Service Time Model Research Articles

Biosorptive removal of Zn(II) ions by Pongamia oil cake (Pongamia pinnata) in batch and fixed-bed column studies using response surface methodology and artificial neural network

Design of experiment and artificial neural networks (ANN) have been effectively employed to predict the rate of uptake of Zn(II) ions onto defatted pongamia oil cake. Four independent variables such as, pH (2.0–7.0), initial concentration of Zn(II) ions (50–500 mg/L), temperature (30ºC-50 °C), and dosage of biosorbent (1.0–5.0 g/L) were used for the batch mode while the three independent variables viz. flowrate, initial concentration of Zn(II) ions and bed height were employed for the continuous mode. Second-order polynomial equations were then derived to predict the Zn(II) ion uptake rate. The optimum conditions for batch studies was found to be pH: 4.45, metal ion concentration: 462.48 mg/L, dosage: 2.88 g/L, temperature: 303 K and on the other hand the column studies flow rate: 5.59 mL/min, metal ion concentration: 499.3 mg/L and bed height: 14.82 cm. Under these optimal condition, the adsorption capacity was 80.66 mg/g and 66.29 mg/g for batch and column studies, respectively. The same data was fed to train a feed-forward multilayered perceptron, using MATLAB to develop the ANN based model. The predictive capabilities of the two methodologies were compared, by means of the absolute average deviation (AAD) (4.57%), model predictive error (MPE) (4.15%), root mean square error (RMSE) (3.19), standard error of prediction (SEP) (4.23) and correlation coefficient (R) (0.99) for ANN and for RSM AAD (16.27%), MPE (21,25%), RMSE (13.15%), SEP and R (0.96) by validation data. The findings suggested that compared to the prediction ability of RSM model, the properly trained ANN model has better prediction ability. In batch studies, equilibrium data was used to determine the isotherm constants and first and second order rate constants. In column, bed depth service time (BDST) and Thomas model was used to fit the obtained column data.

Adsorption of Pb(II) by a polyvinylidene fluoride membrane bearing chelating poly(amino phosphonic acid) and poly(amino carboxylic acid) groups

Pb(II) can cause a hazardous effect on ecosystem and public health due to its high biotoxicity. A polyvinylidene fluoride-type membrane bearing both poly(amino phosphonic acid) and poly(amino carboxylic acid) functional groups was fabricated for the purpose of Pb(II) removal from the aqueous solutions. The adsorption behaviors of the fabricated chelating membrane toward Pb(II) were studied by the series of static and continuous adsorption experiments. When the pH, adsorption equilibrium time, initial Pb(II) concentration, and temperature were 5.1, 300 min, 1.0 mmol g−1, and 298 K, respectively, Pb(II) uptake of the membrane was 1.1 mmol g−1. The presence of coexisting metal ions and complexing reagents decreased the Pb(II) uptake. The adsorption kinetic and isotherm adsorption followed pseudo-second-order equation and Langmuir model, respectively; this adsorption process showed a spontaneous and exothermic feature. The bed depth service time and Thomas models were suitable for describing obtained breakthrough curves.

Fixed-bed column system for Cd2+ uptake from aqueous solution by sodium- and thiourea-modified clinoptilolite-rich tuff

