Search results for: uniform error

Authors: Zayed Alsulami, Asma Aldosseri, Ahmed Ezziden, Abdulrahman Alonazi

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Children are more susceptible to medication errors than adults. Medication administration process is the last stage in the medication treatment process and most of the errors detected in this stage. Little research has been undertaken about medication errors in children in the Middle East countries. This study was aimed to evaluate how the paediatric nurses adhere to the medication administration policy and also to identify any medication preparation and administration errors or any risk factors. An observational, prospective study of medication administration process from when the nurses preparing patient medication until administration stage (May to August 2014) was conducted in Saudi Arabia. Twelve paediatric nurses serving 90 paediatric patients were observed. 456 drug administered doses were evaluated. Adherence rate was variable in 7 steps out of 16 steps. Patient allergy information, dose calculation, drug expiry date were the steps in medication administration with lowest adherence rates. 63 medication preparation and administration errors were identified with error rate 13.8% of medication administrations. No potentially life-threating errors were witnessed. Few logistic and administrative factors were reported. The results showed that the medication administration policy and procedure need an urgent revision to be more sensible for nurses in practice. Nurses’ knowledge and skills regarding the medication administration process should be improved.

Keywords: medication sasfety, paediatric, medication errors, paediatric ward

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Authors: Apoorva Bamal, Agnieszka Indiana Olbert

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Floods are known to be one of the most devastating hydro-climatic events, impacting a wide range of stakeholders in terms of environmental, social and economic losses. With difference in inundation durations and level of impact, flood hazards are of different degrees and strength. Amongst various set of domains being impacted by floods, environmental degradation in terms of water quality deterioration is one of the majorly effected but less highlighted domains across the world. The degraded water quality is caused by numerous natural and anthropogenic factors that are both point and non-point sources of pollution. Therefore, it is essential to understand the nature and source of the water pollution due to flooding. The major impact of floods is not only on the physico-chemical water quality parameters, but also on the biological elements leading to a vivid influence on the aquatic ecosystem. This deteriorated water quality is impacting many water categories viz. agriculture, drinking water, aquatic habitat, and miscellaneous services requiring an appropriate water quality to survive. This study identifies, reviews, evaluates and assesses multiple researches done across the world to determine the impact of floods on water quality. With a detailed statistical analysis of top relevant researches, this study is a synopsis of the methods used in assessment of impact of floods on water quality in different geographies, and identifying the gaps for further abridgement. As per majority of the studies, different flood magnitudes have varied impact on the water quality parameters leading to either increased or decreased values as compared to the recommended values for various categories. There is also an evident shift of the biological elements in the impacted waters leading to a change in its phenology and inhabitants of the specified water body. This physical, chemical and biological water quality degradation by floods is dependent upon its duration, extent, magnitude and flow direction. Therefore, this research provides an overview into the multiple impacts of floods on water quality, along with a roadmap of way forward to an efficient and uniform linkage of floods and impacted water quality dynamics.

Keywords: floods, statistical analysis, water pollution, water quality

Procedia PDF Downloads 81

Authors: Alexandra Papagianni, George Filis, Panagiotis Papadopoulos

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The liberalization of the energy market and the increasing penetration of fluctuating renewables (e.g., wind and solar power) have heightened the importance of the spot market for ensuring efficient electricity supply. This is further emphasized by the EU’s goal of achieving net-zero emissions by 2050. The day-ahead market (DAM) plays a key role in European energy trading, accounting for 80-90% of spot transactions and providing critical insights for next-day pricing. Therefore, short-term electricity price forecasting (EPF) within the DAM is crucial for market participants to make informed decisions and improve their market positioning. Existing literature highlights out-of-sample performance as a key factor in assessing EPF accuracy, with influencing factors such as predictors, forecast horizon, model selection, and strategy. Several studies indicate that electricity demand is a primary price determinant, while renewable energy sources (RES) like wind and solar significantly impact price dynamics, often lowering prices. Additionally, incorporating data from neighboring countries, due to market coupling, further improves forecast accuracy. Most studies predict up to 24 steps ahead using hourly data, while some extend forecasts using higher-frequency data (e.g., half-hourly or quarter-hourly). Short-term EPF methods fall into two main categories: statistical and computational intelligence (CI) methods, with hybrid models combining both. While many studies use advanced statistical methods, particularly through different versions of traditional AR-type models, others apply computational techniques such as artificial neural networks (ANNs) and support vector machines (SVMs). Recent research combines multiple methods to enhance forecasting performance. Despite extensive research on EPF accuracy, a gap remains in understanding how forecasting strategy affects prediction outcomes. While iterated strategies are commonly used, they are often chosen without justification. This paper contributes by examining whether the choice of forecasting strategy impacts the quality of day-ahead price predictions, especially for multi-step forecasts. We evaluate both iterated and direct methods, exploring alternative ways of conducting iterated forecasts on benchmark and state-of-the-art forecasting frameworks. The goal is to assess whether these factors should be considered by end-users to improve forecast quality. We focus on the Greek DAM using data from July 1, 2021, to March 31, 2022. This period is chosen due to significant price volatility in Greece, driven by its dependence on natural gas and limited interconnection capacity with larger European grids. The analysis covers two phases: pre-conflict (January 1, 2022, to February 23, 2022) and post-conflict (February 24, 2022, to March 31, 2022), following the Russian-Ukraine conflict that initiated an energy crisis. We use the mean absolute percentage error (MAPE) and symmetric mean absolute percentage error (sMAPE) for evaluation, as well as the Direction of Change (DoC) measure to assess the accuracy of price movement predictions. Our findings suggest that forecasters need to apply all strategies across different horizons and models. Different strategies may be required for different horizons to optimize both accuracy and directional predictions, ensuring more reliable forecasts.

