Search results for: dimensional affect prediction

Authors: R. O. Osaseri, A. R. Usiobaifo

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The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: Ni̇sa Yeni̇kalayci, Türkan Aybi̇ke Akarca

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The ability of correlation the number and space relations, one of the basic scientific process skills, is being used in the transformation of a two-dimensional object into a three-dimensional image or in the expression of symmetry axes of the object. With this research, it is aimed to determine the ability of science students to establish number and space relations. The research was carried out with a total of 90 students studying in the first semester of the Science Education program of a state university located in the Turkey’s Black Sea Region in the fall semester of 2017-2018 academic year. An ‘Integrative Perception Test (IPT)’ was designed by the researchers to collect the data. Within the scope of IPT, the courses and workbooks specific to the field of science were scanned and the ones without symmetrical structure from the visual items belonging to the ‘Physics - Chemistry – Biology’ sub-fields were selected and listed. During the application, it was expected that students would imagine and draw images of the missing half of the visual items that were given incomplete in the first place. The data obtained from the test in which there are 30 images or pictures in total (f Physics = 10, f Chemistry = 10, f Biology = 10) were analyzed descriptively based on the drawings created by the students as ‘complete (2 points), incomplete/wrong (1 point), empty (0 point)’. For the teaching of new concepts in small aged groups, images or pictures showing symmetrical structures and similar applications can also be used.

Keywords: integrative perception, number and space relations, science education, scientific process skills

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Authors: Ahmad Fahim Nasiry, Shigeo Honma

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We examine two-dimensional oil displacement by water in a petroleum reservoir. The pore fluid is immiscible, and the porous media is homogenous and isotropic in the horizontal direction. Buckley-Leverett theory and a combination of Laplacian and Darcy’s law are used to study the fluid flow through porous media, and the Laplacian that defines the dispersion and diffusion of fluid in the sand using heavy oil is discussed. The reservoir is homogenous in the horizontal direction, as expressed by the partial differential equation. Two main factors which are observed are the water saturation and pressure distribution in the reservoir, and they are evaluated for predicting oil recovery in two dimensions by a physical and mathematical simulation model. We review the numerical simulation that solves difficult partial differential reservoir equations. Based on the numerical simulations, the saturation and pressure equations are calculated by the iterative alternating direction implicit method and the iterative alternating direction explicit method, respectively, according to the finite difference assumption. However, to understand the displacement of oil by water and the amount of water dispersion in the reservoir better, an interpolated contour line of the water distribution of the five-spot pattern, that provides an approximate solution which agrees well with the experimental results, is also presented. Finally, a computer program is developed to calculate the equation for pressure and water saturation and to draw the pressure contour line and water distribution contour line for the reservoir.

Keywords: numerical simulation, immiscible, finite difference, IADI, IDE, waterflooding

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Authors: Peng Hao Wang, Garam Kim, Ronald Sterkenburg

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In composite manufacturing, the fabrication of tooling and tooling maintenance contributes to a large portion of the total cost. However, as the applications of composite materials continue to increase, there is also a growing demand for more tooling. The demand for more tooling places heavy emphasis on the industry’s ability to fabricate high quality tools while maintaining the tool’s cost effectiveness. One of the popular techniques of tool fabrication currently being developed utilizes additive manufacturing technology known as 3D printing. The popularity of 3D printing is due to 3D printing’s ability to maintain low material waste, low cost, and quick fabrication time. In this study, a team of Purdue University School of Aviation and Transportation Technology (SATT) faculty and students investigated the effectiveness of a 3D printed composite mold. A steel valve cover from an aircraft reciprocating engine was modeled utilizing 3D scanning and computer-aided design (CAD) to create a 3D printed composite mold. The mold was used to fabricate carbon fiber versions of the aircraft reciprocating engine valve cover. The carbon fiber valve covers were evaluated for dimensional accuracy and quality while the 3D printed composite mold was evaluated for durability and dimensional stability. The data collected from this study provided valuable information in the understanding of 3D printed composite molds, potential improvements for the molds, and considerations for future tooling design.

Keywords: additive manufacturing, carbon fiber, composite tooling, molds

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Authors: Liang Wang, Beste F. Yuksel, David Guy Brizan

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A computational model of affect that can distinguish between spontaneous and posed smiles with no errors on a large, popular data set using deep learning techniques is presented in this paper. A Long Short-Term Memory (LSTM) classifier, a type of Recurrent Neural Network, is utilized and compared to human classification. Results showed that while human classification (mean of 0.7133) was above chance, the LSTM model was more accurate than human classification and other comparable state-of-the-art systems. Additionally, a high accuracy rate was maintained with small amounts of training videos (70 instances). The derivation of important features to further understand the success of our computational model were analyzed, and it was inferred that thousands of pairs of points within the eyes and mouth are important throughout all time segments in a smile. This suggests that distinguishing between a posed and spontaneous smile is a complex task, one which may account for the difficulty and lower accuracy of human classification compared to machine learning models.