ABSTRACTTwo kinds of clinoptilolite-rich tuffs from the state of Sonora (Mexico), previously treated with NaCl solution and then modified with thiourea, were investigated to remove Cd2+ from aqueous solution in a fixed-bed column system. Experiments were conducted with a 30 mg L−1 Cd2+ solution at a pH value of 5 and three-bed heights of sodium- and thiourea-modified clinoptilolite-rich tuffs. The experimental data were examined with the bed depth service time model (BDST), the Thomas model, and a mass balance approach. According to the BDST model, the dynamic sorption capacity (No) for the thiourea-modified clinoptilolite-rich tuff was 0.0357 Kg L−1. This value corresponded to 1.2 times higher than that for sodium-modified clinoptilolite-rich tuff (0.0287 Kg L−1). The experimental data obtained for sodium- modified clinoptilolite-rich tuff (ZSGNa) with 3 cm of bed height, fitted to the Thomas model, with R2 = 0.9679 and Cd sorption capacity of 35.4 mg g−1, while for the thiourea-modified clinoptilolite-rich tuff (ZSGThio) with 4.5 cm of bed height, was 36.52 mg g−1 with R2 = 0.9368. The parameters calculated with the mass balance model describe a favourable process where the system with ZSGThio (6 cm bed height) had the best performance for sorption capacity up to the breakthrough point, qb = 22.35 mg g−1. The zeolite modified with thiourea exhibited higher capacity in Cd2+ removal than the one modified with NaCl, in the column with 6 cm of bed height. To investigate the mechanisms of removal of Cd2+ by the modified zeolites, Na⁺ was measured to determine the milliequivalents of cadmium removed.

Adsorption of phosphorus by alkaline Tunisian soil in a fixed bed column.

The present study evaluates the phosphorus (P) adsorption by alkaline soil in fixed bed column mode operation. The effects of flow rate, bed height, and initial P concentration on breakthrough curves were evaluated. Data confirmed that both the breakthrough and exhaustion time increased in parallel with the rise in bed height and the decline in flow rate and initial P concentration. The adsorption capacity was observed to increase with decreasing flow rate and bed height and increasing initial concentration. Moreover, continuous adsorption experiments were conducted using three salts (NaCl, KCl and CaCl2) with the same concentration (0.01 M) to investigate the P adsorption behavior in saline conditions. The results showed that all three salts improve the P adsorption in the soil column. Consequently, the bed performance was significantly enhanced with salts addition. The maximum adsorption capacity of 13.47 mg g-1 for P, 16.13 mg g-1 for P-NaCl, 22.10 mg g-1 for P-KCl, 30.05 mg g-1 for P-CaCl2 was attained at an initial influent concentration of 300 mg g-1, bed height of 22 cm, and flow rate of 10 mL min-1. TheCaCl2 addition was therefore the most effective in increasing P adsorption. Thomas, Yoon-Nelson and Clark models were applied to experimental results to forecast the breakthrough curves by nonlinear regression analysis. Meanwhile, the bed depth service time model was employed to examine the effective model parameters in scaling up the process using linear regression analysis. The values of correlation coefficient (R2) and the sum of squared error evidenced that the Thomas model is the most appropriate model to fit the experimental data. The reusability experiment showed that the adsorbent material still had high P adsorption capacity, and tolerable desorption efficiency.

Adsorption of cadmium (II) from simulated wastewater using <i>Albizia saman</i> pod activated carbon in fixed bed columns

The possibility of using Albizia saman pod activated carbon (ASPAC) as an adsorbent in fixed down flow adsorption columns to remove Cd (II) from wastewater was investigated for the purpose of converting the waste to a valuable product. The effects of impregnation ratio, particle size, carbon height, pressure head and initial cadmium Cd (II) concentration on the adsorption of Cd (II) from wastewater were investigated. The obtained adsorption data from the experiment was then fitted into the Hutchin’s bed depth service time (BDST) model to study the columns performance at 15% and 90% breakthrough concentrations. The BDST model constants were determined. An optimal pressure head of 5 cm, impregnation ratio of 1:6, packing height of 3.5 cm, particle size of 75 μm and initial Cd (II) concentration of 0.029 mg/L were found to be the most effective combination, which removed 100 % of the Cd (II) within a service time of 14 hrs. There was a gradual decrease in the percentage of adsorbed Cd (II) with time; the percentage adsorbed became zero at 44, 56 and 86 hours respectively for 2.5 cm, 3 cm and 3.5 cm carbon heights. The breakthrough curves for Cd (II) adsorption maintained the characteristic S-curve for most dynamic studies. Chi-squared test performed on the developed BDST models revealed the goodness of fit of the models for the prediction of the columns performance at all breakthrough concentrations investigated. The use of ASPAC as adsorbent for the removal of Cd (II) from wastewater in adsorption columns is therefore recommended.Key words: Activated carbon, cadmium (II), fixed bed columns, Albizia saman pod, wastewater.