Keywords: short-term electricity price forecast, forecast strategies, forecast horizons, recursive strategy, direct strategy

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Authors: S. Deswal, M. Pal

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The paper aims to compare the performance of vertical and inclined multiple plunging jets and to model and predict their mass transfer capacity by multi-linear regression based approach. The multiple vertical plunging jets have jet impact angle of θ = 90O; whereas, multiple inclined plunging jets have jet impact angle of θ = 600. The results of the study suggests that mass transfer is higher for multiple jets, and inclined multiple plunging jets have up to 1.6 times higher mass transfer than vertical multiple plunging jets under similar conditions. The derived relationship, based on multi-linear regression approach, has successfully predicted the volumetric mass transfer coefficient (KLa) from operational parameters of multiple plunging jets with a correlation coefficient of 0.973, root mean square error of 0.002 and coefficient of determination of 0.946. The results suggests that predicted overall mass transfer coefficient is in good agreement with actual experimental values; thereby suggesting the utility of derived relationship based on multi-linear regression based approach and can be successfully employed in modelling mass transfer by multiple plunging jets.

Keywords: mass transfer, multiple plunging jets, multi-linear regression, earth sciences

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Authors: Milenko Košutić, Jelena Filipović, Zvonko Nježić

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Extrusion technology is thermal processing that is applied to improve the nutritional, hygienic, and physical-chemical characteristics of the raw material. Overall, the extrusion process is an efficient method for the production of a wide range of food products. It combines heat, pressure, and shear to transform raw materials into finished goods with desired textures, shapes, and nutritional profiles. The extruded products’ quality is remarkably dependent upon feed material composition, barrel temperature profile, feed moisture content, screw speed, and other extrusion system parameters. Given consumer expectations for snack foods, a high expansion index and low bulk density, in addition to crunchy texture and uniform microstructure, are desired. This paper investigates the effects of simultaneous different types of corn (white corn, yellow corn, red corn, and black corn) addition and different screw speed (350, 500, 650 rpm) on the physical, technological, and functional properties of flakes products. Black corn flour and screw speed at 350 rpm positively influenced physical, technological characteristics, mineral composition, and antioxidant properties of flake products with the best total score analysis of 0,59. Overall, the combination of Tukey's HSD test and PCA enables a comprehensive analysis of the observed corn products, allowing researchers to identify them. This research aims to analyze the influence of different types of corn flour (white corn, yellow corn, red corn, and black corn) on the nutritive and sensory properties of the product (quality, texture, and color), as well as the acceptance of the new product by consumers on the territory of Novi Sad. The presented data point that investigated corn flakes from black corn flour at 350 rpm is a product with good physical-technological and functional properties due to a higher level of antioxidant activity.

Keywords: corn types, flakes product, nutritive quality, acceptability

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Authors: M. Bodner, M. Scampicchio

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Fourier Transform Infrared (FT-IR) spectroscopy coupled with chemometrics was used to distinguish between butter samples and non-butter samples. Further, quantification of the content of margarine in adulterated butter samples was investigated. Fingerprinting region (1400-800 cm^–1) was used to develop unsupervised pattern recognition (Principal Component Analysis, PCA), supervised modeling (Soft Independent Modelling by Class Analogy, SIMCA), classification (Partial Least Squares Discriminant Analysis, PLS-DA) and regression (Partial Least Squares Regression, PLS-R) models. PCA of the fingerprinting region shows a clustering of the two sample types. All samples were classified in their rightful class by SIMCA approach; however, nine adulterated samples (between 1% and 30% w/w of margarine) were classified as belonging both at the butter class and at the non-butter one. In the two-class PLS-DA model’s (R² = 0.73, RMSEP, Root Mean Square Error of Prediction = 0.26% w/w) sensitivity was 71.4% and Positive Predictive Value (PPV) 100%. Its threshold was calculated at 7% w/w of margarine in adulterated butter samples. Finally, PLS-R model (R² = 0.84, RMSEP = 16.54%) was developed. PLS-DA was a suitable classification tool and PLS-R a proper quantification approach. Results demonstrate that FT-IR spectroscopy combined with PLS-R can be used as a rapid, simple and safe method to identify pure butter samples from adulterated ones and to determine the grade of adulteration of margarine in butter samples.

