Liver microcirculation analysis by red blood cell motion modeling in intravital microscopy images

Intravital microscopy has been used to visualize the microcirculation by imaging fluorescent labeled red blood cells (RBCs). Traditionally, microcirculation has been modeled by computing the mean velocity of a few, randomly selected, manually tracked RBCs. However, this protocol is tedious, time consuming, and subjective with technician related bias. We present a new method for analyzing the microcirculation by modeling the RBC motion through automatic tracking. The tracking of RBCs is challenging as in each image, as many as 200 cells move through a complex network of vessels at a wide range of speeds while deforming in shape. To reliably detect RBCs traveling at a wide range of speeds, a window of temporal template matching is applied. Then, cells appearing in successive frames are corresponded based on the motion behavior constraints in terms of the direction, magnitude, and path. The performance evaluation against a ground truth indicates the detection accuracy up to 84% TP at 6% FP and a correspondence accuracy of 89%. We include an in-depth discussion on comparison of the microcirculation based on motion modeling from the proposed automated method against a mean velocity from manual analysis protocol in terms of precision, objectivity, and sensitivity.     

Bias voltage effect on the dielectric properties of organic–inorganic blend SiNWs elaborated via metal assisted chemical etching

The electrical proprieties of poly (3-hexylthiophene): Silicon nanowires (P3HT: SiNWs) nanocomposite was investigated by impedance spectroscopy technique. The effect of bias voltage under and without illumination was discussed. Indeed, the imaginary part of the impedance shows a high relaxation frequency related to Maxwell–Wagner–Sillars (MWS) polarization. The relaxation time was found in the range of ms and it was shifted towards high frequency with increasing the bias voltage especially at 0.6 V At bias voltage equal to V_th and under illumination, the conductivity increases because the trapped charges acquire the necessary energy to escape from the interface and the hopping time found was reduced. This indicates a change of the conduction mechanism. The Cole–Cole diagram was excellently fitted through an equivalent circuit including a chemical capacitance Cµ, a contact electrical resistance Rs and recombination resistance Rp.     

Two‐sided matching framework for optimal user association in 5G multi‐RAT UDNs

Recently, academic and industrial research communities are paying more explicit attention to the 5G multiple radio access technology ultra‐dense networks (5G multi‐RAT UDNs) for boosting network capacity, especially in UD urban zones. To this aim, in this paper, we intend to tackle the user association problem in 5G multi‐RAT UDNs. By considering the decoupled uplink/downlink access (DUDA), we divide our user association problem into two distinct subproblems representing, respectively, the uplink and the downlink channels. Next, we formulated each one as a nonlinear optimization problem with binary variables. Then, to solve them, we were restricted by the hard complexity, as well as the hard feasibility of centralized user association schemes. Thus, to resolve our user association problem in a reasonable time and distributed manner, we formulated each subproblem as a many‐to‐one matching game based on matching theory. Next, we provide two fully distributed association algorithms to compute the uplink and downlink stable matching among user equipments (UEs) and base stations (BSs). Simulation results corroborate our theoretical model and show the effectiveness and improvement of our achieved results in terms of the overall network performance, quality of service (QoS), and energy efficiency (EE) of UEs.     

Enhanced fair earliest due date first scheduling strategy for multimedia applications in LTE downlink framework

Guaranteeing a certain delay threshold for delay‐sensitive applications in long term evolution (LTE) cellular communication system is a very challenging mission. By implementing an optimal scheduling strategy, this mission will be achieved. In this article, a novel scheduler is introduced in order to meet a predefined level of service quality by guaranteeing a specific delay threshold for delay‐sensitive applications in LTE cellular systems. The proposed scheduler assigns the available resource blocks (RBs) to active user equipments (UEs) tacking into consideration several attributes. The expiration date of each packet, the channel quality, the average data rate previously achieved by each UE, and the number of dropped packets for each UE compared with the average number of packets totally dropped are all considered in the proposed scheduler working mechanism. Consequently, the proposed scheduling strategy reduces the number of packets dropped for multimedia applications, and at the same time maximizes the overall throughput of the network. Simulation results are provided to study and evaluate the performance of the proposed scheduling strategy. A comparative study is presented between the proposed strategy and the most recent scheduling techniques. The obtained results prove that the proposed scheduling strategy has considerably acceptable and appreciated results compared with the results of the state‐of‐the‐art scheduling techniques.     

