Search results for: weighted average index

Authors: Ayesha M. Facey

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The evaluation sought to determine the factors associated with the high failure rate among students taking a first-year introductory statistics course. By utilizing Tyler’s Objective Based Model, the main objectives were: to assess the effectiveness of the lecturer’s teaching strategies; to determine the proportion of students who attends lectures and tutorials frequently and to determine the impact of infrequent attendance on performance; to determine how the assigned activities assisted in students understanding of the course content; to ascertain the possible issues being faced by students in understanding the course material and obtain possible solutions to the challenges and to determine whether the learning outcomes have been achieved based on an assessment of the second in-course examination. A quantitative survey research strategy was employed and the study population was students enrolled in semester one of the academic year 2015/2016. A convenience sampling approach was employed resulting in a sample of 98 students. Primary data was collected using self-administered questionnaires over a one-week period. Secondary data was obtained from the results of the second in-course examination. Data were entered and analyzed in SPSS version 22 and both univariate and bivariate analyses were conducted on the information obtained from the questionnaires. Univariate analyses provided description of the sample through means, standard deviations and percentages while bivariate analyses were done using Spearman’s Rho correlation coefficient and Chi-square analyses. For secondary data, an item analysis was performed to obtain the reliability of the examination questions, difficulty index and discriminant index. The examination results also provided information on the weak areas of the students and highlighted the learning outcomes that were not achieved. Findings revealed that students were more likely to participate in lectures than tutorials and that attendance was high for both lectures and tutorials. There was a significant relationship between participation in lectures and performance on examination. However, a high proportion of students has been absent from three or more tutorials as well as lectures. A higher proportion of students indicated that they completed the assignments obtained from the lectures sometimes while they rarely completed tutorial worksheets. Students who were more likely to complete their assignments were significantly more likely to perform well on their examination. Additionally, students faced a number of challenges in understanding the course content and the topics of probability, binomial distribution and normal distribution were the most challenging. The item analysis also highlighted these topics as problem areas. Problems doing mathematics and application and analyses were their major challenges faced by students and most students indicated that some of the challenges could be alleviated if additional examples were worked in lectures and they were given more time to solve questions. Analysis of the examination results showed that a number of learning outcomes were not achieved for a number of topics. Based on the findings recommendations were made that suggested adjustments to grade allocations, delivery of lectures and methods of assessment.

Keywords: evaluation, item analysis, Tyler’s objective based model, university statistics

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Authors: Abhishek S. Shete

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There is nothing new in the use of alcohol made from root crops as a motor fuel. Alcohol is an excellent alternative motor fuel for petrol engines. The reason alcohol fuel has not been fully exploited is that, up until now; gasoline has been cheap, available, and easy to produce. However, nowadays, crude oil is getting scarce, and the historic price difference between alcohol and gasoline is getting narrower. Alcohol fuel can be an important part of the solution for Rwanda because there is tremendous scope to use bulk production of sweet potato into alcohol. The total sweet potato production in both seasons is found to be 1.607.296 tones/year. The average productivity of sweet potato in the country irrespective of seasons is found to be 8.9 tones/ha. If all of the available agricultural surplus were converted to ethanol, alcohol would supply less than 5% of motor fuel needs.

Keywords: root crops, sweet potato, surplus, alcohol

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Authors: Okike Benjamin, Garba E. J. D.

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The researcher has developed a new encryption technique known as Merged Irregular Transposition Cipher. In this cipher method of encryption, a message to be encrypted is split into parts and each part encrypted separately. Before the encrypted message is transmitted to the recipient(s), the positions of the split in the encrypted messages could be swapped to ensure more security. This work seeks to develop a model by considering the split number, S and the average number of characters per split, L as the message under consideration is split from 2 through 10. Again, after developing the model, the error level in the model would be determined.

Keywords: merged irregular transposition, error level, model estimation, message splitting

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Authors: Wesley A. Saltarelli, Nicolas R. Finkler, Adriana C. P. Miwa, Maria C. Calijuri, Davi G. F. Cunha

