empirical cumulative distribution function
Recently Published Documents


TOTAL DOCUMENTS

32
(FIVE YEARS 13)

H-INDEX

5
(FIVE YEARS 1)

2022 ◽  
Vol 2022 ◽  
pp. 1-16
Author(s):  
Alaa M. Mukhtar ◽  
Rashid A. Saeed ◽  
Rania A. Mokhtar ◽  
Elmustafa Sayed Ali ◽  
Hesham Alhumyani

Emerging 5G network cellular promotes key empowering techniques for pervasive IoT. Evolving 5G-IoT scenarios and basic services like reality augmented, high dense streaming of videos, unmanned vehicles, e-health, and intelligent environments services have a pervasive existence now. These services generate heavy loads and need high capacity, bandwidth, data rate, throughput, and low latency. Taking all these requirements into consideration, internet of things (IoT) networks have provided global transformation in the context of big data innovation and bring many problematic issues in terms of uplink and downlink (DL) connectivity and traffic load. These comprise coordinated multipoint processing (CoMP), carriers’ aggregation (CA), joint transmissions (JTs), massive multi-inputs multi-outputs (MIMO), machine-type communications, centralized radios access networks (CRAN), and many others. CoMP is one of the most significant technical enhancements added to release 11 that can be implemented in heterogonous networks implementation approaches and the homogenous networks’ topologies. However, in a massive 5G-IoT device scenario with heavy traffic load, most cell edge IoT users are severely suffering from intercell interference (ICI), where the users have poor signal, lower data rates, and limited QoS. This work is aimed at addressing this problematic issue by proposing two types of DL-JT-CoMP techniques in 5G-IoT that are compliant with release 18. Downlink JT-CoMP with two homogeneous network CoMP deployment scenarios is considered and evaluated. The scenarios used are IoT intrasite and intersite CoMP, which performance evaluated using downlink system-level simulator for long-term evolution-advanced (LTE-A) and 5G. Numerical simulation scenarios were results under high dense scenario—with IoT heavy traffic load which shows that intersite CoMP has better empirical cumulative distribution function (ECDF) of average UE throughput than intrasite CoMP approximately 4%, inter-site CoMP has better ECDF of average user entity (UE) spectral efficiency than intrasite CoMP almost 10%, and intersite CoMP has approximately same ECDF of average signal interference noise ratio (SINR) as intrasite CoMP and intersite CoMP has better fairness index than intrasite CoMP by 5%. The fairness index decreases when the users’ number increase since the competition among users is higher.


2021 ◽  
Author(s):  
Yu Rong ◽  
Panagiotis C. Theofanopoulos ◽  
Georgios C. Trichopoulos ◽  
Daniel W. Bliss

Abstract This study presents findings at Terahertz (THz) frequency band for non-contact cardiac sensing application. For the first time, cardiac pulse information is simultaneously extracted using THz waves based on the two established principles in electronics and optics. The first fundamental principle is micro-Doppler (mD) motion effect, initially introduced in coherent laser radar system 1, 2 and first experimentally demonstrated for vital sign detection 3. This motion based method, primarily using coherent phase information from the radar receiver, has been widely exploited in microwave frequency bands and has recently found popularity in millimeter waves (mmWave). The second fundamental principle is reflectance based optical measurement using infrared or visible light. The variation in the light reflection is proportional to the volumetric change of the heart, often referred as photoplethysmography (PPG). PPG has been a popular technology for pulse diagnosis. Recently it has been widely incorporated into various smart wearables for long-term monitoring, such fitness training and sleep monitoring. Herein, the concept of Terahertz-Wave-Plethysmography (TPG) is introduced, which detects blood volume changes in the upper dermis tissue layer by measuring the reflectance of THz waves, similar to the existing remote PPG (rPPG) principle 4. The TPG principle is justified by scientific deduction, electromagnetic wave (EM) simulations and carefully designed experimental demonstrations. Additionally, pulse measurements from various peripheral body parts of interest (BOI), palm, inner elbow, temple, fingertip and forehead, are demonstrated using a wideband THz sensing system developed by Terahertz Electronics Lab at Arizona State University (ASU), Tempe. Among the BOIs under test, it is found that the measurements from forehead BOI gives the best accuracy with mean heart rate (HR) estimation error 1.51 beats per minute (BPM) and stand deviation (std) 1.08 BPM. The results validate the feasibility of radar based plethysmography for direct pulse monitoring. Finally, a comparative study on pulse sensitivity in TPG and rPPG is conducted. The results indicate that the TPG contains more pulsatile from the forehead BOI than that in the rPPG signals and thus generate better heart rate (HR) estimation statistic in the form of empirical cumulative distribution function (CDF) of HR estimation error.