Keywords: adulterated butter, margarine, PCA, PLS-DA, PLS-R, SIMCA

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Authors: Jaskaran Singh Sidhu

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Aim: The purpose of this study is to find the relationship between wellness among sportsmen and non sportsmen. Methodology: The present study is an experimental study for 80 senior secondary volleyball players of 16-19 years of age from Ludhiana District of Punjab (India), and 80 non-sportsperson were taken from senior secondary school of Ludhiana district. The sample for this study was taken through a random sampling technique. Tools: A five point scale havinf 50 items was used to acess the wellness Statistical Analysis: To find out the relationship among the variables exists or not, a t-test was used to test the significance of the difference between the means. Statistics for each characteristic were calculated; Mean, Standard deviation, Standard error of Mean. Data were analyzed using SPSS (statistical package for the social sciences). Statistical significance was set at p < 0.05. Results: Substantial deviations were noted at p<0.5 in the totality of wellness. Sportsmen show significant differences exist at p<0.5 in three parameters of wellness i.e., physical wellness, mental wellness, and social wellness. In spiritual and emotional wellness attributes, non-sportsmen shows significant difference at p<0.5. Conclusion: From the data interpretation it reflects that overall wellness can be improved by participation in sports. It further noted in study that participation in sports promote the attributes of wellness i.e., physical wellness, mental wellness, emotional wellness and social wellness.

Keywords: physical, mental, social, emotional, wellness, spiritual

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Authors: Ghaem Zamani, Farveh Aghaye Nezhad, Amin Barari

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The installation process of caissons has usually been a challenging step in the design phase, especially in the case of suction-assisted installation. The engineering practice for estimating the caisson penetration resistance is primarily controlled by the resistance governed by inner and outer skirt friction and the tip resistance. Different methods have been proposed in the literature to evaluate the above components, while the CPT-based methodology has attained notable popularity among others. In this method, two empirical coefficients are suggested, k𝒻 and kp, which relate the frictional resistance and tip resistance to the cone penetration resistance (q𝒸), respectively. A series of jacking installation and uninstallation experiments for different soil densities were carried out in the offshore geotechnical laboratory of Aalborg University, Denmark. The main goal of these tests was to find appropriate values for empirical coefficients of the CPT-based method for the buckets with large embedment ratio (i.e., d/D=1, where d is the skirt length and D is the diameter) and increased tip area penetrated into dense sand deposits. The friction resistance effects were isolated during the pullout experiments; hence, the k𝒻 was back-measured from the tests in the absence of tip resistance. The actuator force during jacking installation equals the sum of frictional resistance and tip resistance. Therefore, the tip resistance of the bucket is calculated by subtracting the back-measured frictional resistance from penetration resistance; hence the relevant coefficient kp would be achieved. The cone penetration test was operated at different points before and after each installation attempt to measure the cone penetration resistance (q𝒸), and the average value of q𝒸 is used for calculations. The experimental results of the jacking installation tests indicated that a larger friction area considerably increased the penetration resistance; however, this effect was completely diminished when foundation suction-assisted penetration was used. Finally, the values measured for the empirical coefficient of the CPT-based method are compared with the highest expected and most probable values suggested by DNV(1992) for uniform thickness buckets.

Keywords: suction caisson, offshore geotechnics, cone penetration test, wind turbine foundation

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Authors: Bikram K. Das, Kalyan K. Chattopadhyay

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The advent of 2-D materials in the last decade has induced a fresh spur of growth in fuel cell technology as these materials have some highly promising traits that can be exploited to felicitate Oxygen Reduction Reaction (ORR) in an efficient way. Among the various 2-D carbon materials, graphyne (Gy) and graphdiyne (Gdy)1 with their intrinsic non-uniform charge distribution holds promises in this purpose and it is expected2 that substitutional Nitrogen (N) doping could further enhance their efficiency. In this regard, dispersive force corrected density functional theory is used to map the oxygen reduction reaction (ORR) kinetics of five different kinds of N doped graphyne and graphdiyne systems (namely αGy, βGy, γGy, RGy and 6,6,12Gy and Gdy) in alkaline medium. The best doping site for each of the Gy/ Gdy system is determined comparing the formation energies of the possible doping configurations. Similarly, the best di-oxygen (O₂) adsorption sites for the doped systems are identified by comparing the adsorption energies. O₂ adsorption on all N doped Gy/ Gdy systems is found to be energetically favorable. ORR on a catalyst surface may occur either via the Eley-Rideal (ER) or the Langmuir–Hinschelwood (LH) pathway. Systematic studies performed on the considered systems reveal that all of them favor the ER pathway. Further, depending on the nature of di-oxygen adsorption ORR can follow either associative or dissociative mechanism; the possibility of occurrence of both the mechanisms is tested thoroughly for each N doped Gy/ Gdy. For the ORR process, all the Gy/Gdy systems are observed to prefer the efficient four-electron pathway but the expected monotonically exothermic reaction pathway is found only for N doped 6,6,12Gy and RGy following the associative pathway and for N doped βGy, γGy and Gdy following the dissociative pathway. Further computation performed for these systems reveals that for N doped 6,6,12Gy, RGy, βGy, γGy and Gdy the overpotentials are 1.08 V, 0.94 V, 1.17 V, 1.21 V and 1.04 V respectively depicting N doped RGy is the most promising material, to carry out ORR in alkaline medium, among the considered ones. The stability of the ORR intermediate states with the variation of pH and electrode potentials is further explored with Pourbiax diagrams and the activities of these systems in the alkaline medium are compared with the prior reported B/N doped identical systems for ORR in an acidic medium in terms of a common descriptor.