Adsorptive batch and column studies of Congo Red onto gulmohar leaf powder

The present manuscript describes the adsorptive batch and column treatment of synthetic Congo Red dye onto naturally prepared adsorbents viz. gulmohar leaf powder and activated gulmohar leaf powder using sulfuric acid. The surface characterizations of naturally prepared adsorbents were performed by various sophisticated analytical techniques. Effect of various process parameters like adsorbent dosage, temperature, initial concentration, and pH for batch study; and flow rate and bed height for column study are explored. All batch adsorption data are analyzed using Freundlich and Langmuir adsorption isotherm model. The Thomas, Yoon-Nelson, Adams and Bohart, and Bed Depth Service Time model are applied to predict the breakthrough curves and to determine the characteristic parameters of the column useful for process design. Activated gulmohar leaf powder is more feasible adsorbent compared to normal gulmohar leaf powder. Maximum adsorption capacity related to Adams and Bohart model; and Langmuir isotherm was found to be 919.4 mg/L; and 434.7 mg/g, respectively, for activated gulmohar leaf powder.

Removal of ciprofloxacin hydrochloride from aqueous solution using vertical bed and sequential bed columns

In the present paper column studies for the removal of ciprofloxacin hydrochloride from aqueous solution using vertical and sequential bed adsorption columns using ZnO nanoparticles and groundnut shell powder (GSP) as adsorbents have been discussed. Bed depth service time model (BDST) has been used to determine the column parameters i.e length of the column, bed depth and flow rate. Studies at varying drug concentrations and flow rates have been carried out at pH 4 for ZnO nanoparticles and 6 for groundnut shell powder i.e the pH where maximum adsorption of ciprofloxacin has been found to occur in batch studies using ZnO nanoparticles and groundnut shell powder. The bed capacity for ZnO nanoparticles has been found to be 6.1 mg/g and 6.24 mg/g using a vertical bed and sequential bed column respectively and for groundnut shell powder it is 5.59 mg/g and 6.29 mg/g for a feed concentration of 80 mg/L and flow rate 5 ml/min. at 298 K temperature. Analyses of breakthrough curves show that the time taken by columns for 50% breakthrough and 90% exhaustion increases with increase in the feed concentration and flow rate. The Thomas model and Yoon-Nelson models are in good agreement with experimental data. It is found that the bed capacity for sequential column, which is easier to handle and use, is slightly better than that of vertical column and can be considered for use in small scale industries.

Performance and dynamic modelling of biochar and kaolin packed bed adsorption column for aqueous phase methylene blue (MB) dye removal

ABSTRACT A practical continuous adsorption study in a packed-bed column was conducted by using two separate layers of kaolin and pine cone based biochar packed bed adsorbents for the removal of methylene blue (MB) dye from its aqueous solution. A series of column experiments were performed to determine the breakthrough curves (BTCs) by varying bed height (3–7 cm), inlet flow rate (13–17 ml/min) and initial dye concentration (50–150 mg/L). The Thomas, Yoon-Nelson, Bed Depth Service Time (BDST) and Dose response (DR) dynamic models were applied to column experimental data under various operational conditions to predict the column breakthrough curves (BTC) using both nonlinear regression and linear regression and to determine various characteristic parameters such as percentage removal of dye, breakthrough time, used bed length, mass transfer zone (MTZ) and dye adsorption density q (total) that are useful for process design. The MB dye adsorption was found to be most favourable under low flow rate, high adsorbent bed height and high initial dye concentrations. The experimental column breakthrough data were in good agreement with the various dynamic models and the results of various model characteristic parameters could be used to scale up the process to an actual industrial column operation. Also, this column study revealed the feasibility of pine cone biochar and kaolin adsorbents as alternative sustainable adsorbents for dye-bearing wastewater treatment.