2021 ◽  
Vol 13 (21) ◽  
pp. 4243
Author(s):  
Mona Morsy ◽  
Ruhollah Taghizadeh-Mehrjardi ◽  
Silas Michaelides ◽  
Thomas Scholten ◽  
Peter Dietrich ◽  
...  

Water depletion is a growing problem in the world’s arid and semi-arid areas, where groundwater is the primary source of fresh water. Accurate climatic data must be obtained to protect municipal water budgets. Unfortunately, the majority of these arid regions have a sparsely distributed number of rain gauges, which reduces the reliability of the spatio-temporal fields generated. The current research proposes a series of measures to address the problem of data scarcity, in particular regarding in-situ measurements of precipitation. Once the issue of improving the network of ground precipitation measurements is settled, this may pave the way for much-needed hydrological research on topics such as the spatiotemporal distribution of precipitation, flash flood prevention, and soil erosion reduction. In this study, a k-means cluster analysis is used to determine new locations for the rain gauge network at the Eastern side of the Gulf of Suez in Sinai. The clustering procedure adopted is based on integrating a digital elevation model obtained from The Shuttle Radar Topography Mission (SRTM 90 × 90 m) and Integrated Multi-Satellite Retrievals for GPM (IMERG) for four rainy events. This procedure enabled the determination of the potential centroids for three different cluster sizes (3, 6, and 9). Subsequently, each number was tested using the Empirical Cumulative Distribution Function (ECDF) in an effort to determine the optimal one. However, all the tested centroids exhibited gaps in covering the whole range of elevations and precipitation of the test site. The nine centroids with the five existing rain gauges were used as a basis to calculate the error kriging. This procedure enabled decreasing the error by increasing the number of the proposed gauges. The resulting points were tested again by ECDF and this confirmed the optimum of thirty-one suggested additional gauges in covering the whole range of elevations and precipitation records at the study site.


2021 ◽  
Author(s):  
Bruno Majone ◽  
Diego Avesani ◽  
Patrick Zulian ◽  
Aldo Fiori ◽  
Alberto Bellin

Abstract. Climate change impact studies on hydrological extremes often rely on the use of hydrological models with parameters inferred by using observational data of daily streamflow. In this work we show that this is an error prone procedure when the interest is to develop reliable Empirical Cumulative Distribution Function curves of annual streamflow maximum. As an alternative approach we introduce a methodology, coined Hydrological Calibration of eXtremes (HyCoX), in which the calibration of the hydrological model is carried out by directly targeting the probability distribution of high flow extremes. In particular, hydrological simulations conducted during a reference period, as driven by climate models’ outputs, are constrained to maximize the probability that the modeled and observed high flow extremes belong to the same population. The application to the Adige river catchment (southeastern Alps, Italy) by means of HYPERstreamHS, a distributed hydrological model, showed that this procedure preserves statistical coherence and produce reliable quantiles of the annual maximum streamflow to be used in assessment studies.


2021 ◽  
Vol 22 (9) ◽  
Author(s):  
RACHMAT HIDAYAT ◽  
MUKTI ZAINUDDIN ◽  
ACHMAR MALLAWA ◽  
MUZZNEENA AHMAD MUSTAPHA ◽  
A. RANI SAHNI PUTRI

Abstract. Hidayat R, Zainuddin M, Mallawa A, Mustapha MA, Putri ARS. 2021. Mapping spatial-temporal skipjack tuna habitat as a reference for Fish Aggregating Devices (FADs) settings in Makassar Strait, Indonesia. Biodiversitas 22: 3637-3647. Skipjack tuna (Katsuwonus pelamis) has a high economic value in the international market. Catching skipjack tuna using fish aggregating devices (FADs) without knowing its habitat characteristics can damage the ecosystem. This study aimed to determine suitable fishing areas for setting skipjack’s FADs. The data used included that on catch, sea surface temperature (SST), and sea surface chlorophyll-a (SSC) in the Makassar Strait obtained for 2017-2019. The generalized additive model (GAM) and empirical cumulative distribution function (ECDF) analyses were used to investigate the skipjack’s tuna habitat. A pelagic habitat index (PHI), with PHI > 75%, was applied to determine suitable FAD positions. The gravity center of the skipjack tuna habitat for ten months (January-October 2020) was calculated to validate the model’s results. The results showed that the optimum SST range was from 28.78°C to 31.25°C, while the SSC from 0.18 to 0.28 mg m-3. The best skipjack habitats in the southern Makassar Strait are criterion 4 (PHI > 90%) and criterion 3 (PHI = 85-90%), having a relatively high consistency of the average PHI values. These results can help determine the optimal positions for setting FADs to benefit the global management and sustainable development of skipjack tuna fisheries.


