Window System Research Articles

Experimental mechanical analysis of traditional in-service glass windows subjected to dynamic tests and hard body impact

The large use of glass in buildings, and especially the presence of fenestrations and facade systems, represents a potential critical issue for people safety. The brittle nature of glass (with limited elastic deformation and resistance) is often enforced by its use in combination of several secondary components, whose reciprocal interaction and potential damage should be properly assessed. In the case of windows, accordingly, a special care should be spent for glass members but also for the framing system and possible adhesive or mechanical connections. This study aims at exploring the dynamic response and damage sensitivity of traditional glass window systems, based on the experimental derivation of few key material properties and mechanical parameters. To this aim the attention is focused on traditional, in-service windows that belongs to existing residential buildings and are typically sustained by timber frames, through a linear flexible connection. In doing so, major advantage is taken from experimental analysis, both in the static and dynamic field, for whole window assemblies of single components. For comparative purposes, selected window specimens including plastic (PVC) frame members and Insulated Glass Units (IGUs) are also taken into account in the paper. The static characteristics of the windows components are first preliminary derived. The dynamic performance of such a kind of systems is then experimentally explored with the support of modal analysis techniques and hard body impact procedures, including the experimental derivation of stiffness parameters for the frame members and the glass panels. Further assessment of experimental outcomes is finally achieved with the support of Finite Element numerical analyses.

APLIKASI MENDETEKSI JENIS HARGA ASSESORIESHANDPHONE MENGGUNAKAN AUGMENTED REALITY

Augmented reality (AR) is a technology that can display information that is virtual but presented in a real world view (2010). With this technology in the business world, adequate presentation of information can be done appropriately and accurately. The purpose of this study is to create an application that can display information on the price of goods using the camera on an Android smartphone. The method to achieve the purpose of this paper is the experimental method utilizing the Vuforia database as a place to store data on the price of goods and collect samples of existing objects as targets to be recognized by the camera to display information on the price of goods. The language used in this application is the C # programming language with a 64-bit Windows system. The results of this study are displaying information on cellphone prices by taking data from Vuforia which will be automatically displayed by the application using the camera on a smartphone.

Monte-Carlo optical model coupled with Inverse Adding-Doubling for Building Integrated Photovoltaic smart window design and characterisation

Building Integrated Photovoltaic (BIPV) glazings are promising technologies with the benefits of electricity generation, solar shading and building energy savings. A new approach is to integrate BIPV windows with thermotropic materials such as Hydroxypropyl Cellulose (HPC) hydrogel, which offers adaptive advantages for the systems to respond to time-varying weather conditions but also enhances the PV electricity generation. To design such systems, knowledge of the temperature-dependent scattering properties of the selected thermotropic materials is of significance. In this study, a Building Integrated Photovoltaic (BIPV) smart window system consisting of a thermotropic membrane synthesised using HPC and gellan gum gelling agent for electricity generation and also solar control has been designed and investigated. An advanced optical model, which combines a Monte-Carlo ray-tracing technique with an Inverse Adding-Doubling (IAD) method, has been developed for characterising the thermotropic membrane in terms of angular scattering distribution under various membrane temperatures and HPC concentrations. Then the developed optical model has been validated by comparison with experimental measurements. Subsequently, the validated optical model has been used to design and optimise the proposed BIPV smart window. The effects of HPC concentration, geometric concentration ratio, thermotropic membrane thickness and glass refractive index on PV power outputs have been evaluated. Finally, a prototype of the BIPV smart window with a 6 wt% HPC membrane has been manufactured and tested under indoor conditions. From the experimental tests, it was found that the total transmittance of the double-pane glass sample with a 6 wt% HPC membrane layer decreases from approximately 90%to 14%, when the membrane temperature increases from 27 °C to 56 °C. The measured short-circuit current for the prototype BIPV smart window is up to 1.15 times higher than that of its counterpart system with a similar PV area but no membrane.

Decentralized Multisite VBM Analysis During Adolescence Shows Structural Changes Linked to Age, Body Mass Index, and Smoking: a COINSTAC Analysis.

