monitoring of noise, light and sleep promotion strategies in ICU.MethodsThe study was longitudinal, prospective, hospital-based, analytic, and observational. Insomnia Severity Index (ISI) and the Epworth Sleepiness Scale (ESS) pre hospitalisation scores were recorded. Patients underwent 24-hour polysomnography (PSG) with the simultaneous monitoring of noise and light in their environments. Patients stabilised in ICU were transferred to HDU, where the 24-hour PSG with the simultaneous monitoring of noise and light in their environments was repeated. Following PSG, the Richards-Campbell Sleep Questionnaire (RCSQ) was employed to rate patients’ sleep in both the ICU and HDU.ResultsOf 46 screened patients, 26 patients were treated in the ICU and then transferred to the HDU. The mean (SD) of the study population’s mean (SD) age was 35.96 (11.6) years with a predominantly male population (53.2% (n=14)). The mean (SD) of the ISI and ESS scores were 6.88 (2.58) and 4.92 (1.99), respectively. The comparative analysis of PSG data recording from the ICU and HDU showed a statistically significant reduction in N1, N2 and an increase in N3 stages of sleep (p<0.05). Mean (SD) of RCSQ in the ICU and the HDU were 54.65 (7.70) and 60.19 (10.85) (p-value = 0.04) respectively. The disease severity (APACHE II) has a weak correlation with the arousal index but failed to reach statistical significance (coeff= 0.347, p= 0.083).ConclusionSleep in ICU is disturbed and persisting during the recovery period in critically ill. However, during recovery, sleep architecture shows signs of restoration.

Architecture evaluation in continuous development

ContextIn automotive, stage-gate processes have previously been the norm, with architecture created mainly during an early phase and then used to guide subsequent development phases. Current iterative and Agile development methods, where the implementation evolves continuously, changes the role of architecture. ObjectiveWe investigate how architecture evaluation can provide useful feedback during development of continuously evolving systems. MethodStarting from the Architecture Tradeoff Analysis Method (ATAM), we performed architecture evaluation, both in a national research project led by an automotive Original Equipment Manufacturer (OEM), and at the OEM, in the context of continuous development. This allows us to include the experience of several architects from different organizations over several years. Using data produced during the evaluations we perform a post-hoc analysis to derive initial findings. We then validate and refine these findings through a series of focus groups with architects and industry experts. FindingsWe propose principles of continuous evaluation and evolution of architecture, and based on these discuss a roadmap for future research. ConclusionIn iterative development settings, the needs are different from what typical architecture evaluation methods provide. Our principles show the importance of dedicated feedback-loops for continuous evolution of systems and their architecture.

Assessment of the quality of digital libraries based on the principles of information architecture. Research plan

PurposeThe purpose of this paper is to present a detailed plan of research on the information architecture of digital library websites.Design/methodology/approachThe research plan was prepared on the basis of a critical analysis of the scientific literature concerning the areas and criteria for the analysis and evaluation of the information architecture of digital resources. The evaluation criteria selected in individual areas of information architecture and the entire evaluation model were tested on the example of Europeana. The study proposes criteria for all areas of information architecture: service identity, organizational system, labeling system and navigation system.FindingsThe proposed research model containing areas and criteria for assessing usefulness from the point of view of information architecture may complement the methodology for assessing digital libraries. In a structured manner, it presents areas important for building good digital resources together with criteria for heuristic evaluation. This thesis is confirmed by a study conducted on the example of Europeana.Research limitations/implicationsFor a more precise assessment of quality, you can add to the proposed criteria related to the information architecture the criteria proposed by Nielsen or other authors. These include, e.g. help users recognize, diagnose and recover from errors, result relevance, consistency of terminology and specific action conventions and an appropriate visual presentation.Practical implicationsThe model can be used to assess the quality of websites of various digital libraries.Originality/valueThe methodology of assessing the quality of digital libraries is in the stage of formation and development. Such studies can apply evaluation criteria prepared to analyze all kinds of information systems and most of all web pages. At the beginning of the 21st century, concepts of using information architecture principles to design and evaluate digital libraries’ usability began to take shape. However, no detailed criteria for evaluating digital libraries based on the principles of information architecture have been presented.

