bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adaptive PLS inferential soft sensor for continuous online estimation of NOx emission in industrial water-tube boiler
Authors: Hasnen S H , Zabiri H , Prakash K K , Mat T T 
Published: December 2019

Abstract
In common industrial application, the use of a linear and static PLS soft sensor for online prediction and monitoring of industrial boiler is often preferred due to its simple and intuitive framework. However, process dynamics and time-variant factors can negatively affect the accuracy and reliability of PLS soft sensor over its long-term application in process industries. In this paper, development of adaptive soft sensor based on dynamic PLS method has been applied to an industrial water-tube boiler for continuous online prediction of Nitric Oxides emission. In the case study, it is found that the adaptive PLS soft sensor which includes lagged measurements of NOx emission in the model input can significantly improve the prediction accuracy and reliability by 72.7% relative to the performance of linear and static PLS soft sensor when tested on online dataset containing gradual and abrupt changes in the process operating conditions.
Temperature control of vacuum dividing wall column – case study on oleochemical fatty acid fractionation
Authors: Alias A , Othman M R 
Published: December 2019

Abstract
Analysis of oleochemical compositions in distillation column often have large process delays. Inferential control is commonly used by means of stage temperature as the measured variable which provide more responsive in composition control. This work aims to evaluate the performance of temperature control in vacuum dividing wall column (VDWC) for fatty acid oleochemical fractionation. Product purity at 99% used as inferred parameter to determine the temperature. Sensitivity analysis was used to determine the relationship between stage and temperature difference for changes in the manipulated variables. The most sensitive tray was selected and implemented to a Distillate- Side Stream- Boilup (DSV) control configuration in Aspen Dynamics following the work by Othman (2019b). Controller adopted with PI and PID settings using Ziegler-Nichols (ZN) and Internal Model Control (IMC) tuning calculation method. Both methods were compared based on the settling time and overshoot. The best setting was then fine-tuned before tested to set point tracking without any disturbances. From the sensitive analysis, temperature at stage 6, 29 and 34 were selected used as controlled variable which inferred distillate, middle and bottom product purity at 99% respectively. PID controller setting based on ZN method provide the best setup with fastest settling time and smallest overshoot and provide good performance for set point tracking.
A kinetic model for the photocatalytic reduction of CO2 to methanol pathways
Authors: Abdullah H , Khan M M R , Yaakob Z , Ismail N A 
Published: December 2019

Abstract
Carbon dioxide (CO2) is one of the greenhouse gases that contribute to global warming. CO2 could be converted to valuable products such as hydrocarbons through the photocatalytic process. The aim of this research was to develop the kinetic model for the photocatalytic reduction of CO2 to methanol (CH3OH) in liquid phase reaction using cerium oxide-titanium dioxide (CeO2-TiO2) catalyst. The Langmuir-Hinshelwood approach was used in developing rate laws for the catalytic reaction using the catalytic reaction mechanism proposed. The catalytic reaction mechanism is about the adsorption of reactant (CO2 dissolved in the liquid phase), the reaction on catalyst surface and desorption of product. The experimental kinetic data were evaluated in the Polymath 6.1 software. In this study, two types of mechanism are proposed whereas one is considered the carbon monoxide (CO) oxidation while the other is not. Based on the model fitting, it was found that the model considers the CO oxidation is fitted well with the experimental data represents that the oxidation reaction of intermediate product, CO is the rate-determining step in the photocatalytic reduction of CO2 to CH3OH in liquid phase reaction.
Screening of the factors for novel pour point depressant copolymer synthesis to improve the copolymer yield
Authors: Elarbe B S , Ridzuan N , Yusoh K , Elganidi I , Abdullah N 
Published: December 2019