Keywords: affective computing, affect detection, computer vision, deep learning, human-computer interaction, machine learning, posed smile detection, spontaneous smile detection

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Authors: Lebogang L. R. Mphahlele, Bruce B. Sithole

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Chicken meat is the highest consumed meat in south Africa, with a per capita consumption of >33 kg yearly. Hence, South Africa produces over 250 million kg of waste chicken feathers each year, the majority of which is landfilled or incinerated. The discarded feathers have caused environmental pollution and natural protein resource waste. Therefore, the valorisation of waste chicken feathers is measured as a more environmentally friendly and cost-effective treatment. Feather contains 91% protein, the main component being beta-keratin, a fibrous and insoluble structural protein extensively cross linked by disulfide bonds. Keratin is usually converted it into nanofibers via electrospinning for a variety of applications. keratin nanofiber composites have many potential biomedical applications for their attractive features, such as high surface-to-volume ratio and very high porosity. The application of nanofibers in the biomedical wound dressing requires antimicrobial properties for materials. One approach is incorporating inorganic nanoparticles, among which silver nanoparticles played an important alternative antibacterial agent and have been studied against many types of microbes. The objective of this study is to combine synthetic polymer, chicken feather keratin, and antibacterial nanoparticles to develop novel electrospun antibacterial nanofibrous composites for possible wound dressing application. Furthermore, this study will converting a two-dimensional electrospun nanofiber membrane to three-dimensional fiber networks that resemble the structure of the extracellular matrix (ECM)

Keywords: chicken feather keratin, nanofibers, nanoparticles, nanocomposites, wound dressing

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Authors: Wei Jun, Liao Hualin, Wang Huajian, Chen Jingkai, Liang Hongjun, Liu Chuanfu

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Kuqa Piedmont is rich in oil and gas resources and has great development potential in Tarim Basin, China. However, there is a huge thick gravel layer developed with high content, wide distribution and variation in size of gravel, leading to the condition of strong heterogeneity. So that, the drill string is in a state of severe vibration and the drill bit is worn seriously while drilling, which greatly reduces the rock-breaking efficiency, and there is a complex load state of impact and three-dimensional in-situ stress acting on the rock in the bottom hole. The dynamic mechanical properties and the influencing factors of conglomerate, the main component of gravel layer, are the basis of engineering design and efficient rock breaking method and theoretical research. Limited by the previously experimental technique, there are few works published yet about conglomerate, especially rare in dynamic load. Based on this, a kind of 3D SHPB system, three-dimensional prestress, can be applied to simulate the in-situ stress characteristics, is adopted for the dynamic test of the conglomerate. The results show that the dynamic strength is higher than its static strength obviously, and while the three-dimensional prestress is 0 and the loading strain rate is 81.25~228.42 s-1, the true triaxial equivalent strength is 167.17~199.87 MPa, and the strong growth factor of dynamic and static is 1.61~1.92. And the higher the impact velocity, the greater the loading strain rate, the higher the dynamic strength and the greater the failure strain, which all increase linearly. There is a critical prestress in the impact direction and its vertical direction. In the impact direction, while the prestress is less than the critical one, the dynamic strength and the loading strain rate increase linearly; otherwise, the strength decreases slightly and the strain rate decreases rapidly. In the vertical direction of impact load, the strength increases and the strain rate decreases linearly before the critical prestress, after that, oppositely. The dynamic strength of the conglomerate can be reduced properly by reducing the amplitude of impact load so that the service life of rock-breaking tools can be prolonged while drilling in the stratum rich in gravel. The research has important reference significance for the speed-increasing technology and theoretical research while drilling in gravel layer.

Keywords: huge thick gravel layer, conglomerate, 3D SHPB, dynamic strength, the deformation characteristics, prestress

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Authors: Silvia Arrate, Waldo Salud, Eloy París

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The wear of cutting tools is one of the most decisive elements when planning tunneling works, programming the maintenance stops and saving the optimum stock of spare parts during the evolution of the excavation. Being able to predict the behavior of cutting tools can give a very competitive advantage in terms of costs and excavation performance, optimized to the needs of the TBM itself. The incredible evolution of data science in recent years gives the option to implement it at the time of analyzing the key and most critical parameters related to machinery with the purpose of knowing how the cutting head is performing in front of the excavated ground. Taking this as a case study, Metro Line 3 of Guadalajara in Mexico will develop the feasibility of using Specific Energy versus data science applied over parameters of Torque, Penetration, and Contact Force, among others, to predict the behavior and status of cutting tools. The results obtained through both techniques are analyzed and verified in the function of the wear and the field situations observed in the excavation in order to determine its effectiveness regarding its predictive capacity. In conclusion, the possibilities and improvements offered by the application of digital tools and the programming of calculation algorithms for the analysis of wear of cutting head elements compared to purely empirical methods allow early detection of possible damage to cutting tools, which is reflected in optimization of excavation performance and a significant improvement in costs and deadlines.

Keywords: cutting tools, data science, prediction, TBM, wear

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Authors: Sophia Liang Zhou

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For investors, businesses, consumers, and governments, an accurate assessment of future housing prices is crucial to critical decisions in resource allocation, policy formation, and investment strategies. Previous studies are contradictory about macroeconomic determinants of housing price and largely focused on one or two areas using point prediction. This study aims to develop data-driven models to accurately predict future housing market trends in different markets. This work studied five different metropolitan areas representing different market trends and compared three-time lagging situations: no lag, 6-month lag, and 12-month lag. Linear regression (LR), random forest (RF), and artificial neural network (ANN) were employed to model the real estate price using datasets with S&P/Case-Shiller home price index and 12 demographic and macroeconomic features, such as gross domestic product (GDP), resident population, personal income, etc. in five metropolitan areas: Boston, Dallas, New York, Chicago, and San Francisco. The data from March 2005 to December 2018 were collected from the Federal Reserve Bank, FBI, and Freddie Mac. In the original data, some factors are monthly, some quarterly, and some yearly. Thus, two methods to compensate missing values, backfill or interpolation, were compared. The models were evaluated by accuracy, mean absolute error, and root mean square error. The LR and ANN models outperformed the RF model due to RF’s inherent limitations. Both ANN and LR methods generated predictive models with high accuracy ( > 95%). It was found that personal income, GDP, population, and measures of debt consistently appeared as the most important factors. It also showed that technique to compensate missing values in the dataset and implementation of time lag can have a significant influence on the model performance and require further investigation. The best performing models varied for each area, but the backfilled 12-month lag LR models and the interpolated no lag ANN models showed the best stable performance overall, with accuracies > 95% for each city. This study reveals the influence of input variables in different markets. It also provides evidence to support future studies to identify the optimal time lag and data imputing methods for establishing accurate predictive models.

