Low-Cost Electronics for Online I-V Tracing at Photovoltaic Module Level: Development of Two Strategies and Comparison between Them

The measurement of current–voltage (I-V) curves of single photovoltaic (PV) modules is at this moment the most powerful technique regarding the monitoring and diagnostics of PV plants, providing accurate information about the possible failures or degradation at the module level. Automating these measurements and allowing them to be made online is strongly desirable in order to conceive a systematic tracking of plant health. Currently, I-V tracers present some drawbacks, such as being only for the string level, working offline, or being expensive. Facing this situation, the authors have developed two different low-cost online I-V tracers at the individual module level, which could allow for a cost-affordable future development of a fully automated environment for the tracking of the plant status. The first system proposed implements a completely distributed strategy, since all the electronics required for the I-V measurement are located within each of the modules and can be executed without a power line interruption. The second one uses a mixed strategy, where some common electronics are moved from PV modules to the inverter or combiner box and need an automated very short disconnection of the modules string under measurement. Experiments show that both strategies allow the tracing of individual panel I-V curves and sending of the data afterwards in numerical form to a central host with a minimum influence on the power production and with a low-cost design due to the simplicity of the electronics. A comparison between both strategies is exposed, and their costs are compared with the previous systems proposed in the literature, obtaining cost reductions of over 80–90% compared with actual commercial traces.

Performance Evaluation of Hybrid Air Purification System with Vegetation Soil and Electrostatic Precipitator Filters

This paper describes designing, manufacturing, and evaluating an eco-friendly modular-type air purification system to enhance the removal efficiency of fine particulate matter (PM) in urban public spaces, especially in hotspots. This system consists of artificial soil based-vegetation and electrostatic precipitator (ESP) filters. Unlike the so-called passive removal method, which adsorbs fine PM only by the leaves of plants, the vegetation soil filter based on multi-layered different artificial soils adopts an active removal method in which air purification is performed in the soil itself, bypassing external air by using the air circulation fan in the soil. The ESP filter is designed and evaluated to have a high fine PM removal efficiency, even at high suction velocity, to remove large amounts of outdoor fine PM. Throughout the experimental measurements on the hybrid air purification system with vegetation soil and ESP filters, it is observed that the vegetation soil filter has a 78.5% reduction efficiency for PM2.5 and a 47% for PM10 at the inlet air velocity of 0.15 m/s. The ESP filter also has a 73.1% reduction efficiency for PM2.5 and 87.3% for PM10 at an inlet air velocity of 3 m/s. Based on the performance evaluations of the vegetation soil filter and the ESP filter, it is noted that each individual module will be applied to an air purification tower with vertical expansion and installed in a high concentration area of fine PM in a downtown area to contribute to the fine PM reduction in the community.

TECHNOLOGICAL AND DESIGN FEATURES OF DESIGNING A MODULAR REINFORCED CONCRETE FOUNDATION FOR A HIGH-RISE BUILDING OF VARIOUS TYPES

The paper proposes a new type of modular collapsible reinforced concrete foundation for steel support for various types of structures: power lines, wind power plants, billboards, traffic lights, etc.The foundation has the shape of a cross-hammer in the plan and consists of separate modules manufactured at the factory and connected to each other by concrete dowels and tie bolts on the construction site. At the same time, this technological approach makes it possible to obtain more stable (uniform) strength and deformation properties of both the individual module and the assembled foundation as a whole. Reducing the material consumption is achieved by creating a cavity in each typical module and filling it with local inert material (soil). The central module has an anchor device for joining with the support according to the type of flange connection. This device, along with the use of conventional anchor bolts, involves filling the central module with non-shrinkable fast-hardening steel-fiber concrete. Thus, the positive result of the proposed solution is to increase the bearing capacity of the foundation as a whole, increase the strength and stiffness of its main joints, and simplify installation in comparison with traditional approaches to construction. A comparative calculation of the foundations of the proposed and standard known solutions showed the effectiveness of the first one by at least 17.2%.

Technological and construction features of modular reinforced concrete foundation designing for various high-rise structures

The paper proposes a new type of modular collapsible reinforced concrete foundation for steel support of various types of structures: power lines, wind power plants, billboards, traffic lights, etc. The foundation has the shape of a cross-hammer in the plan and consists of separate modules manufactured at the factory and connected to each other by concrete dowels and tie bolts on the construction site. At the same time, this technological approach makes it possible to obtain more stable (uniform) strength and deformation properties of both the individual module and the assembled foundation as a whole. Reducing the material consumption is achieved by creating a cavity in each typical module and filling it with local inert material (soil). The Central module has an anchor device for joining with the support according to the type of flange connection. This device, along with the use of conventional anchor bolts, involves filling the Central module with non-shrinkable fast-hardening steel-fiber concrete. Thus, the positive result of the proposed solution is to increase the bearing capacity of the Foundation as a whole, increase the strength and stiffness of its main joints, and simplify installation in comparison with traditional approaches to construction. A comparative calculation of the foundations of the proposed and standard known solutions showed the effectiveness of the first one by at least 17.2%.

