Search results for: partial least squares discriminant analysis

Authors: M. Ibrahim Ali, M. El Dawi, M. A. Mohamed Ali

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In this study, the use of magnetic gradient survey, and the geoelectrical ground methods used together to explore archaeological features in Nuri’s pyramids area. Research methods used and the procedures and methodologies have taken full right during the study. The magnetic survey method was used to search for archaeological features using (Geoscan Fluxgate Gradiometer (FM36)). The study area was divided into a number of squares (networks) exactly equal (20 * 20 meters). These squares were collected at the end of the study to give a major network for each region. Networks also divided to take the sample using nets typically equal to (0.25 * 0.50 meter), in order to give a more specific archaeological features with some small bipolar anomalies that caused by buildings built from fired bricks. This definition is important to monitor many of the archaeological features such as rooms and others. This main network gives us an integrated map displayed for easy presentation, and it also allows for all the operations required using (Geoscan Geoplot software). The parallel traverse is the main way to take readings of the magnetic survey, to get out the high-quality data. The study area is very rich in old buildings that vary from small to very large. According to the proportion of the sand dunes and the loose soil, most of these buildings are not visible from the surface. Because of the proportion of the sandy dry soil, there is no connection between the ground surface and the electrodes. We tried to get electrical readings by adding salty water to the soil, but, unfortunately, we failed to confirm the magnetic readings with electrical readings as previously planned.

Keywords: archaeological features, independent grids, magnetic gradient, Nuri pyramid

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Authors: Ghada S. Moussa

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Vehicle classification is an important task in traffic surveillance and intelligent transportation systems. Classification of vehicle images is facing several problems such as: high intra-class vehicle variations, occlusion, shadow, illumination. These problems and others must be considered to develop a reliable vehicle classification system. In this study, a reliable multi-type vehicle classification system based on Bag-of-Words (BoW) paradigm is developed. Our proposed system used and compared four well-known classifiers; Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), k-Nearest Neighbour (KNN), and Decision Tree to classify vehicles into four categories: motorcycles, small, medium and large. Experiments on a large dataset show that our approach is efficient and reliable in classifying vehicles with accuracy of 95.7%. The SVM outperforms other classification algorithms in terms of both accuracy and robustness alongside considerable reduction in execution time. The innovativeness of developed system is it can serve as a framework for many vehicle classification systems.

Keywords: vehicle classification, bag-of-words technique, SVM classifier, LDA classifier, KNN classifier, decision tree classifier, SIFT algorithm

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Authors: Fekadu Melak, Tsegaye Girma Asere

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Trace element ions, such as Cr(VI) and F−, are of particular interest due to their environmental impact. Both ions exhibit an anionic nature in water that can show similar removal tendencies except for their significant differences in ionic radius. Accordingly, partial freezing was performed to examine freeze separation efficiencies of Cr(VI) and F– from aqueous solutions. Real groundwater and simulated wastewater were included to test effeciency of F– and Cr(VI), respectively. Parameters such as initial ion concentration, salt addition, and freeze duration were explored. Under optimal operating conditions, freeze separation efficiencies of 90 ± 0.12 to 97 ± 0.54% and 58 ± 0.23% to 60 ± 0.34% from 5 mg/L of Cr(VI) and F–, respectively, were demonstrated. The F– ion intercalation into the ice, initiating the decrement of freeze separation efficiency was observed in the salt addition processes. The influences of structuring-destructuring (kosmotropicity-chaotropicity) and the size-exclusion nature of ice crystals were used to explain the plausible mechanism in freeze separation efficiency trace elemental ions.

Keywords: Cr(VI), F-, partial freezing, size exclusion

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Authors: Omonov Jahongir Mahmatkulovic

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Purpose: To study the significance of D-dimer (DD), prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrinogen coagulation parameters (Fg) in predicting the course, severity and prognosis of COVID-19. Source and method of research: From September 15, 2021, to November 5, 2021, 93 patients aged 25 to 60 with suspected COVID-19, who are under inpatient treatment at the multidisciplinary clinic of the Tashkent Medical Academy, were retrospectively examined. DD, PT, APTT, and Fg were studied in dynamics and studied changes. Results: Coagulation disorders occurred in the early stages of COVID-19 infection with an increase in DD in 54 (58%) patients and an increase in Fg in 93 (100%) patients. DD and Fg levels are associated with the clinical classification. Of the 33 patients who died, 21 had an increase in DD in the first laboratory study, 27 had an increase in DD in the second and third laboratory studies, and 15 had an increase in PT in the third test. The results of the ROC analysis of mortality showed that the AUC DD was three times 0.721, 0.801, and 0.844, respectively; PT was 0.703, 0.845, and 0.972. (P<0:01). Conclusion”: Coagulation dysfunction is more common in patients with severe and critical conditions. DD and PT can be used as important predictors of mortality from COVID-19.