Additive manufacturing of anti-SARS-CoV-2 Copper-Tungsten-Silver alloy

Purpose The COVID-19 pandemic emphasises the need for antiviral materials that can reduce airborne and surface-based virus transmission. This study aims to propose the use of additive manufacturing (AM) and surrogate modelling for the rapid development and deployment of novel copper-tungsten-silver (Cu-W-Ag) microporous architecture that shows strong antiviral behaviour against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Design/methodology/approach The research combines selective laser melting (SLM), in-situ alloying and surrogate modelling to conceive the antiviral Cu-W-Ag architecture. The approach is shown to be suitable for redistributed manufacturing by representing the pore morphology through a surrogate model that parametrically manipulates the SLM process parameters: hatch distance (h_d), scan speed (S_s) and laser power (L_p). The method drastically simplifies the three-dimensional (3D) printing of microporous materials by requiring only global geometrical dimensions solving current bottlenecks associated with high computed aided design data transfer required for the AM of porous materials. Findings The surrogate model developed in this study achieved an optimum parametric combination that resulted in microporous Cu-W-Ag with average pore sizes of 80 µm. Subsequent antiviral evaluation of the optimum architecture showed 100% viral inactivation within 5 h against a biosafe enveloped ribonucleic acid viral model of SARS-CoV-2. Research limitations/implications The Cu-W-Ag architecture is suitable for redistributed manufacturing and can help reduce surface contamination of SARS-CoV-2. Nevertheless, further optimisation may improve the virus inactivation time. Practical implications The study was extended to demonstrate an open-source 3D printed Cu-W-Ag antiviral mask filter prototype. Social implications The evolving nature of the COVID-19 pandemic brings new and unpredictable challenges where redistributed manufacturing of 3D printed antiviral materials can achieve rapid solutions. Originality/value The papers present for the first time a methodology to digitally conceive and print-on-demand a novel Cu-W-Ag alloy that shows high antiviral behaviour against SARS-CoV-2.

The genetic architecture of Plakophilin 2 cardiomyopathy

PurposeThe genetic architecture of Plakophilin 2 (PKP2) cardiomyopathy can inform our understanding of its variant pathogenicity and protein function. MethodsWe assess the gene-wide and regional association of truncating and missense variants in PKP2 with arrhythmogenic cardiomyopathy (ACM), and arrhythmogenic right ventricular cardiomyopathy (ARVC) specifically. A discovery data set compares genetic testing requisitions to gnomAD. Validation is performed in a rigorously phenotyped definite ARVC cohort and non-ACM individuals in the Geisinger MyCode cohort. ResultsThe etiologic fraction (EF) of ACM-related diagnoses from truncating variants in PKP2 is significant (0.85 [0.80,0.88], p < 2 × 10−16), increases for ARVC specifically (EF = 0.96 [0.94,0.97], p < 2 × 10−16), and is highest in definite ARVC versus non-ACM individuals (EF = 1.00 [1.00,1.00], p < 2 × 10−16). Regions of missense variation enriched for ACM probands include known functional domains and the C-terminus, which was not previously known to contain a functional domain. No regional enrichment was identified for truncating variants. ConclusionThis multicohort evaluation of the genetic architecture of PKP2 demonstrates the specificity of PKP2 truncating variants for ARVC within the ACM disease spectrum. We identify the PKP2 C-terminus as a potential functional domain and find that truncating variants likely cause disease irrespective of transcript position.