Keywords: graphdiyne, graphyne, nitrogen-doped, ORR

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Authors: Pravin Kumar, Rajendra K. Singh, Prabhakar Singh

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A widespread research work on Mo-based double perovskite systems has been reported as a potential application for electrode materials of solid oxide fuel cells. Mo-based double perovskites studied in form of B-site ordered double perovskite materials, with general formula A₂B′B″O₆ structured by alkaline earth element (A = Sr, Ca, Ba) and heterovalent transition metals (B′ = Fe, Co, Ni, Cr, etc. and B″ = Mo, W, etc.), are raising a significant interest as potential mixed ionic-electronic conductors in the temperature range of 500-800 °C. Such systems reveal higher electrical conductivity, particularly those assigned in form of Sr₂CoMoO₆₋δ (M = Mg, Mn, Fe, Co, Ni, Zn etc.) which were studied in different environments (air/H₂/H₂-Ar/CH₄) at an intermediate temperature. Among them, the Sr₂CoMoO₆₋δ system is a potential candidate as an anode material for solid oxide fuel cells (SOFCs) due to its better electrical conductivity. Therefore, Sr₂CoMoO₆₋δ (SCM) system with La-doped on Sr site has been studied to discover the structural and electrical properties. The double perovskite system Sr₂CoMoO₆₋δ (SCM) and doped system Sr₂-ₓLaₓCoMoO₆₋δ (SLCM, x=0.04) were synthesized by the citrate-nitrate combustion synthesis route. Thermal studies were carried out by thermo-gravimetric analysis. Phase justification was confirmed by powder X-ray diffraction (XRD) as a tetragonal structure with space group I4/m. A minor phase of SrMoO₄ (s.g. I41/a) was identified as a secondary phase using JCPDS card no. 85-0586. Micro-structural investigations revealed the formation of uniform grains. The average grain size of undoped (SCM) and doped (SLCM) compositions was calculated by a linear intercept method and found to be ⁓3.8 μm and 2.7 μm, respectively. The electrical conductivity of SLCM is found higher than SCM in the air within the temperature range of 200-600 °C. SLCM system was also measured in reducing atmosphere (pure H₂) in the temperature range 300-600 °C. SLCM has been showed the higher conductivity in the reducing atmosphere (H₂) than in air and therefore it could be a promising anode material for SOFCs.

Keywords: double perovskite, electrical conductivity, SEM, XRD

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Authors: Lamla Thungathaa, Conrad Mahlasea, Lisa Ngcebesha

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1,4-Diamino-3,6-dinitropyrazolo[4,3-c]pyrazole (LLM-119) and its structural isomer 3,6-dinitropyrazolo[3,4-c]pyrazole-1,4(6H)-diamine were designed by structural reorientation of the fused pyrazole rings and their respective substituents (-NO2 and -NH2). Structural reorientation involves structural rearrangement which result in different structural isomers, employing this approach, six structural isomers of LLM-119 were achieved. The effect of structural reorientation (isomerisation and derivatives) on the enthalpy of formation, detonation properties, impact sensitivity, and density of these molecules is studied Computationally. The computational method used are detailed in the document and they yielded results that are close to the literature values with a relative error of 2% for enthalpy of formation, 2% for density, 0.05% for detonation velocity, and 4% for detonation pressure. The correlation of the structural reorientation to the calculated thermochemical and detonation properties of the molecules indicated that molecules with a -NO2 group attached to a Carbon atom and -NH2 connected to a Nitrogen atom maximize the enthalpy of formation and detonation velocity. The joining of pyrazole molecules has less effect on these parameters. It was seen that density and detonation pressure improved when both –NO2 or -NH2 functional groups were on the same side of the molecular structure. The structural reorientation gave rise to 3,4-dinitropyrazolo[3,4-c]pyrazole-1,6-diamine which exhibited optimal density and detonation performance compared to other molecules.

Keywords: LLM-119, fused rings, azole, structural isomers, detonation properties

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Authors: Cameron Hamilton, Walter Potter, Gerrit Hoogenboom, Ronald McClendon, Will Hobbs

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A model was constructed to predict the amount of solar radiation that will make contact with the surface of the earth in a given location an hour into the future. This project was supported by the Southern Company to determine at what specific times during a given day of the year solar panels could be relied upon to produce energy in sufficient quantities. Due to their ability as universal function approximators, an artificial neural network was used to estimate the nonlinear pattern of solar radiation, which utilized measurements of weather conditions collected at the Griffin, Georgia weather station as inputs. A number of network configurations and training strategies were utilized, though a multilayer perceptron with a variety of hidden nodes trained with the resilient propagation algorithm consistently yielded the most accurate predictions. In addition, a modeled DNI field and adjacent weather station data were used to bolster prediction accuracy. In later trials, the solar radiation field was preprocessed with a discrete wavelet transform with the aim of removing noise from the measurements. The current model provides predictions of solar radiation with a mean square error of 0.0042, though ongoing efforts are being made to further improve the model’s accuracy.