Decolorization of synthetic dye wastewater using packed bed electro-adsorption column

The present study reports the electro-adsorption of Methylene blue (MB) dye from synthetic wastewater onto activated carbon in a packed bed electro-adsorption column and the break through data was analyzed for dye adsorption. The influences of bed height, flow rate and initial dye concentration with and without the presence of electrical potential on packed bed adsorption have been investigated and the possibility of regeneration of column was studied. The parameters such as bed capacity, mass transfer zone, bed utilization and adsorbent usage were evaluated from the break through curves. The columns characteristic design parameters have been evaluated using the adsorption models such as Bed Depth Service Time (BDST), Adam-boharts, Thomas and Yoon-Nelson models. The model parameters have been derived using origin software. Out of four adsorption models, Thomas and Yoon-Nelson models were found to be ideal to analyze the column performance with R2 ≥ 0.80. From the results, it is observed that electro-adsorption is more efficient than adsorption as the adsorption capacity is 3.18 folds higher and the amount of adsorbent required was much lesser for electro-adsorption. Also the saturation capacity is 0.17 mg/g for electro-adsorption whereas it is 0.069 mg/g for conventional adsorption at optimized condition, which confirms the stability of electro-adsorption column. It has been observed that modifications in electrode played a major role in dye waste water treatment processes.

Experimental and modelling studies on fixed bed adsorption for Cu(II) removal from aqueous solution by carboxyl modified jute fiber

To guide the practical application of fibrous materials in wastewater treatment, this study explored the engineering design of fixed bed adsorption technique by using carboxyl-modified jute fiber (CMJF) for copper ion (Cu(II)) removal from aqueous solution. The study, conducted by means of adsorption experiments in a column with a fixed bed of sorbent, investigated the effects of the CMJF sorbent dosage, the flow rate and the initial Cu(II) concentration on the corresponding breakthrough curves and compared the dynamic adsorption performance of raw and modified jute in the same process conditions. Compared with the fixed bed of raw jute fiber, the CMJF sorbent exhibited a breakthrough time about 3.2 times longer and a dynamic adsorption capacity roughly 4.2 times higher at the optimal conditions (packing height of 8 cm, flow rate of 17.45 cm/min and initial concentration of 100 mg/L). The dynamic adsorption capacity, 50% breakthrough time and 10% breakthrough time could be well predicted by Thomas, Yoon–Nelson and Bed Depth Service Time (BDST) models, respectively. Besides, these dynamic models well described the fixed bed adsorption behavior, and the CMJF exhibited better fixed bed adsorption performance than raw jute.

Application of zirconium caged activated biochar alginate beads towards deionization of Cr(VI) laden water in a fixed bed column reactor

An investigation of dynamic fixed bed loaded with zirconium caged steam activated biochar alginate bead was performed towards deionization of Cr(VI) laden aqueous solution. Impact of process parametric factors which include bed height (5 to 30 cm), initial influent concentration (10 to 60 mg/L) and flow rate (1 to 4 mL/min) were studied at a constant pH of 3 ± 0.5 from a synthetic non-competitive Cr(VI) solution. As interpreted from the experimentations it was observed that with every increase in bed height, length of the breakthrough curve also increased. On the contrary to bed height, increase in metal concentration and flow rate with predefined bed height efficacy of the column decreased. The adsorbent bed was able to retain 499.5 mg of ions with an uptake of 116.805 mg/g from an optimum influent metal concentration of 50 mg/L at a flow rate of 1 mL/min. A removal of 93.54% was observed at this optimum condition. The process was evaluated with bed depth service time model, Thomas and Yoon-Nelson model which substantiated the findings. From desorption-adsorption cycle it was observed that the column retained its removal efficacy up to 7 cycles with a column regeneration percentage of 51.108%. This adsorbent was capable of removing Cr(VI) from a multi-ion synthetic waste water solution where the breakthrough curve showed similarity with 10 mg/L of synthetic single Cr(VI) ion solution. Thus, the prepared zirconium caged adsorbent could be used in a fixed bed column reactor towards remediating metal ions from contaminated aqueous solution.