Keywords: Covid19, DD, PT, Coagulogram analysis, APTT

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Authors: Arawati Agus, Rahmah Ismail

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An effective training has been increasingly recognized as critical factors in enhancing the skills and knowledge of employee or personnel in the organization. More and more manufacturing companies in Malaysia are increasingly incorporating training as an important element in supply chain management (SCM) to improve their employee skills and knowledge and ultimately organizational performances. In order to understand the connection of training in SCM and the performance of an organization, this paper considers of many arguments from various research papers. This paper presents the findings of a research which examines the relationship between training in SCM, personnel differentiation and business performance of manufacturing companies in Malaysia. The study measures perception of senior management regarding the incorporation of training in SCM and the level of personnel differentiation and business performance measurements in their companies. The associations between training in SCM, personnel differentiation and business performance dimensions are analyzed through methods such as Pearson’s correlations and Smart partial least squares (smart PLS) using 126 respondents’ data. The correlation results demonstrate that training in SCM has significant correlations with personnel differentiation determinants (comprises of variables namely employee differentiation and service differentiation). The findings also suggest that training in SCM has significant correlations with business performance determinants (comprises of indicators, namely market share, profitability, ROA and ROS). Specifically, both personnel differentiation and business performance have high correlations with training in SCM, namely ‘Employee training on production skills’, ‘On the job production employee training’ and ‘Management training on supply chain effectiveness’ and ‘Employee training on supply chain technologies’. The smart PLS result also reveals that training in SCM exhibits significant impact on both personnel differentiation (directly) and business performance (indirectly mediated by personnel differentiation). The findings of the study provide a demonstration of the importance of training in SCM in enhancing competitive performances in Malaysian manufacturing companies.

Keywords: training in SCM, personnel differentiation, business performance, Pearson’s correlation, Smart PLS

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Authors: Miranda E. Karban

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A distinctive pattern of occipital squama convexity, known as the occipital bun or chignon, has traditionally been considered a derived Neandertal trait. However, some early modern and extant Homo sapiens share similar occipital bone morphology, showing pronounced internal and external occipital squama curvature and paralambdoidal flattening. It has been posited that these morphological patterns are homologous in the two groups, but this claim remains disputed. Many developmental hypotheses have been proposed, including assertions that the chignon represents a developmental response to a long and narrow cranial vault, a narrow or flexed basicranium, or a prognathic face. These claims, however, remain to be metrically quantified in a large subadult sample, and little is known about the feature’s developmental, functional, or evolutionary significance. This study assesses patterns of chignon development and covariation in a comparative sample of extant human growth study cephalograms. Cephalograms from a total of 549 European-derived North American subjects (286 male, 263 female) were scored on a 5-stage ranking system of chignon prominence. Occipital squama shape was found to exist along a continuum, with 34 subjects (6.19%) possessing defined chignons, and 54 subjects (9.84%) possessing very little occipital squama convexity. From this larger sample, those subjects represented by a complete radiographic series were selected for metric analysis. Measurements were collected from lateral and posteroanterior (PA) cephalograms of 26 subjects (16 male, 10 female), each represented at 3 longitudinal age groups. Age group 1 (range: 3.0-6.0 years) includes subjects during a period of rapid brain growth. Age group 2 (range: 8.0-9.5 years) includes subjects during a stage in which brain growth has largely ceased, but cranial and facial development continues. Age group 3 (range: 15.9-20.4 years) includes subjects at their adult stage. A total of 16 landmarks and 153 sliding semi-landmarks were digitized at each age point, and geometric morphometric analyses, including relative warps analysis and two-block partial least squares analysis, were conducted to study covariation patterns between midsagittal occipital bone shape and other aspects of craniofacial morphology. A convex occipital squama was found to covary significantly with a low, elongated neurocranial vault, and this pattern was found to exist from the youngest age group. Other tested patterns of covariation, including cranial and basicranial breadth, basicranial angle, midcoronal cranial vault shape, and facial prognathism, were not found to be significant at any age group. These results suggest that the chignon, at least in this sample, should not be considered an independent feature, but rather the result of developmental interactions relating to neurocranial elongation. While more work must be done to quantify chignon morphology in fossil subadults, this study finds no evidence to disprove the developmental homology of the feature in modern humans and Neandertals.

Keywords: chignon, craniofacial covariation, human cranial development, longitudinal growth study, occipital bun

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Authors: S. K. Ashiquer Rahman

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The proper policy handling might not able to attain the target since some of recessions, e.g., pandemic-led crises, the variables shocks of the economics. At the level of this situation, the Central bank implements the monetary policy to choose increase the exogenous expenditure and level of money supply consecutively for booster level economic growth, whether the monetary policy is relatively more effective than fiscal policy in altering real output growth of a country or both stand for relatively effective in the direction of output growth of a country. The dispute with reference to the relationship between the monetary policy and fiscal policy is centered on the inflationary penalty of the shortfall financing by the fiscal authority. The latest variables socks of economics as well as the pandemic-led crises, central banks around the world predicted just about a general dilemma in relation to increase rates to face the or decrease rates to sustain the economic movement. Whether the prices hang about fundamentally unaffected, the aggregate demand has also been hold a significantly negative attitude by the outbreak COVID-19 pandemic. To empirically investigate the effects of economics shocks associated COVID-19 pandemic, the paper considers the effectiveness of the monetary policy and fiscal policy that linked to the adjustment mechanism of different economic variables. To examine the effects of economics shock associated COVID-19 pandemic towards the effectiveness of Monetary Policy and Fiscal Policy in the direction of output growth of a Country, this paper uses the Simultaneous equations model under the estimation of Two-Stage Least Squares (2SLS) and Ordinary Least Squares (OLS) Method.