There has been an upward trend in developing frameworks that enable neuroimaging researchers to address challenging questions by leveraging data across multiple sites all over the world. One such open-source framework is the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation (COINSTAC) that works on Windows, macOS, and Linux operating systems and leverages containerized analysis pipelines to analyze neuroimaging data stored locally across multiple physical locations without the need for pooling the data at any point during the analysis. In this paper, the COINSTAC team partnered with a data collection consortium to implement the first-ever decentralized voxelwise analysis of brain imaging data performed outside the COINSTAC development group. Decentralized voxel-based morphometry analysis of over 2000 structural magnetic resonance imaging data sets collected at 14 different sites across two cohorts and co-located in different countries was performed to study the structural changes in brain gray matter which linked to age, body mass index (BMI), and smoking. Results produced by the decentralized analysis were consistent with and extended previous findings in the literature. In particular, a widespread cortical gray matter reduction (resembling a 'default mode network' pattern) and hippocampal increase with age, bilateral increases in the hypothalamus and basal ganglia with BMI, and cingulate and thalamic decreases with smoking. This work provides a critical real-world test of the COINSTAC framework in a "Large-N" study. It showcases the potential benefits of performing multivoxel and multivariate analyses of large-scale neuroimaging data located at multiple sites.

Machine-OlF-Action: a unified framework for developing and interpreting machine-learning models for chemosensory research.

Machine Learning-based techniques are emerging as state-of-the-art methods in chemoinformatics to selectively, effectively and speedily identify biologically relevant molecules from large databases. So far, a multitude of such techniques have been proposed, but unfortunately due to their sparse availability, and the dependency on high-end computational literacy, their wider adaptation faces challenges, at least in the context of G-Protein Coupled Receptors (GPCRs)-associated chemosensory research. Here, we report Machine-OlF-Action (MOA), a user-friendly, open-source computational framework, that utilizes user-supplied SMILES (simplified molecular input line entry system) of the chemicals, along with their activation status, to synthesize classification models. MOA integrates a number of popular chemical databases collectively harboring approximately 103 million chemical moieties. MOA also facilitates customized screening of user-supplied chemical datasets. A key feature of MOA is its ability to embed molecules based on the similarity of their local neighborhood, by utilizing a state-of-the-art model interpretability framework LIME. We demonstrate the utility of MOA in identifying previously unreported agonists for human and mouse olfactory receptors OR1A1 and MOR174-9 by leveraging the chemical features of their known agonists and non-agonists. In summary, here we develop an ML-powered software playground for performing supervisory learning tasks involving chemical compounds. MOA is available for Windows, Mac and Linux operating systems. It's accessible at (https://ahuja-lab.in/). Source code, user manual, step-by-step guide and support is available at GitHub (https://github.com/the-ahuja-lab/Machine-Olf-Action). For results, reproducibility and hyperparameters, refer to Supplementary Notes. Supplementary data are available at Bioinformatics online.

Reliability analysis and optimization of multi-state sliding window system with sequential demands and time constraints

This paper proposes a new model that generalizes the multi-state sliding window system to the case involving sequential demands and time constraints. In this model, the system (named MSWS-SD&TC) contains n linearly or circularly arranged multi-state elements (MEs), and its function depends on the ability that each r-consecutive-ME group can meet the demands of sequential tasks subject to time constraints. The reliability model of the system is built with consideration of the optimal performance assignment scheme in each group of MEs. In order to effectively determine the optimal performance assignment scheme with minimum completion time in each r-consecutive-ME group, we develop a dynamic programming algorithm in this paper. We use a technique of universal generating function to represent the system states and evaluate the system reliability. Since the order of MEs has strong impact on the system reliability, we also investigate the optimal sequencing problem for the MEs in the system, and solve the problem with a genetic algorithm. Examples of evaluating system reliability and element sequencing optimization are presented for illustration.