Kinetic modeling of lead removal in a resin column–parameters evaluation

Abstract Lead contamination of water streams, a potential threat to ecosystem, was treated using a cation exchange resin under continuous conditions in a upflow column. The optimal pH for maximum lead removal was identified through the batch experiments. Neutral pH was found to be favorable due to non-existence of competing hydrogen ions and absence of hydroxide containing precipitate formations. The effects of flow rates (4.0 to 8.0 mL/ min) and the resin bed depth (6 to 18 cm) were studied under optimal pH and fixed initial lead concentration of 50 mg/L. The breakthrough curves were plotted and analyzed in detail. Bed Depth Service Time (BDST) and Thomas model were fitted to the experimental data and the model parameters were determined. The maximum exchange capacity of the bed (q0) was determined as 14.60 mg/g at a flow rate of 4 mL/min and a bed height of 12 cm and the Thomas model constant decreased with decrease in flow rate. BDST model parameters, namely, N0 and Ka, increased with increase in flow rates. BDST proved to be a better fit compared to Thomas model under the entire range of operating conditions tested.

Potentiality of a fruit peel (banana peel) toward abatement of fluoride from synthetic and underground water samples collected from fluoride affected villages of Birbhum district

Contamination of underground water with fluoride (F) is a tremendous health hazard. Excessive F (> 1.5 mg/L) in drinking water can cause both dental and skeletal fluorosis. A fixed-bed column experiments were carried out with the operating variables such as different initial F concentrations, bed depths, pH and flow rates. Results revealed that the breakthrough time and exhaustion time decrease with increasing flow rate, decreasing bed depth and increasing influent fluoride concentration. The optimized conditions are: 10 mg/L initial fluoride concentration; flow rate 3.4 mL/min, bed depth 3.5 and pH 5. The bed depth service time model and the Thomas model were applied to the experimental results. Both the models were in good agreement with the experimental data for all the process parameters studied except flow rate, indicating that the models were appropriate for removal of F by natural banana peel dust in fix-bed design. Moreover, column adsorption was reversible and the regeneration was accomplished by pumping of 0.1 M NaOH through the loaded banana peel dust column. On the other hand, field water sample analysis data revealed that 86.5% fluoride can be removed under such optimized conditions. From the experimental results, it may be inferred that natural banana peel dust is an effective adsorbent for defluoridation of water.

Concrete/maghemite nanocomposites as novel adsorbents for arsenic removal

Concrete/maghemite nanocomposites were prepared by aging a mixture of magnetite nanoparticles (NPs), sand and Portland cement. Diverse spectroscopies and magnetometry revealed that the nanocomposites incorporate maghemite NPs in the concrete structure. Scanning electron microscopy also revealed the presence of maghemite NPs and variations on the surface morphology of concrete. Regarding the evaluation of the arsenic removal properties of concrete/maghemite nanocomposite, it was found that the addition of the NPs improved the arsenic removal capacity of concrete. Batch studies revealed that the adsorption isotherms fitted to the Gunary isotherm model. Furthermore, column studies demonstrated the application of the nanocomposites for arsenic removal from well water under dynamic conditions. Using the bed depth service time model for the evaluation of the column performance, it was shown that the columns of concrete/maghemite nanocomposites can diminish the arsenic concentration of water from 10 ppm to 10 ppb. By XPS, the adsorption of As(V) species on the nanocomposites was demonstrated. The use of magnetic NPs in concrete demonstrated that the magnetic properties of maghemite are conserved and the arsenic removal capacity of concrete is augmented. Moreover, the nanocomposites can be used in continuous flow systems for arsenic removal from hard water.