Integrated Mobile and web-based Application for Enhancing delivery of HIV/AIDS Healthcare Information in Tanzania

This study aims to develop an integrated e-health platform for enhancing delivery of HIV/AIDS healthcare information in Tanzania, which consists of a mobile application and a web-based system. The study is based on the system's functional and non-functional requirements for an e-health system for delivery of HIV/AIDS healthcare information. The Rapid Application Development (RAD) model was adopted during the system development. The system requirements were modelled into Data Flow Diagram (DFD) in order to obtain the clear flow of the HIV/AIDS healthcare information between the clients and HIV/AIDS healthcare practitioners. With the use of different software development tools and environment such as Android studio and Symfony framework; both android application and web-based system were developed. Finally, the developed system was tested for individual module functioning as well as the functioning of the fully integrated system. The user acceptance survey gave the mean score of above 4 on the scale of 5 for each tested aspect of the system. These scores show that the developed system was positively accepted by the users and commended the Ministry of Health and to deploy the system for enhanced delivery of HIV/AIDS healthcare information.

Network Monitoring on Cloud Environment using SDN

Network Monitoring is going to be play a vital role in today’s software defined networking as the completed network/topology information is now available at a centralized controller which is having the complete picture about the underlying network with respect to the connectivity, fault management, a centralized configuration and performance along with enhanced security. Network Monitoring System (NMS) Application which has been developed as part of this project is a north bound application sitting on top of SDN (ODL) controller and sending periodic requested in the form of http request. This application will send various unique requests towards the ODL using different Rest URL and processed the response for each request which will be in the form of JSON format. Each response will then be fed to individual module and the data will be extracted, processed and will be updated accordingly in individual display pages meant for specific purpose.

Modular network for high-rate quantum conferencing

One of the main open problems in quantum communication is the design of efficient quantum-secured networks. This is a challenging goal, because it requires protocols that guarantee both unconditional security and high communication rates, while increasing the number of users. In this scenario, continuous-variable systems provide an ideal platform where high rates can be achieved by using off-the-shelf optical components. At the same time, the measurement-device independent architecture is also appealing for its feature of removing a substantial portion of practical weaknesses. Driven by these ideas, here we introduce a modular design of continuous-variable network where each individual module is a measurement-device-independent star network. In each module, the users send modulated coherent states to an untrusted relay, creating multipartite secret correlations via a generalized Bell detection. Using one-time pad between different modules, the network users may share a quantum-secure conference key over arbitrary distances at constant rate.

Towards Visible and Thermal Drone Monitoring with Convolutional Neural Networks

This paper reports a visible and thermal drone monitoring system that integrates deep-learning-based detection and tracking modules. The biggest challenge in adopting deep learning methods for drone detection is the paucity of training drone images especially thermal drone images. To address this issue, we develop two data augmentation techniques. One is a model-based drone augmentation technique that automatically generates visible drone images with a bounding box label on the drone's location. The other is exploiting an adversarial data augmentation methodology to create thermal drone images. To track a small flying drone, we utilize the residual information between consecutive image frames. Finally, we present an integrated detection and tracking system that outperforms the performance of each individual module containing detection or tracking only. The experiments show that, even being trained on synthetic data, the proposed system performs well on real-world drone images with complex background. The USC drone detection and tracking dataset with user labeled bounding boxes is available to the public.

The Unified Protocol for Anxiety Disorders

Of any cluster of illnesses outlined in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), none is more prevalent, likely to serve as a comorbid diagnosis, or costly in the United States than anxiety disorders. This chapter outlines the applications of the Unified Protocol for Transdiagnostic Treatment of Emotional Disorders (UP) for the treatment of such disorders. First, we briefly review the background research that provides context for the use of transdiagnostic treatment for anxiety disorders. The UP, with its intent to target comorbidity, is an approach that can be especially helpful for therapists who want to use an evidence-based treatment, prefer the structure of a manualized protocol, and value the benefits that a workbook can bring to patients. We then present two clinical case studies to demonstrate how each individual module of the UP maps onto typical cases of principal and comorbid anxiety. Recommendations for specific methods of protocol implementation are also described.

How much cryosphere model complexity is just right? Exploration using the conceptual cryosphere hydrology framework

Making meaningful projections of the impacts that possible future climates would have on water resources in mountain regions requires understanding how cryosphere hydrology model performance changes under altered climate conditions and when the model is applied to ungaged catchments. Further, if we are to develop better models, we must understand which specific process representations limit model performance. This article presents a modeling tool, named the Conceptual Cryosphere Hydrology Framework (CCHF), that enables implementing and evaluating a wide range of cryosphere modeling hypotheses. The CCHF represents cryosphere hydrology systems using a set of coupled process modules that allows easily interchanging individual module representations and includes analysis tools to evaluate model outputs. CCHF version 1 (Mosier, 2016) implements model formulations that require only precipitation and temperature as climate inputs – for example variations on simple degree-index (SDI) or enhanced temperature index (ETI) formulations – because these model structures are often applied in data-sparse mountain regions, and perform relatively well over short periods, but their calibration is known to change based on climate and geography. Using CCHF, we implement seven existing and novel models, including one existing SDI model, two existing ETI models, and four novel models that utilize a combination of existing and novel module representations. The novel module representations include a heat transfer formulation with net longwave radiation and a snowpack internal energy formulation that uses an approximation of the cold content. We assess the models for the Gulkana and Wolverine glaciated watersheds in Alaska, which have markedly different climates and contain long-term US Geological Survey benchmark glaciers. Overall we find that the best performing models are those that are more physically consistent and representative, but no single model performs best for all of our model evaluation criteria.