Abstract
Pour point depressants (PPDs) commonly used in the oil and gas industry as a chemical wax inhibitor to control the temperature of the crude oil below their wax appearance temperature (WAT) points, and to improve the flowability of crude oil. In this study, different conditions of Stearyl Acrylate-Behenyl Acrylate (SABA) copolymer were synthesized by free-radical solution polymerization method at different range conditions of polymerization. Four factors considered during the synthesize of the copolymer are the mass ratio of monomers (1:1, 1:2, 1:3, 2:1, and 3:1 wt%), reaction temperature from 60 to 100 °C, the concentration of initiator from 0.5 to 2.5 wt% and reaction time from 5 to 9 hour. The results showed that the best conditions to obtain the highest yield of SABA copolymer were at the mass ratio of monomers of 1:1 (w/w), the reaction temperature of 90 °C, the reaction time of 7 h, and concentration of initiator at 1 wt%.
Treatment of Palm Oil Mill Effluent (POME) using Membrane Anaerobic System (MAS)
Authors: Hybat M S , Abdurahman N H , Yasmeen Z H , Jemaat Z , Azhari N H 
Published: December 2019

Abstract
The directly discharged of Palm Oil Mill Effluent (POME) into the river causes environmental hazards due to the biochemical oxygen demand (BOD) and high Chemical Oxygen Demand (COD). The main issue of the traditional methods for POME treatment is that are not suitable for high suspended solid wastewaters and their gas production is less efficient at a high treatment volume. Therefore, in this study Membrane Anaerobic System (MAS) was used as alternative effective method for treating POME. The result obtained from the six steady states with concentration ranging from 11,048 to 15,700 mg/L mg/L for the MLSS, while the MLVSS recorded a concentration range between 10,540 and 17,600 mg/L. Moreover, the COD removal efficiency and HRT recorded from 94 to 97% and 150 to 10 days, respectively. Also, the coefficient of microorganism yield, decay rate, and the produced methane gas were obtained as 0.52g VSS/g COD, 0.31 day-1 and 0.182 to 0.564 l/g, respectively. Kinetic equations from Monod, Contois, and Chen, & Hashimoto were employed to describe the kinetics of POME treatment at organic loading rates ranging from 0.5 to 13 kg COD/m3/day. POME were characterized using Transform Infrared (FTIR) spectroscopy, in the regions of 900 to 1740 and 2800 to 3400 cm-1. Scanning Electron Microscope (SEM), the obtained result confirmed the potential of Membrane Anaerobic System (MAS) for the efficient treatment of POME effluent.
The efficiency of membrane anaerobic system (MAS) in treating sugarcane mill effluent (SCME)
Authors: Yasmeen Z H , Abdurahman N H , Hybat M S , Yunus R M 
Published: December 2019

AbstractIn recent times, the environmental issues have been on an alarming rate mostly for public authorities, societies, and industrial establishments. Sugarcane mill effluent (SCME) which contain high miscellaneous pollutants such as the chemical oxygen demand (COD), biological oxygen demand (BOD), total suspended solid (TSS) and the volatile suspended solid (VSS). However, the conventional method has the merit of COD reduction from SCME, but is limited in capturing the methane gas produced. In this study the membrane anaerobic system (MAS) was used as a cost-effective replacement method for treating SCME. In this study, six steady states were reached as part of the kinetic study with concentration ranging from 6312 to 14043 mg/l. for the mixed liquor suspended solids (MLSS) and 4790 to 12887 mg/l for mixed liquor volatile suspended solids (MLVSS). The three kinetic equations (Monod, Contois and Chen and Hashimoto) were used to explain the kinetics of SCME treatment at organic loading rates ranging from 0.5 to 13 kg COD/m3/day. The removal efficiency of COD was from 94.2% to 93.9% and produced methane gas (CH4) 75.4%. The scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectroscopy (SEM/EDX), and Fourier transforms infrared spectroscopy (FTIR) were subsequently used to quantitatively and qualitatively determine the content of the biomass before and after treatment.
Preparation and characterization of grease formulated from waste transformer oil
Authors: Mohd Sofi S N A , Abd Aziz M A , Anang Japar N S , Abdu Rahman N W , Abdulhalim A R , Mohd Yunus M Y 
Published: December 2019