Keywords: linear regression, random forest, artificial neural network, real estate price prediction

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Authors: Eric Mxolisi Mkhondo

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Geometrical deviations and interaction of mechanical parts influences the performance of miniature systems.These deviations tend to cause costly problems during assembly due to imperfections of components, which are invisible to a naked eye.They also tend to cause unsatisfactory performance during operation due to deformation cause by environmental conditions.One of the effective tools to manage the deviations and interaction of parts in the system is tolerance analysis.This is a quantitative tool for predicting the tolerance variations which are defined during the design process.Traditional tolerance analysis assumes that the assembly is static and the deviations come from the manufacturing discrepancies, overlooking the functionality of the whole system and deformation of parts due to effect of environmental conditions. This paper presents an integrated tolerance analysis approach for miniature system in operation.In this approach, a computer-aided design (CAD) model is developed from system’s specification.The CAD model is then used to specify the geometrical and dimensional tolerance limits (upper and lower limits) that vary component’s geometries and sizes while conforming to functional requirements.Worst-case tolerances are analyzed to determine the influenced of dimensional changes due to effects of operating temperatures.The method is used to evaluate the nominal conditions, and worse case conditions in maximum and minimum dimensions of assembled components.These three conditions will be evaluated under specific operating temperatures (-40°C,-18°C, 4°C, 26°C, 48°C, and 70°C). A case study on the mechanism of a zoom lens system is used to illustrate the effectiveness of the methodology.

Keywords: geometric dimensioning, tolerance analysis, worst-case analysis, zoom lens mechanism

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Authors: Erna Astuti, Supranto, Rochmadi, Agus Prasetya

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Biodiesel production from vegetable oil will produce glycerol as by-product about 10% of the biodiesel production. The amount of glycerol that was produced needed alternative way to handling immediately so as to not become the waste that polluted environment. One of the solutions was to process glycerol to polyglycidyl nitrate (PGN). PGN is synthesized from glycerol by three-step reactions i.e. nitration of glycerol, cyclization of 13- dinitroglycerine and polymerization of glycosyl nitrate. Optimum condition of nitration of glycerol with nitric acid has not been known. Thermodynamic feasibility should be done before run experiments in the laboratory. The aim of this study was to determine the parameters those affect nitration of glycerol and nitric acid and chose the operation condition. Many parameters were simulated to verify its possibility to experiment under conditions which would get the highest conversion of 1, 3-dinitroglycerine and which was the ideal condition to get it. The parameters that need to be studied to obtain the highest conversion of 1, 3-dinitroglycerine were mol ratio of nitric acid/glycerol, reaction temperature, mol ratio of glycerol/dichloromethane and pressure. The highest conversion was obtained in the range of mol ratio of nitric acid /glycerol between 2/1 – 5/1, reaction temperature of 5-25o C and pressure of 1 atm. The parameters that need to be studied further to obtain the highest conversion of 1.3 DNG are mol ratio of nitric acid/glycerol and reaction temperature.

Keywords: Nitration, glycerol, thermodynamic, optimum condition

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Authors: Ahmed Z. Mazen, Nejat Rahmanian, Iqbal Mujtaba, Ali Hassanpour

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In oil and gas well drilling, the drill bit is an important part of the Bottom Hole Assembly (BHA), which is installed and designed to drill and produce a hole by several mechanisms. The efficiency of the bit depends on many drilling parameters such as weight on bit, rotary speed, and mud properties. When the bit is pulled out of the hole, the evaluation of the bit damage must be recorded very carefully to guide engineers in order to select the bits for further planned wells. Having a worn bit for hole drilling may cause severe damage to bit leading to cutter or cone losses in the bottom of hole, where a fishing job will have to take place, and all of these will increase the operating cost. The main factor to reduce the cost of drilling operation is to maximize the rate of penetration by analyzing real-time data to predict the drill bit wear while drilling. There are numerous models in the literature for prediction of the rate of penetration based on drilling parameters, mostly based on empirical approaches. One of the most commonly used approaches is Bourgoyne and Young model, where the rate of penetration can be estimated by the drilling parameters as well as a wear index using an empirical correlation, provided all the constants and coefficients are accurately determined. This paper introduces a new methodology to estimate the eight coefficients for Bourgoyne and Young model using the gPROMS parameters estimation GPE (Version 4.2.0). Real data collected form similar formations (12 ¼’ sections) in two different fields in Libya are used to estimate the coefficients. The estimated coefficients are then used in the equations and applied to nearby wells in the same field to predict the bit wear.