Keywords: IS-LM framework, pandemic. Economics variables shocks, simultaneous equations model, output growth

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Authors: Sajad Haghanifar, Seyed-Farshid Kashani Bozorg

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Nano-crystalline Mg2Ni-based powder was produced by mechanical alloying technique using binary and ternary powder mixtures with stoichiometric compositions of Mg2Ni, Mg1.9C0.1Ni and Mg2C0.1Ni0.9. The structures and morphologies of the milled products were studied by XRD, SEM and HRTEM. Their electrochemical hydrogen storage characteristics were investigated in 6 M KOH solution. X-Ray diffraction, scanning and transmission electron microscopy of the milled products showed the formation of Mg2Ni-based nano-crystallites after 5, 15 and 30 h of milling using the initial powder mixtures of Mg1.9C0.1Ni, Mg2Ni and Mg2C0.1Ni0.9, respectively. It was found that partial substitution of C for Mg has beneficial effect on the formation kinetic of nano-crystalline Mg2Ni. Contrary to this, partial substitution of C for Ni was resulted in retardation of formation kinetic of nano-crystalline Mg2Ni. In addition, the negative electrode made from Mg1.9C0.1Ni ternary milled product after 30 hour of milling exhibited the highest initial discharge capacity and longest discharge life. Thus, partial substitution of C for Mg is beneficial to electrode properties of the Mg2Ni-based crystallites. The relation between the discharge capacity and cycling number of mechanically alloyed products was proposed on the basis of the fact that the degradation of discharge capacity was mainly caused by the oxidation of magnesium and nickel. The experimental data fitted the deduced equation well.

Keywords: Mg2Ni, hydrogen absorbing materials, electrochemical properties, nano-crystalline, amorphous, mechanical alloying, carbon

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Authors: Rafael Martins Manzano Silva, Jean-Francois Tremong

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Electrification of railway lines allows to increase speed, power, capacity and energetic efficiency of rolling stocks. However, this process of electrification is complex and costly. An electrification project is not just about design of catenary. It also includes installation of structures around electrification, as substation installation, electrical isolation, signalling, telecommunication and civil engineering structures. France has more than 30,000 km of railways, whose only 53% are electrified. The others 47% of railways use diesel locomotive and represent only 10% of the circulation (tons.km). For this reason, a new type of electrification, less expensive than the usual, is requested to enable the modernization of these railways. One solution could be the use of hybrids trains. This technology opens up new opportunities for less expensive infrastructure development such as the partial electrification of railway lines. In a partially electrified railway, the power supply of theses hybrid trains could be made either by the catenary or by the on-board energy storage system (ESS). Thus, the on-board ESS would feed the energetic needs of the train along the non-electrified zones while in electrified zones, the catenary would feed the train and recharge the on-board ESS. This paper’s objective deals with the technical and economic potential identification of partial electrification of railway lines. This study provides different scenarios of electrification by replacing the most expensive places to electrify using on-board ESS. The target is to reduce the cost of new electrification projects, i.e. reduce the cost of electrification infrastructures while not increasing the cost of rolling stocks. In this study, scenarios are constructed in function of the electrification’s cost of each structure. The electrification’s cost varies considerably because of the installation of catenary support in tunnels, bridges and viaducts is much more expensive than in others zones of the railway. These scenarios will be used to describe the power supply system and to choose between the catenary and the on-board energy storage depending on the position of the train on the railway. To identify the influence of each partial electrification scenario in the sizing of the on-board ESS, a model of the railway line and of the rolling stock is developed for a real case. This real case concerns a railway line located in the south of France. The energy consumption and the power demanded at each point of the line for each power supply (catenary or on-board ESS) are provided at the end of the simulation. Finally, the cost of a partial electrification is obtained by adding the civil engineering costs of the zones to be electrified plus the cost of the on-board ESS. The study of the technical and economic potential ends with the identification of the most economically interesting scenario of electrification.

Keywords: electrification, hybrid, railway, storage

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Authors: A. M. Jungudo, M. A. Lasan

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Affordable housing has long been one of the basic necessities of life to man. The ever rising prices of building materials are one of the major causes of housing shortage in many developing countries. Breaching the gap of housing needs in developing countries like Nigeria is an awaiting task longing for attention. This is due to lack of research in the development of local materials that will suit the troubled economies of these countries. The use of earth material to meet the housing needs is a sustainable option and its material is freely available universally. However, people are doubtful of using the earth material due to its modest outlook and uncertain durability. This research aims at enhancing the durability of Compressed Earth Bricks (CEBs) using stone dust as a stabilizer. The result indicates that partial replacement of lateritic soil with stone dust at 30% improves its compressive strength along with abrasive resistance.

Keywords: earth construction, durability, stone dust, sustainable

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Authors: Saghar Heidari

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In this paper, we study the valuation problem of European continuous-installment options under Markov-modulated models with a partial differential equation approach. Due to the opportunity for continuing or stopping to pay installments, the valuation problem under regime-switching models can be formulated as coupled partial differential equations (CPDE) with free boundary features. To value the installment options, we express the truncated CPDE as a linear complementarity problem (LCP), then a finite element method is proposed to solve the resulted variational inequality. Under some appropriate assumptions, we establish the stability of the method and illustrate some numerical results to examine the rate of convergence and accuracy of the proposed method for the pricing problem under the regime-switching model.

Keywords: continuous-installment option, European option, regime-switching model, finite element method

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Authors: A.Zitouni, S.Bentata, B.Bouadjemi, T.Lantri, W. Benstaali, Z.Aziz, S.Cherid

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We investigate the structural, electronic and magnetic properties of the diluted magnetic semiconductors (DMSs) CdCoTe and CdMnTe in the zinc blende phase with 25% of Co and Mn. The calculations are performed by the recent ab initio full potential augmented plane waves (FP_L/APW) method within the spin polarized density-functional theory (DFT) and the generalized gradient approximation GGA. Structural properties are determined from the total energy calculations and we found that these compounds are stable in the ferromagnetic phase. We discuss the electronic structures, total and partial densities of states and total magnetic moments. The calculated densities of states presented in this study identify the half-metallic of CdCoTe and CdMnTe.