Abstract
Grease is known as a lubricating material in a form of solid to semisolid mixture which is produced with the combination of base oil (80% - 95%), thickener (2% - 15%) and additive (0% - 10%). The limitation of soap grease performances as well as the volatile oil prices worldwide has led the interest in seeking alternative grease formulation. This research is focusing on the formulation of non-soap based grease from waste transformer oil (WTO) by two types of non-soap based thickeners, i.e. fumed silica and bentonite. The grease is prepared using different ratios of WTO and non-soap thickener ranging from 90:10 to 65:35. The physical and chemical properties of the formulated grease were evaluated using the ASTM International grease testing standard – for consistency and oil separation, and using the thermalgravimetric analyzer (TGA) and Fourier Transform Infrared Spectroscopy (FTIR) – for thermal stability and composition identification. It was found that the grease consistencies were directly proportional to the amount of thickener and the oil separated from the grease will affect the grease stability. Greases were found thermally stable at temperature as high as 150 °C. From the overall test, the best formulation was the grease formulated using bentonite with the ratio of 80:20 with NLGI grade 2 consistency.
Thermal stability of melt-blended poly (lactic acid) (PLA)/polyamide 66 (PA66)/graphene nanoplatelets (GnP)
Authors: Alhadadi W , Almaqtari A , Hafidzah F , Bijarimi M , Desa M S Z , Merzah H , Normaya E , Norazmi M 
Published: December 2019

Abstract
In recent times the blending of different biodegradable materials to produce nanocomposites with improved properties has been a significant point of discourse by many researchers. This study reports a melt blend of poly (lactic acid) (PLA), polyamide (Nylon 66) and graphene nanoplatelets (GnP). The thermal stability and chemical functional characteristics of the nanocomposites produced were succinctly investigated using thermogravimetric analysis (TGA), differential scanning calorimetry (DSC) and Fourier transform infrared (FTIR). The blending was carried out by using a twin-screw extruder at a revolution speed and time of 50 rpm and 20 minutes, respectively. The composition of GnP in the PLA/PA66 was varied from 0 – 5 wt.%. The results showed that the increased of the GnP concentrations improved the thermal stability of the nanocomposites. It was also observed that a strong interaction between the polymeric materials as demonstrated by the FTIR analysis. The use of a low concentration of graphene in PLA/PA66 blend has been demonstrated to improve the thermal stability of the nanocomposites.
24 fractional factorial design for PVDF/Pebax film composite synthesis on gas selectivity study
Authors: Abdul Wahab M S , Sunarti A R , Ramli N H , Ahmad A L 
Published: December 2019

Abstract
One of the key indicator for membrane film excellencies is by having a good ideal selectivity, and it is defined as the permeability ratio of two pure gases which be separated. This study focused on factors screening and interaction between involved factors in membrane film development on gas selectivity by employing 24 fractional factorial design (FFD). A total of four factors; Pebax concentration, bath temperature, evaporation times and quenching times were chosen to run simultaneously and ideal selectivity was chosen as a single respond. Order of contribution was found to be as follows; Pebax concentration > quenching times > bath temperature > evaporation times, while the most impacting factors towards gas selectivity was Pebax concentration (main effect), evaporation times - Pebax concentration (interaction effect), quenching times (main effect). The composite film produced via this design of experiment managed to obtain higher barrer of CO2 permeability of 393 and selectivity of 64.75. The outcome of the study indicates a very strong judgement in utilizing FFD to minimize and eliminate factors by considering the interaction among the factors involves in membrane film development for an ideal gas selectivity.
Modeling of vanillin adsorption from aqueous solution using resin H103 by artificial neural network
Authors: Chan W S , Samah R A , Zainol N , Fakharudin A S , Aziz S A , Phang L Y 
Published: December 2019