Evaluation of Convolutional Neural Network Architecture for Feasibility Analysis on Fetal Abdomen and Brain Images

This research aims to evaluate the possibilities of fetus ultrasound image classification using machine learning algorithms as normal or abnormal. Most of the earlier research works have produced a high percentage of false-negative classification results—recent research work aimed to reduce the rate of false-negative diagnoses. Also, the number of sonologists for analyzing prenatal ultrasound worldwide is very less and solved by developing an efficient algorithm, which reduces the percentage of false negatives in the diagnosis output. Several earlier research works focused on analyzing fetal abdominal image or fetal head images, making the medical industry use two different diagnostic modules separately. This work aims to design and implement a convolution frame-work named as two Convolution Neural Network (tCNN) model for diagnosing any fetal images. The proposed tCNN model diagnoses the fetal abdominal and fetal brain images and classify them as normal or abnormal. CNN1of tCNN performs segmentation and classification based on the acceptance of abdomen circumference and stomach bubble, umbilical vein, and amniotic fluid measurements. CNN2shows based on head circumference and head and abdominal circumference, femur, crown-rump, and humerus lengths measured.With clinical validation, an extensive experiment carried out and the results compared with the experts in terms of segmentation accuracy and the obstetric measurements. This paper provides a foundation for future multi-classification research works on diagnosing fetal intracranial abnormalities and differential diagnosis using machine learning algorithms.

Cystosonographic and Cystographic Evaluations of Urinary Bladder Defects Managed with Composite Colo-Peritoneal Grafts in Dogs

Radiographic and ultrasonographic evaluations of the urinary bladder architecture following autologous composite colo-peritoneal pedicle graft, as alternative tissue for urinary bladder reconstruction, in the surgical repair of experimental urinary bladder defects were carried out in two dogs. Predetermined 2 ´ 4 cm dimension of urinary bladder defect was created on the dorsum of the urinary bladder, and was patched with harvested 3 ´ 5 cm composite colo-peritoneal pedicle flap. All operations were aseptically and humanely conducted. The gross anatomical evaluation of the urinary bladder architecture was performed by ultrasonography and contrast radiography of the repaired urinary bladder. Post-surgical cystosonographic assessments on day 8 showed thickened urinary bladder wall at the point of the graft, which decreased markedly on day 21. Cystographic evaluation revealed gradual transition of the urinary bladder architecture at the point of graft with clear delineation and minimal blurring at week 2 post-operation, which gradually disappeared at weeks 10 and 14. The cystosonographic and cystographic evaluations demonstrated evidence of advanced healing and well-preserved urinary bladder architecture with no evidence of leaks. The imaging modalities are adequately diagnostic to assess urinary bladder repairs following its management with composite colo-peritoneal graft in dogs.

A Study on Newly Founded Nation Gardens in Turkey: A Landscape Architecture Evaluation of Design Principles

The construction of the newly designed large size garden projects, has become important topic, calling ‘Nation Garden’ in Turkey. As a part of the ‘Green City Visions’, Turkish Ministry of Environment and Urbanization has emerged in 81 provinces with a total size of 81 million m² Nation Gardens projected with various aims, sizes and designs principles. However, 61 of these projects have already been completed, and some of still under construction, at present time. Some opened and serviced Nation Gardens, which are located in provinces of Bursa, Istanbul, Konya, Mersin, Samsun, Sivas and Trabzon, were examined in terms of concept of Nation Garden. It has realized that Some Nation Gardens dominantly planted with lawn (Bursa and Baruthane-Istanbul), while some have combination with trees and shrubs (Samsun and Halkali-Istanbul). When surface coverings considered, the concrete hard and lawn soft properties are balance in most of these gardens. However, these Nation Gardens are planned as attraction centers that reflect the identity of the cities. Therefore, they have built with different social dynamics, demand on different green space setups with different qualities and identities. It has been understood that majority of Nation Gardens have been built on close to shores, forests and lakes, or previously existing areas that have relaunched with minor adjustments.

Safe Haven—Bath House and Library by the Burmese Border

This study gives an overview of contemporary vernacular tendencies in Thai architecture. The research includes ecological, economical, ergonomic and cultural aspects, and the aim is to find a possible future direction for architectural design that is able to incorporate local features and follow traditions yet apply them in a contemporary way. As an example, a case study was carried out about a project realized in Safe Haven Orphanage in Thailand. It consists of two small-scale buildings designed and constructed by TYIN Tegnestue Architects, Sami Rintala and Hans Skotte, together with volunteers and the local community, and they are great examples of a community building “healing architecture”. Due to their aesthetics, their ecological and sustainable approach and their structures, they can provide cultural continuity, which is key for the organic evaluation of regional architecture.