Keywords: electronic structure, half-metallic, magnetic moment, total and partial densities of states

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Authors: Imam Taufik, Hilkatul Ilmi, Puryani, Mochammad Yuwono, Aty Widyawaruyanti

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Artocarpus champeden Spreng stembark (Moraceae) in Indonesia well known as ‘cempedak’ had been traditionally used for malarial remedies. The difference of growth locations could cause the difference of metabolite profiling. As a consequence, there were difference antimalarial activities in spite of the same plants. The aim of this research was to obtain the profile of metabolites that contained in A. champeden stembark from different locations in Indonesia for authentication and quality control purpose of this extract. The profiling had been performed by HPTLC-Densitometry technique and antimalarial activity had been also determined by HRP2-ELISA technique. The correlation between metabolite fingerprinting and antimalarial activity had been analyzed by Principle Component Analysis, Hierarchical Clustering Analysis and Partial Least Square. As a result, there is correlation between the difference metabolite fingerprinting and antimalarial activity from several different growth locations.

Keywords: antimalarial, artocarpus champeden spreng, metabolite fingerprinting, multivariate analysis

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Authors: Hien Thi Dieu Truong, Mahmoud Al-Sarayreh, Pullanagari Reddy, Marlon M. Reis, Richard Archer

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New Zealand mānuka honey is a honeybee product derived mainly from Leptospermum scoparium nectar. The potent antibacterial activity of mānuka honey derives principally from methylglyoxal (MGO), in addition to the hydrogen peroxide and other lesser activities present in all honey. MGO is formed from dihydroxyacetone (DHA) unique to L. scoparium nectar. Mānuka honey also has an idiosyncratic phenolic profile that is useful as a chemical maker. Authentic mānuka honey is highly valuable, but almost all honey is formed from natural mixtures of nectars harvested by a hive over a time period. Once diluted by other nectars, mānuka honey irrevocably loses value. We aimed to apply hyperspectral imaging to honey frames before bulk extraction to minimise the dilution of genuine mānuka by other honey and ensure authenticity at the source. This technology is non-destructive and suitable for an industrial setting. Chemometrics using linear Partial Least Squares (PLS) and Support Vector Machine (SVM) showed limited efficacy in interpreting chemical footprints due to large non-linear relationships between predictor and predictand in a large sample set, likely due to honey quality variability across geographic regions. Therefore, an advanced modelling approach, one-dimensional convolutional neural networks (1D-CNN), was investigated for analysing hyperspectral data for extraction of biochemical information from honey. The 1D-CNN model showed superior prediction of honey quality (R² = 0.73, RMSE = 2.346, RPD= 2.56) to PLS (R² = 0.66, RMSE = 2.607, RPD= 1.91) and SVM (R² = 0.67, RMSE = 2.559, RPD=1.98). Classification of mono-floral manuka honey from multi-floral and non-manuka honey exceeded 90% accuracy for all models tried. Overall, this study reveals the potential of HSI and deep learning modelling for automating the evaluation of honey quality in frames.

Keywords: mānuka honey, quality, purity, potency, deep learning, 1D-CNN, chemometrics

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Authors: Jude Opara, Esemokumo Perewarebo Akpos

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This paper is on non-parametric linear regression over its parametric counterparts with large sample size. Data set on anthropometric measurement of primary school pupils was taken for the analysis. The study used 50 randomly selected pupils for the study. The set of data was subjected to normality test, and it was discovered that the residuals are not normally distributed (i.e. they do not follow a Gaussian distribution) for the commonly used least squares regression method for fitting an equation into a set of (x,y)-data points using the Anderson-Darling technique. The algorithms for the nonparametric Theil’s regression are stated in this paper as well as its parametric OLS counterpart. The use of a programming language software known as “R Development” was used in this paper. From the analysis, the result showed that there exists a significant relationship between the response and the explanatory variable for both the parametric and non-parametric regression. To know the efficiency of one method over the other, the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) are used, and it is discovered that the nonparametric regression performs better than its parametric regression counterparts due to their lower values in both the AIC and BIC. The study however recommends that future researchers should study a similar work by examining the presence of outliers in the data set, and probably expunge it if detected and re-analyze to compare results.

Keywords: Theil’s regression, Bayesian information criterion, Akaike information criterion, OLS

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Authors: Yonwaba Atyosi, Moses Cho, Abel Ramoelo, Nobuhle Majozi, Cecilia Masemola, Yoliswa Mkhize