Keywords: Bourgoyne and Young model, bit wear, gPROMS, rate of penetration

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Authors: Hala Raslan, Noha Eltaweel, Hanaa Rasmi, Solaf Kamel, May Magdy, Sherif Ismail, Khalda Amr

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Introduction: Rheumatoid arthritis (RA) is an inflammatory, autoimmune disorder with progressive joint damage. Osteoarthritis (OA) is a degenerative disease of the articular cartilage that shows multiple clinical manifestations or symptoms resembling those of RA. Genetic predisposition is believed to be a principal etiological factor for RA and OA. In this study, we aimed to measure the expression of the top deregulated miRNAs that might be the cause of pathogenesis in both diseases, according to our latest NGS analysis. Six of the deregulated miRNAs were selected as they had multiple target genes in the RA pathway, so they are more likely to affect the RA pathogenesis.Methods: Eighty cases were recruited in this study; 45 rheumatoid arthiritis (RA), 30 osteoarthiritis (OA) patients, as well as 20 healthy controls. The selection of the miRNAs from our latest NGS study was done using miRwalk according to the number of their target genes that are members in the KEGG RA pathway. Total RNA was isolated from plasma of all recruited cases. The cDNA was generated by the miRcury RT Kit then used as a template for real-time PCR with miRcury Primer Assays and the miRcury SYBR Green PCR Kit. Fold changes were calculated from CT values using the ΔΔCT method of relative quantification. Results were compared RA vs Controls and OA vs Controls. Target gene prediction and functional annotation of the deregulated miRNAs was done using Mienturnet. Results: Six miRNAs were selected. They were miR-15b-3p, -128-3p, -194-3p, -328-3p, -542-3p and -3180-5p. In RA samples, three of the measured miRNAs were upregulated (miR-194, -542, and -3180; mean Rq= 2.6, 3.8 and 8.05; P-value= 0.07, 0.05 and 0.01; respectively) while the remaining 3 were downregulated (miR-15b, -128 and -328; mean Rq= 0.21, 0.39 and 0.6; P-value= <0.0001, <0.0001 and 0.02; respectively) all with high statistical significance except miR-194. While in OA samples, two of the measured miRNAs were upregulated (miR-194 and -3180; mean Rq= 2.6 and 7.7; P-value= 0.1 and 0.03; respectively) while the remaining 4 were downregulated (miR-15b, -128, -328 and -542; mean Rq= 0.5, 0.03, 0.08 and 0.5; P-value= 0.0008, 0.003, 0.006 and 0.4; respectively) with statistical significance compared to controls except miR-194 and miR-542. The functional enrichment of the selected top deregulated miRNAs revealed the highly enriched KEGG pathways and GO terms. Conclusion: Five of the studied miRNAs were greatly deregulated in RA and OA, they might be highly involved in the disease pathogenesis and so might be future therapeutic targets. Further functional studies are crucial to assess their roles and actual target genes.

Keywords: MiRNAs, expression, rheumatoid arthritis, osteoarthritis

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Authors: Francisco Alvarado, Luz Ramírez

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Corneal diseases are one of the main causes of visual impairment and affect almost 4 million, and this study assesses the effects of deep anterior lamellar keratoplasty (DALK) with porcine corneal stroma and postoperative topical treatment with tacrolimus in patients with infectious keratitis. No patient was observed with clinical graft rejection. Among the cases: 2 were positive to fungal culture, 2 with Aspergillus and the other 8 cases were confirmed by bacteriological culture. Corneal diseases are one of the main causes of visual impairment and affect almost 4 million. This study assesses the effects of deep anterior lamellar keratoplasty (DALK) with porcine corneal stroma and postoperative topical treatment with tacrolimus in patients with infectious keratitis. Receiver bed diameters ranged from 7.00 to 9.00 mm. No incidents of Descemet's membrane perforation were observed during surgery. During the follow-up period, no corneal graft splitting, IOP increase, or intolerance to tacrolimus were observed. Deep anterior lamellar keratoplasty seems to be the best option to avoid xenograft rejection, and it could help new surgical techniques in humans.

Keywords: ophthalmology, cornea, corneal transplant, xenografts, surgical innovations

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Authors: Katie E. Jennings

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The interactions between family dynamics and environmental factors with mental health vulnerability in individuals are well known and are a theme for on-going research and debate. The impact upon mental health issues and forensic issues on family dynamics, experience, and emotional wellbeing cannot be over-Emphasised. For forensic patients with diagnosed mental disorders, these relationships and environments may have also been functionally linked to the development and maintenance of those disorders; with significant adverse childhood experiences being a common feature of many Patient’s histories. Mental health hospitals remove the patient from their home environments and provide treatment outside of these relationships and often outside of the home area. There is, therefore, a major focus on Services ensuring that patients are able to build and maintain relationships with family and friends, requiring services to involve families in Patients' care and treatment wherever possible. There are standards set by Government and clinical bodies that require absolute demonstration of the inclusion of family and friends in all aspects of the care and treatment of forensic patients. For some patients and family members, this push to take on a “role” in care can be unhelpful, extremely stressful, and has constant implications for the potential delicate reparation of relationships. Based on work undertaken for over 20 years in forensic mental health settings, this paper explores the positive psychology approach to a dimensional model to family inclusion in mental health care that learns from family court work and allows for the maintenance of relationships to be at both proximal and Distil levels; to prevent the replication of abuse, decrease the need for falsehoods and assist the recovery of all. The model is based on allowing families to choose to not be involved or be involved in different ways if this is seen to be more helpful. It also allows patients to choose the level of potential involvement that they would find helpful, and for this to be reviewed at a timeframe agreed by all parties, rather than when the next survey is due or the patient has a significant care meeting. This paper is significant as there is a lack of research to support services to use a positive psychology approach to work in this area, the assumption that being asked to be involved must be positive for all seems naïve at best for this patient group. Work relating to the psychology of family can significantly contribute to the development of knowledge in this area. The development of a dimensional model will support choice within families and assist in the development of more honest and open relationships.