Mineralized supramolecular hydrogel as thermo-responsive smart window

Everlasting pursuit of the high energy efficiency as well as meeting fluctuant temperature causes various lighting requirements over the day, which is driving the demand for creating a multifunctional smart window (SW) system. Here, an upper critical solution temperature (UCST)- and/or lower critical solution temperature (LCST)-type SW system (denoted as SWU, SWL and SWU+L, respectively) was fabricated through a simple bio-inspired physical cross-link process between amorphous CaCO3 (ACC) and poly(acrylic acid) (PAA). Series of mineralized hydrogel-based chromic layers were first in situ formed by sealing the composite of ACC in PAA matrix into polyethylene terephthalate (PET) “sandwich structure” to fabricate the SW system. As expected, the SWU system exhibited a typical UCST transition process, bringing about a luminous transmittance (Tlum) of 40.70% at 25 °C and a Tlum of 74.76% at 45 °C. The high scattering of the initial state as well as large optical contrast (ΔTlum $$=$$ 34.06%) of the SWU system guarantees residential privacy and energy savings. Also, a thermochromic SWL system with a relatively high luminous transmittance (Tlum) of 47.81% at 25 °C and an acceptable solar modulation property (ΔTlum $$=$$ 16.06%) was constructed. A conceptual SWU+L system was fabricated, that is, a sharp UCST transition followed by a LCST process. This reversible two-stage optical switch process subsequently occurs by continuously increasing temperature, endowing this SW system highly suitable for SW or logic gate. The SW system with multi-thermo-responsiveness brings more flexibility in building facade design.

Window System using Dynamic Insulation Applied to A Detached House in Warm Region

Window System using Dynamic Insulation Applied to A Detached House in Warm Region

A Decision Support Model Proposal for the Detection and Evaluation of Deterioration in Window Systems

A Decision Support Model Proposal for the Detection and Evaluation of Deterioration in Window Systems

Overview of dynamic test methods for examining the glass window resistance

In recent years, glass, and glass facades are increasingly used as part of building structures. Due to its functions, glass is used in commercial, residential, or strategic buildings, such as airports, stations, or offices. However, window system is subject to several forms of the load. This can be an extreme load in the form of an explosion, an earthquake, or other types of loads, such as their wind load, or dynamic impact. In the article, we focused on an overview of several norms, standards, and research that address the issue of resilience of window systems. The aim of the article was to identify the parameters that are examined in various tests in the standards. The investigated parameters of windows in a manual attempt at burglary, impact test, and explosion were discussed in the article.

Condensation Effects on Energy Performance of Building Window Systems

Condensation Effects on Energy Performance of Building Window Systems

Assessment of Fenestration Security as Part of Railway Infrastructure

The safety of train stations can be affected by many internal and external threats. Train stations or stations in generally can be classified as soft targets. It can be assumed a potential target for many, especially terrorist attacks. In elevated number of railways stations, large glass surface as facades and stained-glass windows are presented. They present vulnerable part of construction, affected by various type of accidental loads (as blast and impact) in case of terrorist attacks. In this terrorist attack, the biggest cause of injuries and deaths are caused by debris from glass parts of structure. The paper is focused on the glass used in modern construction of train stations. Based on this, several methods of loading condition are described and the resistance of fenestration on such loads is assessed. The practical part of the paper is focused on two types of window systems and the resistance to dynamic loads was evaluated. The experimental testing was performed using a pendulum test. The results showed the resistance of selected types of windows without, as well as, with the use of security protective film. The paper also interprets possible glass failure under dynamic loading.

Statistical comparison of typical Hungarian administrative public service processes using key performance indicators

This study aims to comparatively analyse the front office operations of two Hungarian gov-ernment windows, one located in a capital city district and the other in a county district centre, to examine the difference in the perceived service levels. First, through an international literature review, the study describes the background of the government window system and the importance of key performance indicators (KPIs). In addition, it demonstrates how KPIs can be measured in a public service context, regardless of the type and complexity of a given service. Second, the study provides a detailed statistical analysis and a comparison of the typical administrative public services related to waiting times, processing times, and lead times. Moreover, it offers an analogy of industrial service process management by presenting how the selected meth-ods and measures can be used to review processes related to an industrial, a manufacturing, or a public service, following a holistic management approach. The study contributes to the literature by using KPIs of the private sector and industry in public service processes and shows how these common KPIs can be measured in the public service context to provide valuable insights into service processes. Finally, it demonstrates the differences between the KPIs of the government windows to help legislators to increase the efficiency and effectiveness of services.