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Spectroscopy has been widely used to understand the hyperspectral remote sensing of soils. Accurate and efficient measurement of soil moisture is essential for precision agriculture. The aim of this study was to understand the spectral behavior of soil at different soil water content levels and identify the significant spectral bands for soil moisture content retrieval at field-scale. The study consisted of 60 soil samples from a maize farm, divided into four different treatments representing different moisture levels. Spectral signatures were measured for each sample in laboratory under artificial light using an Analytical Spectral Device (ASD) spectrometer, covering a wavelength range from 350 nm to 2500 nm, with a spectral resolution of 1 nm. The results showed that the absorption features at 1450 nm, 1900 nm, and 2200 nm were particularly sensitive to soil moisture content and exhibited strong correlations with the water content levels. Continuum removal was developed in the R programming language to enhance the absorption features of soil moisture and to precisely understand its spectral behavior at different water content levels. Statistical analysis using partial least squares regression (PLSR) models were performed to quantify the correlation between the spectral bands and soil moisture content. This study provides insights into the spectral behavior of soil at different water content levels and identifies the significant spectral bands for soil moisture content retrieval. The findings highlight the potential of spectroscopy for non-destructive and rapid soil moisture measurement, which can be applied to various fields such as precision agriculture, hydrology, and environmental monitoring. However, it is important to note that the spectral behavior of soil can be influenced by various factors such as soil type, texture, and organic matter content, and caution should be taken when applying the results to other soil systems. The results of this study showed a good agreement between measured and predicted values of Soil Moisture Content with high R2 and low root mean square error (RMSE) values. Model validation using independent data was satisfactory for all the studied soil samples. The results has significant implications for developing high-resolution and precise field-scale soil moisture retrieval models. These models can be used to understand the spatial and temporal variation of soil moisture content in agricultural fields, which is essential for managing irrigation and optimizing crop yield.

Keywords: soil moisture content retrieval, precision agriculture, continuum removal, remote sensing, machine learning, spectroscopy

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Authors: Suwarno, M. Helmi Prakoso

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Mineral oil is commonly used for high voltage transformer insulation. The insulation quality of mineral oil is affecting the operation process of high voltage transformer. There are many contaminations which could decrease the insulation quality of mineral oil. One of them is water. This research talks about the effect of water content on dielectric properties, physic properties, and partial discharge pattern on mineral oil. Samples were varied with 10 varieties of water content value. And then all samples were tested to measure the dielectric properties, physic properties, and partial discharge pattern. The result of this research showed that an increment of water content value would decrease the insulation quality of mineral oil.

Keywords: dielectric properties, high voltage transformer, mineral oil, water content

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Authors: B. Oral, C. Bal, M. S. Kar, A. Akgürbüz

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Loss of maxillary central incisors occurs in many patients, and the treatment of young adults with this problem is a challenge for both prosthodontists and orthodontists. Common treatment alternatives are distalization of adjacent teeth and fabrication of a conventional 3-unit fixed partial denture, a single implant supported crown restoration or a resin-bonded fixed partial denture. This case report describes the indication of a resin-bonded fixed partial denture, preparation of the abutment teeth and the prosthetic procedures. The technique described here represents a conservative, esthetically pleasing and rapid solution for the missing maxillary central incisor when implant placement and/or guided bone regeneration techniques are not feasible because of financial, social or time restrictions. In this case a 16 year-old female patient who lost her maxillary left central incisor six years ago in a bicycle accident applied to our clinic with a major complaint of her unaesthetic appearance associated with the loss of her maxillary left central incisor. Although there was an indication for orthodontic treatment because of the limited space at the traumatized area, the patient did not accept to receive any orthodontic procedure. That is why an implant supported restoration could not be an option for the narrow area. Therefore maryland bridge as a minimal invasive dental therapy was preferred as a retention appliance so the patient's aesthetic appearance was restored.

Keywords: Maryland bridge, single tooth restoration, aesthetics, maxillary central incisors

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Authors: M. Sagarika, M. Chandra Sekhar

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Agricultural residues are producing in large quantities in India and account for abundant but underutilized source of renewable biomass in agriculture. In India, the amount of crop residues available is estimated to be approximately 686 million tons. Anaerobic digestion is a promising option to utilize the surplus agricultural residues and can produce biogas and digestate. Biogas is mainly methane (CH4), which can be utilized as an energy source in replacement for fossil fuels such as natural gas, oil, in other hand, digestate contains high amounts of nutrients, can be employed as fertilizer. Solid state anaerobic digestion (total solids ≥ 15%) is suitable for agricultural residues, as it reduces the problems like stratification and floating issues that occur in liquid anaerobic digestion (total solids < 15%). The major concern in solid-state anaerobic digestion is the low mass transfer of feedstock and inoculum that resulting in low performance. To resolve this low mass transfer issue, effective mixing of feedstock and inoculum is required. Mechanical mixing using stirrer at the time of digestion process can be done, but it is difficult to operate the stirring of feedstock with high solids percentage and high viscosity. Complete premixing of feedstock and inoculum is an alternative method, which is usual in lab scale studies but may not be affordable due to high energy demand in large-scale digesters. Developing partial premixing methods may reduce this problem. Current study is to improve the performance of solid-state anaerobic digestion of corn stover at feedstock to inoculum ratios 3 and 5, by applying partial premixing methods and to compare the complete premixing method with two partial premixing methods which are two alternative layers of feedstock and inoculum and three alternative layers of feedstock and inoculum where higher inoculum ratios in the top layers. From experimental studies it is observed that, partial premixing method with three alternative layers of feedstock and inoculum yielded good methane.

Keywords: anaerobic digestion, premixing methods, methane yield, corn stover, volatile solids

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Authors: Miang Hong Ngerng, Noor Diyana Jasme, May Jin Theong

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Volatile market environment is inevitable. Fund managers are struggling to choose the right strategy to survive and overcome uncertainties and adverse market movement. Therefore, finding certainty in the mist of uncertainty future is one of the key performance objectives for fund managers. Current available theoretical results are not practical due to strong reliance on the investment assumption made. This paper is to identify the component that can be forecasted in Ex-ante setting which is the realistic situation facing a fund manager in the actual execution of asset allocation in portfolio management. Partial lease square method was used to generate an index with 10 years accounting data from 191 companies listed in KLSE. The result shows that the index reflects the inner nature of the business and up to 30% of the stock return can be explained by the index.