Mathematical modeling of the adsorption/desorption characteristics of anthocyanins from muscadine (Vitis rotundifolia cv. Noble) juice pomace on Amberlite FPX66 resin in a fixed bed column.

Muscadine grape pomace, a by-product of juicing and wine-making, contains significant amounts of anthocyanin 3,5-diglucosides, known to be beneficial to human health. The objective of this research was to use mathematical modeling to investigate the adsorption/desorption characteristics of these anthocyanins from muscadine grape pomace on Amberlite FPX66 resin in a fixed bed column. Anthocyanins were extracted using hot water and ultrasound, and the extracts were loaded onto a resin column at five bed depths (5, 6, 8, 10 and 12 cm) using three flow rates (4, 6 and 8 mL min-1 ). It was found that adsorption on the column fitted the bed depth service time (BDST) model and the empty bed residence time (EBRT) model. Desorption was achieved by eluting the column using ethanol at four concentrations (25, 40, 55 and 70% v/v) and could be described with an empirical sigmoid model. The breakthrough curves of anthocyanins fitted the BDST model for all three flow rates with R2 values of 0.983, 0.992 and 0.984 respectively. The EBRT model was successfully employed to find the operating lines, which allow for column scale-up while still achieving similar results to those found in a laboratory operation. Desorption with 40% (v/v) ethanol achieved the highest recovery rate of anthocyanins at 79.6%. The mathematical models established in this study can be used in designing a pilot/industrial- scale column for the separation and concentration of anthocyanins from muscadine juice pomace. © 2018 Society of Chemical Industry.

Fixed-bed operation for manganese removal from water using chitosan/bentonite/MnO composite beads.

In the present study, a new composite adsorbent, chitosan/bentonite/manganese oxide (CBMnO) beads, cross-linked with tetraethyl-ortho-silicate (TEOS) was applied in a fixed-bed column for the removal of Mn (II) from water. The adsorbent was characterised by scanning electron microscopy (SEM), Fourier transform infra-red (FT-IR), N2 adsorption-desorption and X-ray photoelectron spectroscopy (XPS) techniques, and moreover the point of zero charge (pHpzc) was determined. The extend of Mn (II) breakthrough behaviour was investigated by varying bed mass, flow rate and influent concentration, and by using real environmental water samples. The dynamics of the column showed great dependency of breakthrough curves on the process conditions. The breakthrough time (tb), bed exhaustion time (ts), bed capacity (qe) and the overall bed efficiency (R%) increased with an increase in bed mass, but decreased with the increase in both influent flow rate and concentration. Non-linear regression suggested that the Thomas model effectively described the breakthrough curves while large-scale column performance could be estimated by the bed depth service time (BDST) model. Experiments with environmental water revealed that coexisting ions had little impact on Mn (II) removal, and it was possible to achieve 6.0mg/g breakthrough capacity (qb), 4.0L total treated water and 651 bed volumes processed with an initial concentration of 38.5mg/L and 5.0g bed mass. The exhausted bed could be regenerated with 0.001M nitric acid solution within 1h, and the sorbent could be reused twice without any significant loss of capacity. The findings advocate that CBMnO composite beads can provide an efficient scavenging pathway for Mn (II) in polluted water.