Keywords: family dynamics, forensic, mental disorder, positive psychology

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Authors: Alexander Heckman, Rohan Goswami, Zachi Attia, Paul Friedman, Peter Noseworthy, Demilade Adedinsewo, Pablo Moreno-Franco, Rickey Carter, Tathagat Narula

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Background: Postoperative atrial fibrillation (POAF) is associated with adverse health consequences, higher costs, and longer hospital stays. Utilizing existing predictive models that rely on clinical variables and circulating biomarkers, multiple societies have published recommendations on the treatment and prevention of POAF. Although reasonably practical, there is room for improvement and automation to help individualize treatment strategies and reduce associated complications. Methods and Results: In this retrospective cohort study of solid organ transplant recipients, we evaluated the diagnostic utility of a previously developed AI-based ECG prediction for silent AF on the development of POAF within 30 days of transplant. A total of 2261 non-cardiac transplant patients without a preexisting diagnosis of AF were found to have a 5.8% (133/2261) incidence of POAF. While there were no apparent sex differences in POAF incidence (5.8% males vs. 6.0% females, p=.80), there were differences by race and ethnicity (p<0.001 and 0.035, respectively). The incidence in white transplanted patients was 7.2% (117/1628), whereas the incidence in black patients was 1.4% (6/430). Lung transplant recipients had the highest incidence of postoperative AF (17.4%, 37/213), followed by liver (5.6%, 56/1002) and kidney (3.6%, 32/895) recipients. The AUROC in the sample was 0.62 (95% CI: 0.58-0.67). The relatively low discrimination may result from undiagnosed AF in the sample. In particular, 1,177 patients had at least 1 AI-ECG screen for AF pre-transplant above .10, a value slightly higher than the published threshold of 0.08. The incidence of POAF in the 1104 patients without an elevated prediction pre-transplant was lower (3.7% vs. 8.0%; p<0.001). While this supported the hypothesis that potentially undiagnosed AF may have contributed to the diagnosis of POAF, the utility of the existing AI-ECG screening algorithm remained modest. When the prediction for POAF was made using the first postoperative ECG in the sample without an elevated screen pre-transplant (n=1084 on account of n=20 missing postoperative ECG), the AUROC was 0.66 (95% CI: 0.57-0.75). While this discrimination is relatively low, at a threshold of 0.08, the AI-ECG algorithm had a 98% (95% CI: 97 – 99%) negative predictive value at a sensitivity of 66% (95% CI: 49-80%). Conclusions: This study's principal finding is that the incidence of POAF is rare, and a considerable fraction of the POAF cases may be latent and undiagnosed. The high negative predictive value of AI-ECG screening suggests utility for prioritizing monitoring and evaluation on transplant patients with a positive AI-ECG screening. Further development and refinement of a post-transplant-specific algorithm may be warranted further to enhance the diagnostic yield of the ECG-based screening.

Keywords: artificial intelligence, atrial fibrillation, cardiology, transplant, medicine, ECG, machine learning

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Authors: Kristina Thorell

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Food security has been one of the most important policy issues on the global arena after the Second World War. The overall aim of this presentation is to describe preconditions for a sustainable food supply from a spatial perspective. Special attention is paid to the differences between advanced and less advanced economies around the world. The theoretical framework is based upon models which are explaining complex systems of factors that affect the preconditions for agricultural productions. In additions to this, theories about how population and environmental pollution change through different stages of societal development are explained. The results are based upon data of agricultural practices, population growth, hunger and nutrition levels from different countries around the world. The analysis shows that factors which affect preconditions for agricultural production are dynamic. Factors which support the food security in the near future are a decreasing population growth, technological development and innovation but the environmental crisis is associated to high risks. It is, therefore, important to develop environmental policies and improved methods for organic farming. A final conclusion is that the spatial pattern is clear; the food supply is sufficient within advanced economies but rather complicated in development countries.

Keywords: food security, agricultural geography, demography, advanced economies, population growth, agricultural practices

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Authors: Syed Muhammad Wajih ul Hassan

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This research looks at the perception of first-time voters in Pakistan on the political dynamics of the country. This paper shall review the researches that were conducted by Gallup Pakistan and compare it with our findings regarding the voter behavior and factors that affect the priorities of the voters. A country where democracy has just completed its 2 consecutive tenures for the first time, one would always want to know about the voting trends among youth where young population makes 60% of the population in the country. In that case, it is not only a big task to find out voter patterns and trends voters might adhere to while a general election is approaching. Also, the paper discovers the psychology of young Pakistani voters on the upcoming election of 2018 but also the factors that influence the voting decisions of a voter. This research tries to study the relations among voters and how they view each other in general. The paper also explores the views of voters on the factors that impact decision making of a voter while casting his/her vote in Pakistan. The paper thoroughly studies the expectations of the voters from the current system that prevails in the country. The reason this research was conducted is that this kind of positive approach towards finding out the voter perception is heavily untouched in Pakistani academia. This study can benefit a lot of institutions and professions in the future too. The constraints and obstacles that came while this research was being conducted are also identified in the paper. The mode of research is primary research as it was impossible to find out the perceptions of first-time voters without going on the field and carrying out the research. The research was conducted in one of the most reputable and liberal educational institutions of Pakistan. This research is based on a survey that was conducted through questionnaires where responses were collected through a mix process of random and convenient sampling. The major findings of the study show that young voters have a realistic perspective about the electoral process in the country. The research also articulates the factors that affect the priorities of young voters, and also how young voters view other voters that belong from other sections of the society. To conclude, we can say that this research will give us a perspective that can define and identify the voter priorities of the future in Pakistan.