Keywords: active portfolio management, asset allocation ex-ante investment, asset class, partial lease square

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Authors: Hsin-Hung Lin, Janet Chang, Te-Yi Chang, You-Sheng Huang

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The natural and men-made disasters have become huge challenges for tourism destinations as well as emphasizing the fragility of the industry. Hot springs, among all destinations, are prone to disasters due to their dependence on natural resources and locations. After the COVID-19 outbreak, hot spring destinations have experienced not only the loss of businesses but also the psychological trauma. However, evidence has also shown that the impacts may not necessarily reduce the resilience for people but may be converted into posttraumatic growth. In Taiwan, a large proportion of hot springs are located in rural or indigenous areas. As a result, hot spring resources are associated with community cohesion for local residents. Yet prior research on hot spring destinations has mainly focused on visitors, whereas residents have been overlooked. More specifically, the relationship between hot springs resources and resident resilience in the face of the COVID-19 impacts remains unclear. To fulfill this knowledge gap, this paper aims to explore the COVID-19 impacts on residents’ hot spring experiences as well as individual and community resilience from the perspective of posttraumatic growth. A total of 315 residents of 13 hot spring destinations that are most popular in Taiwan were recruited. Online questionnaires were distributed over travel forums and social networks after the COVID-19. This paper subsequently used Partial Least Squares Structural Equation Modeling for data analysis as the technique offers significant advantages in addressing nonnormal data and small sample sizes. A preliminary test was conducted, and the results showed acceptable internal consistency and no serious common method variance. The path analysis demonstrated that the COVID-19 impacts strengthened residents’ perceptions of hot spring resources and experiences, implying that the pandemic had propelled the residents to visit hot springs for the healing benefits. In addition, the COVID-19 impacts significantly enhanced residents’ individual and community resilience, which indicates that the residents at hot springs are more resilient thanks to their awareness of external risks. Thirdly, residents’ individual resilience was positively associated with hot spring experiences, while community resilience was not affected by hot spring experiences. Such findings may suggest that hot spring experiences are more related to individual-level experiences and, consequently, have insignificant influence on community resilience. Finally, individual resilience was proved to be the most relevant factor that help foster community resilience. To conclude, the authorities may consider exploiting the hot spring resources so as to increase individual resilience for local residents. Such implications can be used as a reference for other post-disaster tourist destinations as well. As for future research, longitudinal studies with qualitative methods are suggested to better understand how the hot spring experiences have changed individuals and communities over the long term. It should be noted that the main subjects of this paper were focused on the hot spring communities in Taiwan. Therefore, the results cannot be generalized for all types of tourism destinations. That is, more diverse tourism destinations may be investigated to provide a broader perspective of post-disaster recovery.

Keywords: community resilience, hot spring destinations, individual resilience, posttraumatic growth

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Authors: Hung-Chu Chen, Han Qi, Bauke de Vries

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Energy consumption in the urban environment has attracted numerous researches in recent decades. However, it is comparatively rare to find literary works which investigated 3D spatial analysis of urban energy demand modelling. In order to analyze the spatial correlation between urban morphology and energy demand comprehensively, this paper investigates their relation by using the spatial regression tool. In addition, the spatial regression tool which is applied in this paper is ordinary least squares regression (OLS) and geographically weighted regression (GWR) model. Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and building volume are explainers of urban morphology, which act as independent variables of Energy-land use (E-L) model. NDBI and NDVI are used as the index to describe five types of land use: urban area (U), open space (O), artificial green area (G), natural green area (V), and water body (W). Accordingly, annual electricity, gas demand and energy demand are dependent variables of the E-L model. Based on the analytical result of E-L model relation, it revealed that energy demand and urban morphology are closely connected and the possible causes and practical use are discussed. Besides, the spatial analysis methods of OLS and GWR are compared.

Keywords: energy demand model, geographically weighted regression, normalized difference built-up index, normalized difference vegetation index, spatial statistics

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Authors: Hsin-Hung Lin, Janet Chang, Te-Yi Chang, You-Sheng Huang

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The natural and men-made disasters have become huge challenges for tourism destinations as well as emphasizing the fragility of the industry. Hot springs, among all destinations, are prone to disasters due to their dependence on natural resources and locations. After the COVID-19 outbreak, hot spring destinations have experienced not only the loss of businesses but also the psychological trauma. However, evidence has also shown that the impacts may not necessarily reduce the resilience for people but may be converted into posttraumatic growth. In Taiwan, a large proportion of hot springs are located in rural or indigenous areas. As a result, hot spring resources are associated with community cohesion for local residents. Yet prior research on hot spring destinations has mainly focused on visitors, whereas residents have been overlooked. More specifically, the relationship between hot springs resources and resident resilience in the face of the COVID-19 impacts remains unclear. To fulfill this knowledge gap, this paper aims to explore the COVID-19 impacts on residents’ hot spring experiences as well as individual and community resilience from the perspective of posttraumatic growth. A total of 315 residents of 13 hot spring destinations that are most popular in Taiwan were recruited. Online questionnaires were distributed over travel forums and social networks after the COVID-19. This paper subsequently used Partial Least Squares Structural Equation Modeling for data analysis as the technique offers significant advantages in addressing nonnormal data and small sample sizes. A preliminary test was conducted, and the results showed acceptable internal consistency and no serious common method variance. The path analysis demonstrated that the COVID-19 impacts strengthened residents’ perceptions of hot spring resources and experiences, implying that the pandemic had propelled the residents to visit hot springs for the healing benefits. In addition, the COVID-19 impacts significantly enhanced residents’ individual and community resilience, which indicates that the residents at hot springs are more resilient thanks to their awareness of external risks. Thirdly, residents’ individual resilience was positively associated with hot spring experiences, while community resilience was not affected by hot spring experiences. Such findings may suggest that hot spring experiences are more related to individual-level experiences and, consequently, have insignificant influence on community resilience. Finally, individual resilience was proved to be the most relevant factor that help foster community resilience. To conclude, the authorities may consider exploiting the hot spring resources so as to increase individual resilience for local residents. Such implications can be used as a reference for other post-disaster tourist destinations as well.As for future research, longitudinal studies with qualitative methods are suggested to better understand how the hot spring experiences have changed individuals and communities over the long term. It should be noted that the main subjects of this paper were focused on the hot spring communities in Taiwan. Therefore, the results cannot be generalized for all types of tourism destinations. That is, more diverse tourism destinations may be investigated to provide a broader perspective of post-disaster recovery.