Keywords: artificial neural networks, resilient propagation, solar radiation, time series forecasting

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Authors: Imene Skhakhfa, Lahbaci Ouerdachi

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To ensure the overall coherence of simulated results, it is necessary to develop a robust validation process. In many applications, it is no longer content to calibrate and validate the model only in relation to the hydro graph measured at the outlet, but we try to better simulate the functioning of the watershed in space. Therefore the timing also performs compared to other variables such as water level measurements in intermediate stations or groundwater levels. As part of this work, we limit ourselves to modeling flood of short duration for which the process of evapotranspiration is negligible. The main parameters to identify the models are related to the method of unit hydro graph (HU). Three different models were tested: SNYDER, CLARK and SCS. These models differ in their mathematical structure and parameters to be calibrated while hydrological data are the same, the initial water content and precipitation. The models are compared on the basis of their performance in terms six objective criteria, three global criteria and three criteria representing volume, peak flow, and the mean square error. The first type of criteria gives more weight to strong events whereas the second considers all events to be of equal weight. The results show that the calibrated parameter values are dependent and also highlight the problems associated with the simulation of low flow events and intermittent precipitation.

Keywords: model calibration, intensity, runoff, hydrograph

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Authors: Yongrong Li, Ralf Domroes

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Due to significant energy savings, enablement of higher machining speed as well as environmentally friendly features, Minimum Quantity Lubrication (MQL) has been used for many machining processes efficiently. However, in the deep hole drilling field (small tool diameter D < 5 mm) and long tool (length L > 25xD) it is always a bottle neck for a single channel MQL system. The single channel MQL, based on the Venturi principle, faces a lack of enough oil quantity caused by dropped pressure difference during the deep hole drilling process. In this paper, a system concept based on a bypass design has explored its possibility to dynamically reach the required pressure difference between the air inlet and the inside of aerosol generator, so that the deep hole drilling demanded volume of oil can be generated and delivered to tool tips. The system concept has been investigated in static and dynamic laboratory testing. In the static test, the oil volume with and without bypass control were measured. This shows an oil quantity increasing potential up to 1000%. A spray pattern test has demonstrated the differences of aerosol particle size, aerosol distribution and reaction time between single channel and bypass controlled single channel MQL systems. A dynamic trial machining test of deep hole drilling (drill tool D=4.5mm, L= 40xD) has been carried out with the proposed system on a difficult machining material AlSi7Mg. The tool wear along a 100 meter drilling was tracked and analyzed. The result shows that the single channel MQL with a bypass control can overcome the limitation and enhance deep hole drilling with a small tool. The optimized combination of inlet air pressure and bypass control results in a high quality oil delivery to tool tips with a uniform and continuous aerosol flow.

Keywords: deep hole drilling, green production, Minimum Quantity Lubrication (MQL), near dry machining

Procedia PDF Downloads 205

Authors: Mariana Mangas, Yaroslava Martins, M. Suárez, Célia Santos, Ana Matos Pires

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Baixo Alentejo is a region of Portugal characterized by an aging population, geographic isolation, social deprivation and a lack of medical staff. It is one of the most problematic regions in regards to mental health, particularly due to the factors mentioned. The aim of this study is a presentation of liaison psychiatry in Hospital José Joaquim Fernandes; a sample of the work done, the current situation and future perspectives. The aim is to present a retrospective study of internal psychiatric emergencies from January 1st, 2016 to August 31st, 2016. Liaison psychiatry of Department of Psychiatry and Mental Health (Psychiatry Service) of ULSBA includes the following activities: internal psychiatry emergencies, HIV consultation (comprised in the general consultation) and liaison psychology (oncology and pain), consisting of a total of 111 internal psychiatry emergencies during the identified period. Gender distribution was uniform. The most prevalent age group was 71-80 years, and 66,6% of patients were 60 years old and over. The majority of the emergency observations was requested by hospital services of medicine (56,8%) and surgery (24,3%). The most frequent reasons for admission were: respiratory disease (18,0%); tumors (15.3%); other surgical and orthopedic pathology (14,5%) and stroke (11,7%). The most frequent psychiatric diagnoses were: neurotic and organic depression (24,3%); delirium (26,1%) and adjustment reaction (14,5%). Major psychiatric pathology (schizophrenia and affective disorders) was found in 10,8%. Antidepressive medication was prescribed in 37,8% patients; antipsychotics in 34,2%. In 9.9% of the cases, no psychotropic drug was prescribed, and 5,4% of patients received psychologic support. Regarding hospital discharge, 42,4% of patients were referred to the general practitioner or to the medical specialist; 22,5% to outpatient gerontopsychiatry; 17,1% to psychiatric outpatient and 14,4% deceased. A future perspective is to start liaison in areas of HIV and psycho oncology in multidisciplinary approach and to improve collaboration with colleagues of other specialties for refining psychiatric referrals.