Keywords: first time voters, general election 2018, Pakistan, young

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Authors: Koe Han Beng, Khoo Boo Cheong

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The rising interest of stepped hull design has been led by the demand of more efficient high-speed boat. At the same time, the need of accurate prediction method for stepped planing hull is getting more important. By understanding the flow at high Froude number is the key in designing a practical step hull, the study surrounding stepped hull has been done mainly in the towing tank which is time-consuming and costly for initial design phase. Here the feasibility of predicting hydrodynamics of high-speed planing hull both with and without step using computational fluid dynamics (CFD) with the volume of fluid (VOF) methodology is studied in this work. First the flow around the prismatic body is analyzed, the force generated and its center of pressure are compared with available experimental and empirical data from the literature. The wake behind the transom on the keel line as well as the quarter beam buttock line are then compared with the available data, this is important since the afterbody flow of stepped hull is subjected from the wake of the forebody. Finally the calm water performance prediction of a conventional planing hull and its stepped version is then analyzed. Overset mesh methodology is employed in solving the dynamic equilibrium of the hull. The resistance, trim, and heave are then compared with the experimental data. The resistance is found to be predicted well and the dynamic equilibrium solved by the numerical method is deemed to be acceptable. This means that computational fluid dynamics will be very useful in further study on the complex flow around stepped hull and its potential usage in the design phase.

Keywords: planing hulls, stepped hulls, wake shape, numerical simulation, hydrodynamics

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Authors: Georgios Koronis, Arlindo Silva

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This study seeks to understand the mechanical behavior of a natural fiber reinforced composite (epoxy/flax) in more depth, utilizing both experimental and numerical methods. It is attempted to identify relationships between the design parameters and the product performance, understand the effect of noise factors and reduce process variations. Optimization of the mechanical performance of manufactured goods has recently been implemented by numerous studies for green composites. However, these studies are limited and have explored in principal mass production processes. It is expected here to discover knowledge about composite’s manufacturing that can be used to design artifacts that are of low batch and tailored to niche markets. The goal is to reach greater consistency in the performance and further understand which factors play significant roles in obtaining the best mechanical performance. A prediction of response function (in various operating conditions) of the process is modeled by the DoE. Normally, a full factorial designed experiment is required and consists of all possible combinations of levels for all factors. An analytical assessment is possible though with just a fraction of the full factorial experiment. The outline of the research approach will comprise of evaluating the influence that these variables have and how they affect the composite mechanical behavior. The coupons will be fabricated by the vacuum infusion process defined by three process parameters: flow rate, injection point position and fiber treatment. Each process parameter is studied at 2-levels along with their interactions. Moreover, the tensile and flexural properties will be obtained through mechanical testing to discover the key process parameters. In this setting, an experimental phase will be followed in which a number of fabricated coupons will be tested to allow for a validation of the design of the experiment’s setup. Finally, the results are validated by performing the optimum set of in a final set of experiments as indicated by the DoE. It is expected that after a good agreement between the predicted and the verification experimental values, the optimal processing parameter of the biocomposite lamina will be effectively determined.

Keywords: design of experiments, flax fabrics, mechanical performance, natural fiber reinforced composites

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Authors: Jiyoung Yoon

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This study examines Spanish textbook explanations of infinitival complements and how they can affect a learner’s second-language acquisition process. Verbs taking infinitival complements are commonly found in the mandate, volition, and emotion verbs, both for Spanish and English. However, while some English verbs take gerunds (María avoids eating/*to eat meat), in Spanish a gerund never functions as the complement of a verb (María evita comer/*comiendo carne). Because of these differences, English learners of Spanish often have difficulty acquiring infinitival complement constructions in Spanish. Specifically, they may employ English-like complement structures, producing such ungrammatical utterances as *Odio comiendo tacos ‘I hate eating tacos.' A compounding factor is that many Spanish textbooks do not emphasize the usages of infinitival complements and, when explanations are provided, they are often vague and insufficient. This study examines Spanish textbook explanations of infinitival complements (intermediate and advanced college-level Spanish textbooks and grammar reference books published in the United States) to determine areas that are problematic and insufficient and how they can affect learners’ second-language acquisition process. In this study, alternative principle-driven explanations are proposed as a replacement.

Keywords: Spanish, teaching, second language, infinitival complement, textbook

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Authors: Nirere Martine

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Purpose –The purpose of this study aims to understand the intention of customers to adopt sustainable packaging and the impact of sustainable packaging on customers’ willingness to buy a product using sustainable packaging. Design/methodology/approach – A new research model based on the technology acceptance model (TAM) and structural equation modeling are used to examine causality and test relationship based on the data collected from 251 Rwanda samples. Findings – The findings indicated that perceived ease of use positively affects perceived usefulness. However, perceived usefulness and perceived ease of use positively affect the intention to adopt sustainable packaging. However, perceived risk and perceived cost negatively affect the intention to adopt sustainable packaging. The intention to adopt sustainable packaging positively affects the willingness to buy a product using sustainable packaging. Originality/value – Many researchers have investigated the issue of a consumers’ behavior to purchase a product. In particular, they have examined whether customers are willing to pay extra for a packaging product. There has been no study that has examined the impact of sustainable packaging on customers’ willingness to buy. The results of this study can help manufacturers form a better understanding of customers’ willingness to purchase a product using sustainable packaging.