Keywords: community resilience, hot spring destinations, individual resilience, posttraumatic growth (PTG)

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Authors: Kemal Efe Eseller, Göktuğ Yazici

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Laser-induced breakdown spectroscopy (LIBS) is a rapid optical atomic emission spectroscopy which is used for material identification and analysis with the advantages of in-situ analysis, elimination of intensive sample preparation, and micro-destructive properties for the material to be tested. LIBS delivers short pulses of laser beams onto the material in order to create plasma by excitation of the material to a certain threshold. The plasma characteristics, which consist of wavelength value and intensity amplitude, depends on the material and the experiment’s environment. In the present work, medicine samples’ spectrum profiles were obtained via LIBS. Medicine samples’ datasets include two different concentrations for both paracetamol based medicines, namely Aferin and Parafon. The spectrum data of the samples were preprocessed via filling outliers based on quartiles, smoothing spectra to eliminate noise and normalizing both wavelength and intensity axis. Statistical information was obtained and principal component analysis (PCA) was incorporated to both the preprocessed and raw datasets. The machine learning models were set based on two different train-test splits, which were 70% training – 30% test and 80% training – 20% test. Cross-validation was preferred to protect the models against overfitting; thus the sample amount is small. The machine learning results of preprocessed and raw datasets were subjected to comparison for both splits. This is the first time that all supervised machine learning classification algorithms; consisting of Decision Trees, Discriminant, naïve Bayes, Support Vector Machines (SVM), k-NN(k-Nearest Neighbor) Ensemble Learning and Neural Network algorithms; were incorporated to LIBS data of paracetamol based pharmaceutical samples, and their different concentrations on preprocessed and raw dataset in order to observe the effect of preprocessing.

Keywords: machine learning, laser-induced breakdown spectroscopy, medicines, principal component analysis, preprocessing

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Authors: Sammy Kibor, Filip Huyghe, Marc Kochzius, James Kairo

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Goldstripe Sardinella, Sardinella gibbosa, (Bleeker, 1849) is a commercially and ecologically important small pelagic fish common in the Western Indian Ocean region. The present study aimed to assess genetic diversity and population structure of the species in the Kenya-Tanzania transboundary area using mtDNA and msDNA markers. Some 630 bp sequence in the mitochondrial DNA (mtDNA) Cytochrome C Oxidase I (COI) and five polymorphic microsatellite DNA loci were analyzed. Fin clips of 309 individuals from eight locations within the transboundary area were collected between July and December 2018. The S. gibbosa individuals from the different locations were distinguishable from one another based on the mtDNA variation, as demonstrated with a neighbor-joining tree and minimum spanning network analysis. None of the identified 22 haplotypes were shared between Kenya and Tanzania. Gene diversity per locus was relatively high (0.271-0.751), highest Fis was 0.391. The structure analysis, discriminant analysis of Principal component (DAPC) and the pair-wise (FST = 0.136 P < 0.001) values after Bonferroni correction using five microsatellite loci provided clear inference on genetic differentiation and thus evidence of population structure of S. gibbosa along the Kenya-Tanzania coast. This study shows a high level of genetic diversity and the presence of population structure (Φst =0.078 P < 0.001) resulting to the existence of four populations giving a clear indication of minimum gene flow among the population. This information has application in the designing of marine protected areas, an important tool for marine conservation.

Keywords: marine connectivity, microsatellites, population genetics, transboundary

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Authors: Sizar Abed Mohammed, Zahraa Ghazi Sadeeq

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The use of the classic method, least squares (OLS) to estimate the linear regression parameters, when they are available assumptions, and capabilities that have good characteristics, such as impartiality, minimum variance, consistency, and so on. The development of alternative statistical techniques to estimate the parameters, when the data are contaminated with outliers. These are powerful methods (or resistance). In this paper, three of robust methods are studied, which are: Maximum likelihood type estimate M-estimator, Modified Maximum likelihood type estimate MM-estimator and Least Trimmed Squares LTS-estimator, and their results are compared with OLS method. These methods applied to real data taken from Duhok company for manufacturing furniture, the obtained results compared by using the criteria: Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Mean Sum of Absolute Error (MSAE). Important conclusions that this study came up with are: a number of typical values detected by using four methods in the furniture line and very close to the data. This refers to the fact that close to the normal distribution of standard errors, but typical values in the doors line data, using OLS less than that detected by the powerful ways. This means that the standard errors of the distribution are far from normal departure. Another important conclusion is that the estimated values of the parameters by using the lifeline is very far from the estimated values using powerful methods for line doors, gave LTS- destined better results using standard MSE, and gave the M- estimator better results using standard MAPE. Moreover, we noticed that using standard MSAE, and MM- estimator is better. The programs S-plus (version 8.0, professional 2007), Minitab (version 13.2) and SPSS (version 17) are used to analyze the data.