Keywords: psychiatry, liaison, internal emergency, psychiatric referral

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Authors: Olaiya Folorunsho, Comfort Y. Daramola, Joel N. Ugwu, Lawrence B. Adewole, Olufisayo S. Ekundayo

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In today world, there is a tremendous rise in the usage of internet due to the fact that almost all the communication and information sharing is done over the web. Conversely, there is a continuous growth of unauthorized access to confidential data. This has posed a challenge to information security expertise whose major goal is to curtail the menace. One of the approaches to secure the safety delivery of data/information to the rightful destination without any modification is steganography. Steganography is the art of hiding information inside an embedded information. This research paper aimed at designing a secured algorithm with the use of image steganographic technique that makes use of Least Significant Bit (LSB) algorithm for embedding the data into the bit map image (bmp) in order to enhance security and reliability. In the LSB approach, the basic idea is to replace the LSB of the pixels of the cover image with the Bits of the messages to be hidden without destroying the property of the cover image significantly. The system was implemented using C# programming language of Microsoft.NET framework. The performance evaluation of the proposed system was experimented by conducting a benchmarking test for analyzing the parameters like Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The result showed that image steganography performed considerably in securing data hiding and information transmission over the networks.

Keywords: steganography, image steganography, least significant bits, bit map image

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Authors: Lotfi Farah, Nadir Farah, Zaiem Kamar

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This paper achieves a maximum power point tracking (MPPT) controller using a high-efficiency reduced rules neuro-fuzzy inference system (HE2RNF) for a 100 kW stand-alone photovoltaic (PV) system connected to the grid. The suggested HE2RNF based MPPT seeks the optimal duty cycle for the boost DC-DC converter, making the designed PV system working at the maximum power point (MPP), then transferring this power to the grid via a three levels voltage source converter (VSC). PV current variation and voltage variation are chosen as HE2RNF-based MPPT controller inputs. By using these inputs with the duty cycle as the only single output, a six rules ANFIS is generated. The high performance of the proposed HE2RNF numerically in the MATLAB/Simulink environment is shown. The 0.006% steady-state error, 0.006s of tracking time, and 0.088s of starting time prove the robustness of this six reduced rules against the widely used twenty-five ones.

Keywords: PV, MPPT, ANFIS, HE2RNF-based MPPT controller, VSC, grid connection

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Authors: Jihad S. Daba, J. P. Dubois, Yvette Antar

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With the exponential growth of cellular users, a new generation of cellular networks is needed to enhance the required peak data rates. The co-channel interference between neighboring base stations inhibits peak data rate increase. To overcome this interference, multi-cell cooperation known as coordinated multipoint transmission is proposed. Such a solution makes use of multiple-input-multiple-output (MIMO) systems under two different structures: Micro- and macro-diversity. In this paper, we study the capacity and bit error rate in cellular networks using MIMO technology. We analyse both micro- and macro-diversity schemes and develop a hybrid model that switches between macro- and micro-diversity in the case of hard handoff based on a cut-off range of signal-to-noise ratio values. We conclude that our hybrid switched micro-macro MIMO system outperforms classical MIMO systems at the cost of increased hardware and software complexity.

Keywords: cooperative multipoint transmission, ergodic capacity, hard handoff, macro-diversity, micro-diversity, multiple-input-multiple output systems, orthogonal frequency division multiplexing

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Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

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Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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Authors: Qasem Qananwah, Ahmad Dagamseh, Hiam AlQuran, Khalid Shaker Ibrahim

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Blood pressure helps the physicians greatly to have a deep insight into the cardiovascular system. The determination of individual blood pressure is a standard clinical procedure considered for cardiovascular system problems. The conventional techniques to measure blood pressure (e.g. cuff method) allows a limited number of readings for a certain period (e.g. every 5-10 minutes). Additionally, these systems cause turbulence to blood flow; impeding continuous blood pressure monitoring, especially in emergency cases or critically ill persons. In this paper, the most important statistical features in the photoplethysmogram (PPG) signals were extracted to estimate the blood pressure noninvasively. PPG signals from more than 40 subjects were measured and analyzed and 12 features were extracted. The features were fed to principal component analysis (PCA) to find the most important independent features that have the highest correlation with blood pressure. The results show that the stiffness index means and standard deviation for the beat-to-beat heart rate were the most important features. A model representing both features for Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP) was obtained using a statistical regression technique. Surface fitting is used to best fit the series of data and the results show that the error value in estimating the SBP is 4.95% and in estimating the DBP is 3.99%.