Automatic PV Grid Fault Detection System with IoT and LabVIEW as Data Logger

Fault detection of the photovoltaic (PV) grid is necessary to detect serious output power reduction to avoid PV modules’ damage. To identify the fault of the PV arrays, there is a necessity to implement an automatic system. In this IoT and LabVIEW-based automatic fault detection of 3 × 3 solar array, a PV system is proposed to control and monitor Internet connectivity remotely. Hardware component to automatically reconfigure the solar PV array from the series-parallel (SP) to the complete cross-linked array underneath partial shading conditions (PSC) is centered on the Atmega328 system to achieve maximum power. In the LabVIEW environment, an automated monitoring system is developed. The automatic monitoring system assesses the voltage drop losses present in the DC side of the PV generator and generates a decimal weighted value depending on the defective solar panels and transmits this value to the remote station through an RF modem, and provides an indicator of the faulty solar panel over the built-in Interface LabVIEW. The managing of this GUI indicator helps the monitoring system to generate a panel alert for damaged panels in the PV system. Node MCU in the receiver section enables transmission of the fault status of PV arrays via Internet connectivity. The IoT-based Blynk app is employed for visualizing the fault status of the 3 × 3 PV array. The dashboard of Blynk visualizes every array with the status.     

Gauss Gradient and SURF Features for Landmine Detection from GPR Images

Recently, ground-penetrating radar (GPR) has been extended as a well-known area to investigate the subsurface objects. However, its output has a low resolution, and it needs more processing for more interpretation. This paper presents two algorithms for landmine detection from GPR images. The first algorithm depends on a multi-scale technique. A Gaussian kernel with a particular scale is convolved with the image, and after that, two gradients are estimated; horizontal and vertical gradients. Then, histogram and cumulative histogram are estimated for the overall gradient image. The bin values on the cumulative histogram are used for discrimination between images with and without landmines. Moreover, a neural classifier is used to classify images with cumulative histograms as feature vectors. The second algorithm is based on scale-space analysis with the number of speeded-up robust feature (SURF) points as the key parameter for classification. In addition, this paper presents a framework for size reduction of GPR images based on decimation for efficient storage. The further classification steps can be performed on images after interpolation. The sensitivity of classification accuracy to the interpolation process is studied in detail.     

GGA-SIC Calculations for Electronic and Magnetic Study of CdS Alloys

Journal of Superconductivity and Novel Magnetism - Electronic and magnetic properties of CdS-based, doped by various transition metal elements (Ti, V, Cr, Mn, Fe, Co or Ni), dilute magnetic...     

ARTIFICIAL INTELLIGENCE(AI)-DRIVEN SPECTRUM MANAGEMENT

Recent advances in communication and networking technologies are leading to a plethora of novel wireless services that range from unmanned aerial vehicle(UAV)communication to smart cognitive networks and massive Internet of Things(IoT)systems.Enabling these emerging applications over the fifth generation(5G)of wireless cellular systems requires meeting numerous challenges pertaining to spectrum sharing and management.In fact,most 5G applications will be highly reliant on intelligent spectrum management techniques,which should adapt to dynamic network environments while also guaranteeing high reliability and high quality-of-experience(QoE).     

COACT: a query interface language for collaborative databases

Data curation activities in collaborative databases mandate that collaborators interact until they converge and agree on the content of their data. In a previous work, we presented a cloud-based collaborative database system that promotes and enables collaboration and data curation scenarios. Our system classifies different versions of a data item to either pending, approved, or rejected. The approval or rejection of a certain version is done by the database Principle Investigators (or PIs) based on its value. Our system also allows collaborators to view the status of each version and help PIs take decisions by providing feedback based on their experiments and/or opinions. Most importantly, our system provided mechanisms for history tracking of different versions to trace the modifications and approval/rejection done by both collaborators and PIs on different versions of a data item. We labeled our system as Update-Pending-Approval model (or UPA). In this paper, we describe a high level SQL query interface language for PIs and collaborators to interact with the UPA framework. We define a set of UPA keywords that are used as a part of the history tracking mechanism to select specific versions of a data item, and a set of UPA options that select specific versions based on possible future decisions of PIs. We implemented our query interface mechanism on top of Apache Phoenix, taking into consideration that the UPA system was implemented on top of Apache HBase. We test the performance of the UPA query language by executing several queries that contain different complexity levels and discuss their results.     

Evaluating Regression Models for Temporal Prediction of Wi-Fi Device Mobility

Wireless Personal Communications - The ability to predict the arrival and residence time of mobile users at a particular place is essential for the development of a wealth of new applications and...