Keywords: Robest, LTS, M estimate, MSE

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Authors: B. F. Nteumagne, E. Pindza, E. Mare

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We apply Lie symmetries analysis to price and hedge options in the fractional Brownian framework. The reputation of Lie groups is well spread in the area of Mathematical sciences and lately, in Finance. In the presence of transactions costs and under fractional Brownian motions, analytical solutions become difficult to obtain. Lie symmetries analysis allows us to simplify the problem and obtain new analytical solution. In this paper, we investigate the use of symmetries to reduce the partial differential equation obtained and obtain the analytical solution. We then proposed a hedging procedure and calibration technique for these types of options, and test the model on real market data. We show the robustness of our methodology by its application to the pricing of digital options.

Keywords: fractional brownian model, symmetry, transaction cost, option pricing

Procedia PDF Downloads 384

Authors: Jesús Horacio, Alfredo Ollero, Víctor Bouzas-Blanco, Augusto Pérez-Alberti

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Rivers have traditionally been classified, assessed and managed in terms of hydrological, chemical and / or biological criteria. Geomorphological classifications had in the past a secondary role, although proposals like River Styles Framework, Catchment Baseline Survey or Stroud Rural Sustainable Drainage Project did incorporate geomorphology for management decision-making. In recent years many studies have been attracted to the geomorphological component. The geomorphological processes and their associated forms determine the structure of a river system. Understanding these processes and forms is a critical component of the sustainable rehabilitation of aquatic ecosystems. The fluvial auto-classification approach suggests that a river is a self-built natural system, with processes and forms designed to effectively preserve their ecological function (hydrologic, sedimentological and biological regime). Fluvial systems are formed by a wide range of elements with multiple non-linear interactions on different spatial and temporal scales. Besides, the fluvial auto-classification concept is built using data from the river itself, so that each classification developed is peculiar to the river studied. The variables used in the classification are specific stream power and mean grain size. A discriminant analysis showed that these variables are the best characterized processes and forms. The statistical technique applied allows to get an individual discriminant equation for each geomorphological type. The geomorphological classification was developed using sites with high naturalness. Each site is a control point of high ecological and geomorphological quality. The changes in the conditions of the control points will be quickly recognizable, and easy to apply a right management measures to recover the geomorphological type. The study focused on Galicia (NW Spain) and the mapping was made analyzing 122 control points (sites) distributed over eight river basins. In sum, this study provides a method for fluvial geomorphological classification that works as an open and flexible tool underlying the fluvial auto-classification concept. The hydrographic mapping is the visual expression of the results, such that each river has a particular map according to its geomorphological characteristics. Each geomorphological type is represented by a particular type of hydraulic geometry (channel width, width-depth ratio, hydraulic radius, etc.). An alteration of this geometry is indicative of a geomorphological disturbance (whether natural or anthropogenic). Hydrographic mapping is also dynamic because its meaning changes if there is a modification in the specific stream power and/or the mean grain size, that is, in the value of their equations. The researcher has to check annually some of the control points. This procedure allows to monitor the geomorphology quality of the rivers and to see if there are any alterations. The maps are useful to researchers and managers, especially for conservation work and river restoration.

Keywords: fluvial auto-classification concept, mapping, geomorphology, river

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Authors: Muhammad Javed Bhatti, Tariq Ali, Muazz Ali

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Due to growing environmental awareness in Pakistan, the researchers are increasingly turning to assess and analyze properties of industrial waste and finding solutions on using industrial waste as secondary material. Due to industrialization, enormous by-products are produced and to utilize these by-products is the main challenge faced in Pakistan. Induction furnace slag is one of the industrial by-products from the iron and steel making industries. This paper highlights the true utilization of induction furnace slag as partial replacement of fine aggregate. For the experimental investigation, mixes were prepared with fine aggregate replacement using 0 percent, 5 percent, 10 percent, 15 percent, 20 percent, 25 percent, 30 percent, 35 percent and 40 percent induction furnace slag to evaluate the workability, compaction factor, compressive strength, flexural strength, modulus of elasticity.

Keywords: compressive strength, deflection, induction furnace slag, workability

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Authors: Anuar Ishak

Abstract:

The characteristics of stagnation point flow of a nanofluid towards a stretching/shrinking sheet are investigated. The governing partial differential equations are transformed into a set of ordinary differential equations, which are then solved numerically using MATLAB routine boundary value problem solver bvp4c. The numerical results show that dual (upper and lower branch) solutions exist for the shrinking case, while for the stretching case, the solution is unique. A stability analysis is performed to determine the stability of the dual solutions. It is found that the skin friction decreases when the sheet is stretched, but increases when the suction effect is increased. It is also found that increasing the thermophoresis parameter reduces the heat transfer rate at the surface, while increasing the Brownian motion parameter increases the mass transfer rate at the surface.

Keywords: dual solutions, heat transfer, forced convection, nanofluid, stability analysis

Procedia PDF Downloads 394