Keywords: blood pressure, noninvasive optical system, principal component analysis, PCA, continuous monitoring

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Authors: I. Wlasny, Z. Klusek, A. Wysmolek

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Hexagonal boron nitride is a representative of a widely popular class of two-dimensional Van Der Waals materials. It finds its uses, among others, in construction of complexly layered heterostructures. Hexagonal boron nitride attracts great interest because of its properties characteristic for wide-gap semiconductors as well as an ultra-flat surface.Van Der Waals heterostructures composed of two-dimensional layered materials, such as transition metal dichalcogenides or graphene give hope for miniaturization of various electronic and optoelectronic elements. In our presentation, we will show the results of our investigations of the not previously reported modification of the hexagonal boron nitride layers with focused laser beam. The electrostatic force microscopy (EFM) images reveal that the irradiation leads to changes of the local electric fields for a wide range of laser wavelengths (from 442 to 785 nm). These changes are also accompanied by alterations of crystallographic structure of the material, as reflected by Raman spectra. They exhibit high stability and remain visible after at least five months. This behavior can be explained in terms of photoionization of the defect centers in h-BN which influence non-uniform electrostatic field screening by the photo-excited charge carriers. Analyzed changes influence local defect structure, and thus the interatomic distances within the lattice. These effects can be amplified by the piezoelectric character of hexagonal boron nitride, similar to that found in nitrides (e.g., GaN, AlN). Our results shed new light on the optical properties of the hexagonal boron nitride, in particular, those associated with electron-phonon coupling. Our study also opens new possibilities for h-BN applications in layered heterostructures where electrostatic fields can be used in tailoring of the local properties of the structures for use in micro- and nanoelectronics or field-controlled memory storage. This work is supported by National Science Centre project granted on the basis of the decision number DEC-2015/16/S/ST3/00451.

Keywords: atomic force microscopy, hexagonal boron nitride, optical properties, raman spectroscopy

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Authors: Sara Mahesar, Saleem M. Chandio, Hira Soomro

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Nonlinear system of equations in two variables is a system which contains variables of degree greater or equal to two or that comprises of the transcendental functions. Mathematical modeling of numerous physical problems occurs as a system of nonlinear equations. In applied and pure mathematics it is the main dispute to solve a system of nonlinear equations. Numerical techniques mainly used for finding the solution to problems where analytical methods are failed, which leads to the inexact solutions. To find the exact roots or solutions in case of the system of non-linear equations there does not exist any analytical technique. Various methods have been proposed to solve such systems with an improved rate of convergence and accuracy. In this paper, a new scheme is developed for solving system of non-linear equation in two variables. The iterative scheme proposed here is modified form of the conventional Newton’s Method (CN) whose order of convergence is two whereas the order of convergence of the devised technique is three. Furthermore, the detailed error and convergence analysis of the proposed method is also examined. Additionally, various numerical test problems are compared with the results of its counterpart conventional Newton’s Method (CN) which confirms the theoretic consequences of the proposed method.

Keywords: conventional Newton’s method, modified Newton’s method, order of convergence, system of nonlinear equations

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Authors: Swapneel U. Naphade, Dushyant A. Patil, Satyabodh M. Kulkarni

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In this work, we propose the concept and geometrical design of a soil moisture control system (SMCS) module by following the product development approach to develop an inexpensive, easy to use and quick to install product targeted towards agriculture practitioners. The module delivers water to the agricultural land efficiently by sensing the soil moisture and activating the delivery valve. We start with identifying the general needs of the potential customer. Then, based on customer needs we establish product specifications and identify important measuring quantities to evaluate our product. Keeping in mind the specifications, we develop various conceptual solutions of the product and select the best solution through concept screening and selection matrices. Then, we develop the product architecture by integrating the systems into the final product. In the end, the geometric design is done using human factors engineering concepts like heuristic analysis, task analysis, and human error reduction analysis. The result of human factors analysis reveals the remedies which should be applied while designing the geometry and software components of the product. We find that to design the best grip in terms of comfort and applied force, for a power-type grip, a grip-diameter of 35 mm is the most ideal.

Keywords: agriculture, human factors, product design, soil moisture control

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Authors: Nhan N. T. Ton, Anh T. N. Dao, Kouichirou Katou, Toshiaki Taniike

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Facile electron-hole recombination and the broad band gap are two major drawbacks of titanium dioxide (TiO₂) when applied in visible-light photocatalysis. Hybridization of TiO₂ with graphene is a promising strategy to lessen these pitfalls. Recently, there have been many reports on the synthesis of TiO₂/graphene nanocomposites, in most of which graphene oxide (GO) was used as a starting material. However, the reduction of GO introduced a large number of defects on the graphene framework. In addition, the sensitivity of titanium alkoxide to water (GO usually contains) significantly obstructs the uniform and controlled growth of TiO₂ on graphene. Here, we demonstrate a novel technique to synthesize TiO₂/graphene nanocomposites without the use of GO. Graphene dispersion was obtained through the chemical exfoliation of graphite in titanium tetra-n-butoxide with the aid of ultrasonication. The dispersion was directly used for the sol-gel reaction in the presence of different catalysts. A TiO₂/reduced graphene oxide (TiO₂/rGO) nanocomposite, which was prepared by a solvothermal method from GO, and the commercial TiO₂-P25 were used as references. It was found that titanium alkoxide afforded the graphene dispersion of a high quality in terms of a trace amount of defects and a few layers of dispersed graphene. Moreover, the sol-gel reaction from this dispersion led to TiO₂/graphene nanocomposites featured with promising characteristics for visible-light photocatalysts including: (I) the formation of a TiO₂ nano layer (thickness ranging from 1 nm to 5 nm) that uniformly and thinly covered graphene sheets, (II) a trace amount of defects on the graphene framework (low ID/IG ratio: 0.21), (III) a significant extension of the absorption edge into the visible light region (a remarkable extension of the absorption edge to 578 nm beside the usual edge at 360 nm), and (IV) a dramatic suppression of electron-hole recombination (the lowest photoluminescence intensity compared to reference samples). These advantages were successfully demonstrated in the photocatalytic decomposition of methylene blue under visible light irradiation. The TiO₂/graphene nanocomposites exhibited 15 and 5 times higher activity than TiO₂-P25 and the TiO₂/rGO nanocomposite, respectively.