Abstract
Vanillin adsorption onto resin H103 was modelled using artificial neural network (ANN) approach and the best ANN algorithm was determined in this work. The first step of ANN modeling was ANN set up, followed by the optimization of ANN. The parameters for the input layers are contact time, initial vanillin concentration, resin dosage, pH, and temperature while the response is residual vanillin concentration. The neural network was trained using backpropagation (BP) algorithm. The result shows that the Levenberg–Marquardt algorithm was best suited the training function and the optimized ANN involved seven neurons at the hidden layer. This model can produce a correlation of determination value of 0.9999 with the mean square error (MSE) value of 0.0277. The best adsorption efficiencies for each factor were 98.11%, 96.03%, 98.14%, 98.2%, and 98.10% at 2.0 g of adsorbent dosage, 30 min of contact time, 100 mg/L of initial vanillin concentration, pH 5, and 25 °C, respectively. The outcomes of this work proved that ANN is excellent in predicting experimental data of vanillin adsorption by resin H103.
Integrated chemical, technology & equipment process knowledge management system based on risk based process safety
Authors: Anuar N I P , Aziz H A , Ahmad R 
Published: December 2019

Abstract
Major accidents in the industry such as fire, gas explosion, and unexpected toxic gas release are continuously reported worldwide. Lacking Process Knowledge Management (PKM) and failure to update and access the information was identified as one of the contributing factors. One of the established elements that intended to minimize this issue is PKM. However, lacking a systematic system to implement the PKM program has hindered the improvement of process safety level at workplace. The study focuses on development of PKMS database based on Risk Based Process Safety (RBPS) guideline. PKMS was developed by using Plan-Do-Check-Act (PDCA) concept. Validation of system was conducted through inserting real plant data from two chemical plants and feedback from process safety expert for further improvement. The developed PKMS allows the end user to store, review, modify and update the data regarding hazardous chemicals, technology and equipment information that involve with the operation. PKMS emphasis hazards related with the process in systematic ways thus minimizing potential incomplete control of hazard. PKMS interfaces allows management to do a self-check audit and helps the management to track the information. As leading indicator, PKMS allows the user to review overall status of the company compliance to the safety standard.
Psychological impact of noise exposure among machine and non-machine operators in construction industry
Authors: Kee H Y , Fauzan N S , Widia M 
Published: December 2019

Abstract
Noise hazard is reported as a serious issue among the construction industry in Malaysia. The aim of the study is to determine the personal noise exposure level and the prevalence of psychological health effect symptoms among the machine and non-machine operators on construction site in Malaysia. Sixty-one (61) construction workers were participated as respondents and categorized into machine and non-machine operators group. All respondents were monitored for 8 hours working time using personal noise dosimeter for personal noise monitoring. Questionnaires and interviewed sessions were used to determine the prevalence of psychological health effect symptoms. The results obtained reveal that the construction workers have high personal noise exposure level where machine operators are significantly higher compared to non-machine operators. The prevalence of psychological health effect symptoms among machine operators is 89% higher than the non-machine operators. Lastly, there is a significant positive relationship between the personal noise exposure level and the prevalence of psychological health effect symptoms among the construction workers.
Influence of natural smoke vent opening in stairway of multistorey building
Authors: Nurud S S , Saari M , Abdullah I , NorMariah A , Rafee B 
Published: December 2019

Abstract
Stairway used as an escape as well as firefighter’s route during evacuation. In addition, stairway connecting different floors of a building and becomes a path for the smoke spread in fire event. In a building, every escape route should be installed with smoke control system to ensure the prevention of dangerous smoke accumulation at those areas. The fire perimeter in terms of heat output and smoke generation is highly depends on building occupancy and the efficacy of smoke confinement may have a great challenge. In this paper, numerical simulations were conducted to study the efficacy of natural smoke vent to confine fire-induced smoke transportation in the stairways of multi-storeys buildings. The simulation used Fire Dynamic Simulator (FDS) was conducted on a full-scale building where the influences of smoke vent opening at different fire size were discussed. When the value of heat release rate (HRR) were kept constant, the different vent’s size opening had a different influence on the efficacy of smoke vent and an appropriate opening size was obtained and proposed for further action. The finding of this study can assist the fire engineer to ensure that the smoke vent installation play a good role in confinement of smoke diffusion.
LQG based control design of electric vehicle driveline
Authors: Akbar Zeeshan Ali , Mumtaz Fahad , Ullah Hameed , Asad Bashir Muhammad 
Published: December 2019