Mobile lung cancer early warning based on Windows Azure cloud computing

In view of the repeated investment in the current medical lung cancer early warning system, 'information island' and the low rate of lung cancer early warning, this paper proposes a mobile lung cancer early warning system based on Windows Azure cloud computing with the application requirements of medical information system. The system is applied to the smart phones of Windows system, and the Windows Azure Microsoft cloud platform is accessed through wireless network, using SQL Azure to store medical data (such as lung CT image, ECG curve and high-resolution colour ultrasound image), embed the medical lung cancer early warning model based on deep learning in the cloud computing platform to process and analyse the patient's medical data, and realise the real-time synchronous update of doctors, patients and cloud platform data. The accuracy of lung cancer early-warning system on LIDC-IDRI is high, and the detection results are uploaded to doctors and patients' smart phones in real time. The results show that the mobile lung cancer early warning system based on Windows Azure cloud computing not only effectively integrates medical resources, but also provides patients with medical services and consultation at home, which integrates the advantages of all aspects and adapts to the development of the times.

Mobile lung cancer early warning based on Windows Azure cloud computing

In view of the repeated investment in the current medical lung cancer early warning system, 'information island' and the low rate of lung cancer early warning, this paper proposes a mobile lung cancer early warning system based on Windows Azure cloud computing with the application requirements of medical information system. The system is applied to the smart phones of Windows system, and the Windows Azure Microsoft cloud platform is accessed through wireless network, using SQL Azure to store medical data (such as lung CT image, ECG curve and high-resolution colour ultrasound image), embed the medical lung cancer early warning model based on deep learning in the cloud computing platform to process and analyse the patient's medical data, and realise the real-time synchronous update of doctors, patients and cloud platform data. The accuracy of lung cancer early-warning system on LIDC-IDRI is high, and the detection results are uploaded to doctors and patients' smart phones in real time. The results show that the mobile lung cancer early warning system based on Windows Azure cloud computing not only effectively integrates medical resources, but also provides patients with medical services and consultation at home, which integrates the advantages of all aspects and adapts to the development of the times.

Condensation risk of exhaust air heat recovery window system: Assessment, key parameters, and prevention measure

The exhaust air window (EAW) can be regarded as a combination of exhaust air heat recovery unit and window system. The window can locally and directly utilize the exhaust air from each air-conditioned room to reduce the heat loss/gain through window. However, condensation may occur at the internal glazing surface of EAW in winter. To avoid the condensation risk of EAW, some prevention measures were proposed and estimated. In this study, a two-dimensional zonal model of EAW was established to calculate its temperature distribution, and to further identify whether condensation will occur under different boundary conditions. The calculated results were compared with the measured data for verifying the accuracy and reliability of model. A sensitivity analysis was conducted to identify the effects of indoor air temperature and relative humidity, exhaust airflow velocity, and adding a low-e coating on prevention of condensation in winter. The results indicated that adding a low-e coating or decreasing the indoor relative humidity can effectively reduce the critical outdoor temperature of condensation and prevent the occurrence of condensation within the EAW. It was estimated that even under the outdoor air temperature of −20 °C, condensation risk can be avoided by employing a low-e glazing.