The spatial and temporal variation in passenger service rate and its impact on train dwell time: A time-series clustering approach using dynamic time warping

ABSTRACTThis study aims to improve the understanding of the underlying mechanism of passenger boarding and alighting processes, as well as its potential influence on train dwell time and train operation. Empirical data collected from one of busiest metro stations in Seoul, Korea, demonstrates the spatial and temporal variation in the passenger service rate, as a result of interference between boarding, alighting, and standing passengers. This study postulates that the level of interference can be associated with the train car occupancy and the proximity of train door to entry points, as waiting passengers tend to cluster near the platform entries. A unique temporal service rate curve is derived from each door location. We introduce Dynamic Time Warping for similarity assessment and clustering. It revealed four groups of train doors showing distinct shapes of curve from each platform. The first cluster includes the train doors located closest to the platform entry points where the initial service rate is drastically impeded by severe inference among passengers. The level of interference gradually diminishes as the door is located farther away from the entry points, but the overall service rate decreases as well. A passenger service time model is derived to include the cluster variable. To test its significance, the prediction capability of the model is presented with and without the cluster variable. The results of this study may be used to guide waiting passengers along the platform to minimize interference and to avoid serious disruption during passenger service time.

Breakthrough Curve Analysis of Enteromorpha prolifera Packed Fixed-Bed Column for the Biosorption

Abstract A continuous fixed-bed study was carried out utilizing Enteromorpha prolifera (EP) biosorbent for removing methylene blue (MB) from aqueous solution. Effect of operating conditions such as bed depth, influent flow rate, pH, MB initial concentration, and column shape were investigated. Results confirmed that excellent sorption is a neutral condition of MB at appropriate flow rate (2 mL/min), and maximum dynamic adsorption capacity of EP for MB was estimated to be 348.06 mg/g. The Thomas and Yoon–Nelson models both described the entire breakthrough curve well at all experimental conditions, while Bohart–Adams and Bed Depth Service Time (BDST) models were only suitable for an initial part of dynamic behavior of the column. Regeneration of the column was conducted by using 1 M NaCl solution as an eluent. Dipole–dipole interactions and the hydrogen bonding were proposed to interpret the mechanisms of the observed biosorption.

Recent Modeling and Analytical Advances in Hospital Inpatient Flow Management

Inpatient flow management plays a critical role in efficient care delivery, patient outcomes, and hospital operational and financial costs. Modeling and performance analysis of inpatient flow present unique features and challenges that differ from operations in other service industries. In this paper, we review recent modeling and analytical advances in the setting of inpatient flow management, with a particular focus on service time models motivated from the observations of inpatient discharges. We first compare two new service time models developed to capture the time-of-day inpatient flow dynamics and reveal interesting connections between the two models. We then review analytical methods developed to analyze systems with the new service time models. Based on one method, which is amenable to a one-dimensional exact analysis under certain conditions, we further introduce its approximations that have explicit analytical forms and enable efficient computations in large systems. In particular, we showcase how to leverage a powerful tool, the Stein's method framework, in the hospital setting for steady-state approximations and characterizing error bounds. We conclude the paper by a literature review on other important aspects in inpatient flow management and propose future research directions, from both the modeling and analytical perspectives.

RF-Spectrum Opportunities for Cognitive Radio Networks Operating Over GSM Channels

In this paper, we characterize the radio frequency spectrum opportunities available in a common global system for mobile communications (GSM) channel to support the operation of a cognitive radio network (CRN). In a first step, we describe the technical details involved to sample the channel using a software defined radio device. Adopting a simple energy-based detector, we identify the two energy regions where the GSM system is active or inactive and evaluate the spectrum sensing accuracy. Based on the output of the detector, we show that the distribution of the durations of busy and idle periods are approximated by geometric distributions. Finally, we validate a theoretical model for the distribution of the service time. The validation results indicate that the service time can be successfully represented by a discrete generalized Pareto distribution, which is confirmed by the Kolmogorov–Smirnov test. Because the throughput of the CRN is represented by the inverse of the service time, the proposed analysis provides an upper bound for the networks’ throughput, indicating the maximum throughput that can be attained when a single secondary user transmits over a GSM cellular channel. The results presented in this paper are validated with real data, confirming the accuracy of the proposed service time model.