Keywords: consumers’ behavioral, sustainable packaging, TAM, Rwanda

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Authors: Muhammad Luthfi, Sutikno Sutikno, Purhadi Purhadi

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Weather forecast has necessarily been improved to provide the communities an accurate and objective prediction as well. To overcome such issue, the numerical-based weather forecast was extensively developed to reduce the subjectivity of forecast. Yet the Numerical Weather Predictions (NWPs) outputs are unfortunately issued without taking dynamical weather behavior and local terrain features into account. Thus, NWPs outputs are not able to accurately forecast the weather quantities, particularly for medium and long range forecast. The aim of this research is to aid and extend the development of ensemble forecast for Meteorology, Climatology, and Geophysics Agency of Indonesia. Ensemble method is an approach combining various deterministic forecast to produce more reliable one. However, such forecast is biased and uncalibrated due to its underdispersive or overdispersive nature. As one of the parametric methods, Bayesian Model Averaging (BMA) generates the calibrated ensemble forecast and constructs predictive PDF for specified period. Such method is able to utilize ensemble of any size but does not take spatial correlation into account. Whereas space dependencies involve the site of interest and nearby site, influenced by dynamic weather behavior. Meanwhile, Geostatistical Output Perturbation (GOP) reckons the spatial correlation to generate future weather quantities, though merely built by a single deterministic forecast, and is able to generate an ensemble of any size as well. This research conducts both BMA and GOP to generate the calibrated ensemble forecast for the daily temperature at few meteorological sites nearby Indonesia international airport.

Keywords: Bayesian Model Averaging, ensemble forecast, geostatistical output perturbation, numerical weather prediction, temperature

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Authors: Ali Safari, Pejman Hosseiniun, Iman Rahbari, MohamadReza Kalhor

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The semiconductor industry is placing an increased emphasis on emerging materials and devices that may provide improved performance, or provide novel functionality for devices. Recently, graphene, as a true two-dimensional carbon material, has shown fascinating applications in electronics. In this paper detailed discussions are introduced for possible applications of grapheme Transistor in RF and digital devices.

Keywords: graphene, GFET, RF, digital

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Authors: Tarik Elaujali

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This study examines a new media effective theory was developed by the author, it is called ‘The Effervescent Disk Theory’ (EDT). The theory main goal is to affect the unaffected audience who are either not exposing to a particular message or do not show interest in it. EDT suggest melting down messages that means to be affected within the media materials which are selected willingly by the audience themselves. A certain set of procedures to test EDT hypotheses were taken and illustrated in this study. A sample of 342 respondents (males & females) was collected from Tripoli University in Libya during the academic year 2013-2014. The designated sample is representing students who were failing to pass the English module for beginners’. This study aims to change the students’ negative notion about the importance of learning English, and to put their new idea into action. The theory seeks to affect audience cognition, emotions, and behaviors. EDT was applied in the present study alongside the media dependency theory. EDT hypotheses were confirmed, study results denoted that 73.6 percentage of the students responded positively and passed their English exam for beginners after being exposed selectively to their favorite TV program that contains a dissolved messages about the importance and vitality of learning English language.

Keywords: effervescent disk theory, selective exposure, media dependency, Libyan students

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Authors: Manuela Villani, Anila Xhahysa, Christopher Brooks, Marco Pagani

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The geological structure of Western Balkans is strongly affected by the collision between Adria microplate and the southwestern Euroasia margin, resulting in a considerably active seismic region. The Harmonization of Seismic Hazard Maps in the Western Balkan Countries Project (BSHAP) (2007-2011, 2012-2015) by NATO supported the preparation of new seismic hazard maps of the Western Balkan, but when inspecting the seismic hazard models produced later by these countries on a national scale, significant differences in design PGA values are observed in the border, for instance, North Albania-Montenegro, South Albania- Greece, etc. Considering the fact that the catalogues were unified and seismic sources were defined within BSHAP framework, obviously, the differences arise from the Ground Motion Prediction Equations selection, which are generally the component with highest impact on the seismic hazard assessment. At the time of the project, a modest database was present, namely 672 three-component records, whereas nowadays, this strong motion database has increased considerably up to 20,939 records with Mw ranging in the interval 3.7-7 and epicentral distance distribution from 0.47km to 490km. Statistical analysis of the strong motion database showed the lack of recordings in the moderate-to-large magnitude and short distance ranges; therefore, there is need to re-evaluate the Ground Motion Prediction Equation in light of the recently updated database and the new generations of GMMs. In some cases, it was observed that some events were more extensively documented in one database than the other, like the 1979 Montenegro earthquake, with a considerably larger number of records in the BSHAP Analogue SM database when compared to ESM23. Therefore, the strong motion flat-file provided from the Harmonization of Seismic Hazard Maps in the Western Balkan Countries Project was merged with the ESM23 database for the polygon studied in this project. After performing the preliminary residual analysis, the candidate GMPE-s were identified. This process was done using the GMPE performance metrics available within the SMT in the OpenQuake Platform. The Likelihood Model and Euclidean Distance Based Ranking (EDR) were used. Finally, for this study, a GMPE logic tree was selected and following the selection of candidate GMPEs, model weights were assigned using the average sample log-likelihood approach of Scherbaum.