Keywords: chemical exfoliation, photocatalyst, TiO₂/graphene, sol-gel reaction

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Authors: Ishapathik Das

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The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Keywords: model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs

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Authors: Alcardo Alex Barakabitze, Tan Xiaoheng

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Orthogonal Frequency Division Multiplexing (OFDM) is a special case of Multi-Carrier Modulation (MCM) technique which transmits a stream of data over a number of lower data rate subcarriers. OFDM splits the total transmission bandwidth into a number of orthogonal and non-overlapping subcarriers and transmit the collection of bits called symbols in parallel using these subcarriers. This paper explores the Peak to Average Power Reduction (PAPR) using the Partial Transmit Sequence technique. We provide the distribution analysis and the basics of OFDM signals and then show how the PAPR increases as the number of subcarriers increases. We provide the performance analysis of CCDF and PAPR expressed in decibels through MATLAB simulations. The simulation results show that, in PTS technique, the performance of PAPR reduction in OFDM systems improves significantly as the number of sub-blocks increases. However, by keeping the same number of sub-blocks variation, oversampling factor and the number of OFDM blocks’ iteration for generating the CCDF, the OFDM systems with 128 subcarriers have an improved performance in PAPR reduction compared to OFDM systems with 256, 512 or >512 subcarriers.

Keywords: OFDM, peak to average power reduction (PAPR), bit error rate (BER), subcarriers, wireless communications

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

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To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

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Authors: Jihad S. Daba, Jean-Pierre Dubois, Georges El Soury

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Fifth generation wireless networks guarantee significant capacity enhancement to suit more clients and services at higher information rates with better reliability while consuming less power. The deployment of massive multiple-input-multiple-output technology guarantees broadband wireless networks with the use of base station antenna arrays to serve a large number of users on the same frequency and time-slot channels. In this work, we evaluate the performance of massive multiple-input-multiple-output systems (MIMO) systems in 5^th generation cellular networks in terms of capacity and bit error rate. Several cases were considered and analyzed to compare the performance of massive MIMO systems while varying the number of antennas at both transmitting and receiving ends. We found that, unlike classical MIMO systems, reducing the number of transmit antennas while increasing the number of antennas at the receiver end provides a better solution to performance enhancement. In addition, enhanced orthogonal frequency division multiplexing and beam division multiple access schemes further improve the performance of massive MIMO systems and make them more reliable.

Keywords: beam division multiple access, D2D communication, enhanced OFDM, fifth generation broadband, massive MIMO

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Authors: Y. Kobori, S. Tanaka, N. Tsukiji, N. Takai, H. Kobayashi

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This paper proposes two kinds of new single-inductor dual-output (SIDO) DC-DC switching converters with ripple-based hysteretic control. First SIDO converters of type 1 utilize the triangular signal generated by the CR-circuit connected across the inductor. This triangular signal is used for generating the PWM signal instead of the saw-tooth signal used in the conventional converters. Second SIDO converters of type 2 utilize the triangular signal generated by the CR-circuit connected across the voltage error amplifier. This paper describes circuit topologies, Operation principles, simulation results and experimental results of the proposed SIDO converters. In simulation results of both type of SIDO converters, static output voltage ripples are less than 5mVpp and over/under shoots of the dynamic load regulations for the output current step are less than +/- 10mV. In experimental results of single output converter of type 2, static output voltage ripples are about 20mVpp. Output ripples of SIDO type 1 converter are about 80mVpp.

Keywords: DC-DC converter, switching converter, SIDO converter, hysteretic control, ripple-based control

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Authors: V. Pourmostaghimi, M. Zadshakoyan

Abstract:

Efficiency and productivity of the finish hard turning can be enhanced impressively by utilizing accurate predictive models for cutting tool wear. However, the ability of genetic programming in presenting an accurate analytical model is a notable characteristic which makes it more applicable than other predictive modeling methods. In this paper, the genetic equation for modeling of tool flank wear is developed with the use of the experimentally measured flank wear values and genetic programming during finish turning of hardened AISI D2. Series of tests were conducted over a range of cutting parameters and the values of tool flank wear were measured. On the basis of obtained results, genetic model presenting connection between cutting parameters and tool flank wear were extracted. The accuracy of the genetically obtained model was assessed by using two statistical measures, which were root mean square error (RMSE) and coefficient of determination (R²). Evaluation results revealed that presented genetic model predicted flank wear over the study area accurately (R² = 0.9902 and RMSE = 0.0102). These results allow concluding that the proposed genetic equation corresponds well with experimental data and can be implemented in real industrial applications.

Keywords: cutting parameters, flank wear, genetic programming, hard turning

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