2021 ◽  
Vol 22 (7) ◽  
Author(s):  
ANDI RANI SAHNI PUTRI ◽  
Mukti Zainuddin ◽  
MUSBIR MUSBIR ◽  
RACHMAT HIDAYAT ◽  
MUZZNEENA AHMAD MUSTAPHA

Abstract. Putri ARS, Zainuddin M, Musbir, Mustapha MA, Hidayat R. 2021. Mapping potential fishing zones for skipjack tuna in the southern Makassar Strait, Indonesia, using Pelagic Habitat Index (PHI). Biodiversitas 22: 3037-3045. Southern Makassar Strait is one of the potential fishing grounds for skipjack tuna in the Indonesian waters. Oceanographic factors become the primary factors that limit the distribution and abundance of fish. The study aimed to identify the relationship between fish distribution with sea surface temperature (SST) and primary productivity (PP) and map out the potential fishing grounds of skipjack tuna in the southern Makassar Strait. It used pelagic habitat index (PHI) analysis, which is strengthened by the results of correlation analysis in the form of generalized additive models (GAM) and Empirical cumulative distribution function (ECDF) analysis. The results showed that the distribution of skipjack tuna was significantly associated with the preferred range of SST 29-30.5°C and PP 350-400 mg C/m2/day. The potential fishing zone is well established near the coast to offshore of Barru and Polman waters (3°-6°S and 117°-119°E), with the peak season in May and October. The spatial pattern of potential fishing grounds for skipjack fishing is associated with hotspots (oceanographic preference), leading to increased feeding opportunities. This study suggests that the spatial pattern of high potential fishing zones could improve fishing, management, and conservation strategies along the southern Makassar Strait.


Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 475
Author(s):  
Hassen Babaousmail ◽  
Rongtao Hou ◽  
Brian Ayugi ◽  
Moses Ojara ◽  
Hamida Ngoma ◽  
...  

This study assesses the performance of historical rainfall data from the Coupled Model Intercomparison Project phase 6 (CMIP6) in reproducing the spatial and temporal rainfall variability over North Africa. Datasets from Climatic Research Unit (CRU) and Global Precipitation Climatology Centre (GPCC) are used as proxy to observational datasets to examine the capability of 15 CMIP6 models’ and their ensemble in simulating rainfall during 1951–2014. In addition, robust statistical metrics, empirical cumulative distribution function (ECDF), Taylor diagram (TD), and Taylor skill score (TSS) are utilized to assess models’ performance in reproducing annual and seasonal and monthly rainfall over the study domain. Results show that CMIP6 models satisfactorily reproduce mean annual climatology of dry/wet months. However, some models show a slight over/under estimation across dry/wet months. The models’ overall top ranking from all the performance analyses ranging from mean cycle simulation, trend analysis, inter-annual variability, ECDFs, and statistical metrics are as follows: EC-Earth3-Veg, UKESM1-0-LL, GFDL-CM4, NorESM2-LM, IPSL-CM6A-LR, and GFDL-ESM4. The mean model ensemble outperformed the individual CMIP6 models resulting in a TSS ratio (0.79). For future impact studies over the study domain, it is advisable to employ the multi-model ensemble of the best performing models.


2021 ◽  
Author(s):  
Silas Michaelides ◽  
Mona Morsy ◽  
Ruhollah Taghizadeh-Mehrjardi ◽  
Thomas Scholten ◽  
Peter Dietrich ◽  
...  

<p>Water scarcity is a growing concern in arid and semi-arid regions of the World, locations where groundwater is the main source of freshwater. In order to preserve local water budgets, it is critical that accurate climatic data be acquired. Unfortunately, the majority of these arid regions feature a very limited number of rain gauges, reducing the reliability of the data produced. The present study offers a series of steps for overcoming the issue of data scarcity. Once resolved, this could then promote greatly needed hydrological studies on topics such as the spatiotemporal distribution of rainfall, the mitigation of flash floods hazards, or the minimization of soil erosion. In the present study, the DEM file and GPM (IMERG) data were used to identify the most suitable locations for a new network of rain gauges at the Eastern side of the Gulf of Suez. These two datasets were clustered using k-means clustering to produce an elbow graph whose elbow-shaped region offered several possible options for the number of optimum clusters at the test site. The authors chose three different cluster sizes (3, 6, and 9) and calculated the possible centroids for each size. Calculations resulted in 3 centroids, 6 centroids, and 9 centroids. These centroids were tested using the empirical cumulative distribution function (ECDF), once the sum of the GPM (IMERG) scenes, the scene limits, and the elevation map limits were determined. This test revealed gaps in all centroids mentioned. Consequently, the authors established nine clusters as the optimal size. Nine centroids were therefore taken, along with the existing five gauges, as a basis for standard error kriging. This allowed the authors to gradually minimize error via looping. The newly added points were tested with an ECDF. The complete spectrum of rainfall and elevation was efficiently covered by the 31 proposed rain gauge locations, and the five existing gauges.</p>


Sign in / Sign up

Export Citation Format

Share Document