Estimation of Cooling Load of a Residential House using TRNSYS

Development of a country will lead to increased utilization and demand for energy. In this research study, transient simulation technique is implemented and eventually, the cooling load of the house is determined. The study focused to provide cooling load characteristics for a residential house. The factors namely: size and shape, thermophysical properties, window systems, orientation, internal gains, ventilation and infiltration aspects that influence the cooling load are considered in the study. A dynamic simulation software-TRNSYS (Transient Systems Simulation Program) is used for the modelling and simulation of the energy flows of the house to determine the cooling thermal load. The study is useful in providing a better solution for a sustainable future by simulating with different design modifications of the house. This study may be extended to focus on the choice of constructional materials, so that good temperature and lower cooling load are attained. A case study of a residential building is situated in the coastal district of Andhra Pradesh, India and located at Latitude (17.68o N) and longitude (83.21oE) is considered to find cooling load through TRNSYS 16. Keywords: Cooling load, Tropical region, Simulation, ventilation

Estimation of Cooling Load of a Residential House using TRNSYS

Development of a country will lead to increased utilization and demand for energy. In this research study, transient simulation technique is implemented and eventually, the cooling load of the house is determined. The study focused to provide cooling load characteristics for a residential house. The factors namely: size and shape, thermophysical properties, window systems, orientation, internal gains, ventilation and infiltration aspects that influence the cooling load are considered in the study. A dynamic simulation software-TRNSYS (Transient Systems Simulation Program) is used for the modelling and simulation of the energy flows of the house to determine the cooling thermal load. The study is useful in providing a better solution for a sustainable future by simulating with different design modifications of the house. This study may be extended to focus on the choice of constructional materials, so that good temperature and lower cooling load are attained. A case study of a residential building is situated in the coastal district of Andhra Pradesh, India and located at Latitude (17.68o N) and longitude (83.21oE) is considered to find cooling load through TRNSYS 16. Keywords: Cooling load, Tropical region, Simulation, ventilation

Traffic characterization in a communications channel for monitoring and control in real-time systems

The response time for remote monitoring and control in real-time systems is a sensitive issue in device interconnection elements. Therefore, it is necessary to analyze the traffic of the communication system in pre-established time windows. In this paper, a methodology based on computational intelligence is proposed for identifying the availability of a data channel and the variables or characteristics that affect the performance and data transfer, which is made up of four stages: a) integration of a communication system with an acquisition module and a final control structure; b) communication channel characterization by means of traffic variables; and c) relevance analysis from the characterization space using SFFS (sequential forward oating selection); d) Channel congestion classification as Low or High using a classifier based on Naive Bayes algorithm. The experimental setup emulates a real process using an on/off remote control of a DC motor on an Ethernet network. The communication time between the client and server was integrated with the operation and control times, to study the whole response time. This proposed approach allows support decisions about channel availability, to establish predictions about the length of the time window when the availability conditions are unknown.

BCL::Conf: Improved Open-Source Knowledge-Based Conformation Sampling Using the Crystallography Open Database.

We previously described BCL::Conf, a knowledge-based conformation sampling algorithm utilizing a small molecule fragment rotamer library derived from the Cambridge Structural Database (CSD, license required), as a component of the BioChemical Library (BCL) cheminformatics toolkit. This paper describes substantial improvements made to the BCL::Conf algorithm and a transition to a rotamer library derived from molecules in the Crystallography Open Database (COD, no license required). We demonstrate the performance of the new BCL::Conf on native conformer recovery in the Platinum dataset of high-quality protein-ligand complexes. This set of 2859 structures has previously been used to assess the performance of over a dozen conformer generation algorithms, including the Conformator, Balloon, RDKit DG, ETKDG, Confab, Frog2, MultiConf-DOCK, CSD conformer generator, ConfGenX-OPSL3 force field, Omega, excalc, iCon, and MOE. These benchmarks suggest that the CSD conformer generator is at the state of the art of reported conformer generators. Our results indicate that the improved BCL::Conf significantly outperforms the CSD conformer generation algorithm at binding conformer recovery across a range of ensemble sizes and with similarly fast rates of conformer generation. BCL::Conf is now distributed with the COD-derived rotamer library and is free for academic use. The BCL can be downloaded at http://meilerlab.org/bclcommons for Windows, Linux, or Apple operating systems. BCL::Conf can now also be accessed via webserver at http://meilerlab.org/bclconf.