Abstract
In this paper LQG (Linear-Quadratic-Gaussian) based control design for drive line of Electric vehicle is presented. Driveline oscillations is a phenomenon of fluctuating vehicle speed caused by torsional vibrations in the vehicle drive line which results as jerks in the vehicle motion. These oscillations result in uncomfortable vehicle ride which is contemporary research problem. The control objective is to achieve steady state driveline in lesser time for this purpose LQG based control is pursued with certain modification in vehicle dynamic model. This paper includes driveline modelling, control design and verification by simulations. Results of simulation show the considerable mitigation of oscillations and LQG based control for driveline of electric vehicle works very well.
Obstacle detection using ultrasonic sensor for a mobile robot
Authors: Azeta Joseph , Bolu Christian , Hinvi Daniel , Abioye Abiodun A 
Published: December 2019

Abstract
There have been a number of successful attempts in designing obstacle avoiding robots. These works differ by selection of sensors, path mapping process and the algorithms applied to set the operational parameters. In this paper we present a los cost ultrasonic distance sensor for obstacle avoidance for mobile robot navigation. The system is implemented using microcontroller Arduino Uno, a Wi-Fi module, an Arduino motor shield driver which controls the robot through the geared dc motors. The system showed good performance under various lighting conditions. Experimental results with varied positions of obstacle show the flexibility of the robot to avoid it and have shown a decent performance in our laboratory. The robot is additionally ready to acknowledge victims before it, the sensing element system is extremely low-cost as a result of it solely uses one distance sensing element.
Finding verifying vertices of a coefficients polytope of characteristic polynomial for analyzing a robust oscillability of a control system with interval parameters
Authors: Khozhaev I V , Gayvoronskiy S A , Ezangina T A 
Published: December 2019

Abstract
The paper is dedicated to extending a root locus theory to systems with interval parameters, which are described with a characteristic polynomial with interval coefficients. On a basis of angular equation of a root locus a set of interval inequalities, including departure angles of root locus edge branches, determining oscillability degree of a control system, was derived. Solving the system of inequalities for low-order control systems resulted in a set of vertices of a characteristic polynomial coefficients polytope, projections of which on a complex plane determine an oscillability of such systems. Examples of application are provided.
Variability in Action Selection Relates to Striatal Dopamine 2/3 Receptor Availability in Humans: A PET Neuroimaging Study Using Reinforcement Learning and Active Inference Models
Authors: Adams Rick A , Moutoussis Michael , Nour Matthew M , Dahoun Tarik , Lewis Declan , Illingworth Benjamin , Veronese Mattia , Mathys Christoph , de Boer Lieke , Guitart-Masip Marc , Friston Karl J , Howes Oliver D , Roiser Jonathan P 
Published: December 2019

AbstractChoosing actions that result in advantageous outcomes is a fundamental function of nervous systems. All computational decision-making models contain a mechanism that controls the variability of (or confidence in) action selection, but its neural implementation is unclear—especially in humans. We investigated this mechanism using two influential decision-making frameworks: active inference (AI) and reinforcement learning (RL). In AI, the precision (inverse variance) of beliefs about policies controls action selection variability—similar to decision ‘noise’ parameters in RL—and is thought to be encoded by striatal dopamine signaling. We tested this hypothesis by administering a ‘go/no-go’ task to 75 healthy participants, and measuring striatal dopamine 2/3 receptor (D2/3R) availability in a subset (n = 25) using [11C]-(+)-PHNO positron emission tomography. In behavioral model comparison, RL performed best across the whole group but AI performed best in participants performing above chance levels. Limbic striatal D2/3R availability had linear relationships with AI policy precision (P = 0.029) as well as with RL irreducible decision ‘noise’ (P = 0.020), and this relationship with D2/3R availability was confirmed with a ‘decision stochasticity’ factor that aggregated across both models (P = 0.0006). These findings are consistent with occupancy of inhibitory striatal D2/3Rs decreasing the variability of action selection in humans.