Keywords: residual analysis, GMPE, western balkan, strong motion, openquake

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Authors: Adeoti Adebowale, Abduljaleel, Ejiogu Fidelis Onyekwo

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Form and image development are fundamental to creative expression in visual arts. The form is an element that distinguishes the difference between two-dimension and three-dimension among the branches of visual arts. Particularly, the sculpture is a three-dimensional form, while the textile design is a two-dimensional form of its visual appearance. The visual expression of each of them is embedded in the creative practice of the artist, which is easily understood and interpreted by the viewer. In this research, an attempt is made to explore and analyse sculptural forms adopted as a motif for wax print in textile design, aiming at breeding yet another pattern and motif suitable for various design uses. For instance, the dynamics of sculptural form adaptation into other areas of creativity, such as architecture, pictorial arts and pottery, as well as automobile bodies, is a discernible image everywhere. The research is studio exploratory, while a camera and descriptive analysis were used to process the data. Two sculptural forms were adopted from the Department of Fine and Applied Arts, Federal Capital Territory College of Education Zuba-Abuja, in this study due to the uniqueness of their technique of execution. The findings resulted in ten (10) paper designs showing the dexterity of studio practice in the development of design for various fashion and textile uses. However, the paper concludes that sculptural form is a source of inspiration for generating design concepts for a textile designer.

Keywords: exploration, design, motifs, sculptural forms, wax print

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Authors: Pongsakorn Komutpol, Pravej Serichetaphongse, Soontra Panmekiate, Atiphan Pimkhaokham

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Statement of Problem: The important parameter of esthetic assessment in anterior maxillary implant include pink esthetic of gingiva and white esthetic of restoration. While the 3 dimensional (3D) implant position are recently concerned as a key for succeeding in implant treatment. However, to our knowledge, the authors did not come across any publication that demonstrated the relations of esthetic outcome and 3D implant position. Objectives: To investigate the correlation between positional accuracy of single-tooth implant restoration (STIR) in all 3 dimensions and their esthetic outcomes. Materials and Methods: 17 patients’ data who had a STIR at central incisor with pristine contralateral tooth were included in this study. Intraoral photographs, dental models, and cone beam computed tomography (CBCT) images were retrieved. The esthetic outcome was assessed in accordance with pink esthetic score and white esthetic score (PES/WES). While the number of correct position in each dimension (mesiodistal, labiolingual, apicocoronal) of the implant were evaluated and defined as 'right' or 'wrong' according to ITI consensus conference by one investigator using CBCT data. The different mean score between right and wrong position in all dimensions was analyzed by Mann-Whitney U test with 0.05 was the significant level of the study. Results: The average score of PES/WES was 15.88 ± 1.65 which was considered as clinically acceptable. The average PES/WES score in 1, 2 and 3 right dimension of the implant position were 16.71, 15.75 and 15.17 respectively. None of the implants placed wrongly in all three dimensions. Statistically significant difference of the PES/WES score was found between the implants that placed right in 3 dimensions and 1 dimension (p = 0.041). Conclusion: This study supported the principle of 3D position of implant. The more properly implant was placed, the higher esthetic outcome was found.

Keywords: accuracy, dental implant, esthetic, 3D implant position

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Authors: Silke Bustamante, Andrea Pelzeter, Andreas Deckmann, Rudi Ehlscheidt, Franziska Freudenberger

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Many companies increasingly seek to enhance their attractiveness as an employer to bind their employees. At the same time, corporate responsibility for social and ecological issues seems to become a more important part of an attractive employer brand. It enables the company to match the values and expectations of its members, to signal fairness towards them and to increase its brand potential for positive psychological identification on the employees’ side. In the last decade, several empirical studies have focused this relationship, confirming a positive effect of employees’ CSR perception and their affective organizational commitment. The current paper aims to take a slightly different view by analyzing the impact of another factor on commitment: the weighted employee’s satisfaction with the employer CSR. For that purpose, it is assumed that commitment levels are rather a result of the fulfillment or disappointment of expectations. Hence, instead of merely asking how CSR perception affects commitment, a more complex independent variable is taken into account: a weighted satisfaction construct that summarizes two different factors. Therefore, the individual level of commitment contingent on CSR is conceptualized as a function of two psychological processes: (1) the individual significance that an employee ascribes to specific employer attributes and (2) the individual satisfaction based on the fulfillment of expectation that rely on preceding perceptions of employer attributes. The results presented are based on a quantitative survey that was undertaken among employees of the German service sector. Conceptually a five-dimensional CSR construct (ecology, employees, marketplace, society and corporate governance) and a two-dimensional non-CSR construct (company and workplace) were applied to differentiate employer characteristics. (1) Respondents were asked to indicate the importance of different facets of CSR-related and non-CSR-related employer attributes. By means of a conjoint analysis, the relative importance of each employer attribute was calculated from the data. (2) In addition to this, participants stated their level of satisfaction with specific employer attributes. Both indications were merged to individually weighted satisfaction indexes on the seven-dimensional levels of employer characteristics. The affective organizational commitment of employees (dependent variable) was gathered by applying the established 15-items Organizational Commitment Questionnaire (OCQ). The findings related to the relationship between satisfaction and commitment will be presented. Furthermore, the question will be addressed, how important satisfaction with CSR is in relation to the satisfaction with other attributes of the company in the creation of commitment. Practical as well as scientific implications will be discussed especially with reference to previous results that focused on CSR perception as a commitment driver.

Keywords: corporate social responsibility, organizational commitment, employee attitudes/satisfaction, employee expectations, employer brand

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