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The metabolism of the streams is an indicator of ecosystem disturbance due to the influences of the catchment on the structure of the water bodies. The study of the respiration and photosynthesis allows the estimation of energy fluxes through the food webs and the analysis of the autotrophic and heterotrophic processes. We aimed at evaluating the metabolism in streams located in the Brazilian savannah, Cerrado (Sao Carlos, SP), by determining and modeling the daily changes of dissolved oxygen (DO) in the water during one year. Three water bodies with minimal anthropogenic interference in their surroundings were selected, Espraiado (ES), Broa (BR) and Canchim (CA). Every two months, water temperature, pH and conductivity are measured with a multiparameter probe. Nitrogen and phosphorus forms are determined according to standard methods. Also, canopy cover percentages are estimated in situ with a spherical densitometer. Stream flows are quantified through the conservative tracer (NaCl) method. For the metabolism study, DO (PME-MiniDOT) and light (Odyssey Photosynthetic Active Radiation) sensors log data for at least three consecutive days every ten minutes. The reaeration coefficient (k2) is estimated through the method of the tracer gas (SF6). Finally, we model the variations in DO concentrations and calculate the rates of gross and net primary production (GPP and NPP) and respiration based on the one station method described in the literature. Three sampling were carried out in October and December 2015 and February 2016 (the next will be in April, June and August 2016). The results from the first two periods are already available. The mean water temperatures in the streams were 20.0 +/- 0.8C (Oct) and 20.7 +/- 0.5C (Dec). In general, electrical conductivity values were low (ES: 20.5 +/- 3.5uS/cm; BR 5.5 +/- 0.7uS/cm; CA 33 +/- 1.4 uS/cm). The mean pH values were 5.0 (BR), 5.7 (ES) and 6.4 (CA). The mean concentrations of total phosphorus were 8.0ug/L (BR), 66.6ug/L (ES) and 51.5ug/L (CA), whereas soluble reactive phosphorus concentrations were always below 21.0ug/L. The BR stream had the lowest concentration of total nitrogen (0.55mg/L) as compared to CA (0.77mg/L) and ES (1.57mg/L). The average discharges were 8.8 +/- 6L/s (ES), 11.4 +/- 3L/s and CA 2.4 +/- 0.5L/s. The average percentages of canopy cover were 72% (ES), 75% (BR) and 79% (CA). Significant daily changes were observed in the DO concentrations, reflecting predominantly heterotrophic conditions (respiration exceeded the gross primary production, with negative net primary production). The GPP varied from 0-0.4g/m2.d (in Oct and Dec) and the R varied from 0.9-22.7g/m2.d (Oct) and from 0.9-7g/m2.d (Dec). The predominance of heterotrophic conditions suggests increased vulnerability of the ecosystems to artificial inputs of organic matter that would demand oxygen. The investigation of the metabolism in the pristine streams can help defining natural reference conditions of trophic state.

Keywords: low-order streams, metabolism, net primary production, trophic state

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Authors: Xianghong Lu, Yuejun Wang, Chengshi Gan, Xin Qian

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The North Sulawesi Arc, located on the east of Indonesia and to the south of the Celebes Sea, is the north part of the K-shape of Sulawesi Island and has a complex tectonic history since the Cenozoic due to the convergence of three plates (Eurasia, India-Australia and Pacific plates). Published rock records contain less precise chronology, mostly using K-Ar dating, and rare geochemistry data, which limit the understanding of the regional tectonic setting. This study presents detailed zircon U-Pb geochronological and Hf-O isotope and whole-rock geochemical analyses for the Na-rich granites from the North Sulawesi Arc. Zircon U-Pb geochronological analyses of three representative samples yield weighted mean ages of 30.4 ± 0.4 Ma, 29.5 ± 0.2 Ma, and 27.3 ± 0.4 Ma, respectively, revealing the Oligocene magmatism in the North Sulawesi Arc. The samples have high Na₂O and low K₂O contents with high Na₂O/K₂O ratios, belonging to Low-K tholeiitic Na-rich granites. The Na-rich granites are characterized by high SiO₂ contents (75.05-79.38 wt.%) and low MgO contents (0.07-0.91 wt.%) and show arc-like trace elemental signatures. They have low (⁸⁷Sr/⁸⁶Sr)i ratios (0.7044-0.7046), high εNd(t) values (from +5.1 to +6.6), high zircon εHf(t) values (from +10.1 to +18.8) and low zircon δ18O values (3.65-5.02). They show an Indian-Ocean affinity of Pb isotopic compositions with ²⁰⁶Pb/²⁰⁴Pb ratio of 18.16-18.37, ²⁰⁷Pb/²⁰⁴Pb ratio of 15.56-15.62, and ²⁰⁸Pb/²⁰⁴Pb ratio of 38.20-38.66. These geochemical signatures suggest that the Oligocene Na-rich granites from the North Sulawesi Arc formed by partial melting of the juvenile oceanic crust with sediment-derived fluid-related metasomatism in a subducting setting and support an intra-oceanic arc origin. Combined with the published study, the emergence of extensive calc-alkaline felsic arc magmatism can be traced back to the Early Oligocene period, subsequent to the Eocene back-arc basalts (BAB) that share similarity with the Celebes Sea basement. Since the opening of the Celebes Sea started from the Eocene (42~47 Ma) and stopped by the Early Oligocene (~32 Ma), the geodynamical mechanism of the formation of the Na-rich granites from the North Sulawesi Arc during the Oligocene might relate to the subduction of the Indian Ocean.

Keywords: North Sulawesi Arc, oligocene, Na-rich granites, in-situ zircon Hf–O analysis, intra-oceanic origin

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Authors: Katherine Dropiewski, Michael Yakimov, Vadim Tokranov, Allan Minns, Pavel Murat, Serge Oktyabrsky

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InAs Quantum Dots (QDs) in a GaAs matrix is a well-documented luminescent material with high light yield, as well as thermal and ionizing radiation tolerance due to quantum confinement. These benefits can be leveraged for high-efficiency, room temperature scintillation detectors. The proposed scintillator is composed of InAs QDs acting as luminescence centers in a GaAs stopping medium, which also acts as a waveguide. This system has appealing potential properties, including high light yield (~240,000 photons/MeV) and fast capture of photoelectrons (2-5ps), orders of magnitude better than currently used inorganic scintillators, such as LYSO or BaF2. The high refractive index of the GaAs matrix (n=3.4) ensures light emitted by the QDs is waveguided, which can be collected by an integrated photodiode (PD). Scintillation structures were grown using Molecular Beam Epitaxy (MBE) and consist of thick GaAs waveguiding layers with embedded sheets of modulation p-type doped InAs QDs. An AlAs sacrificial layer is grown between the waveguide and the GaAs substrate for epitaxial lift-off to separate the scintillator film and transfer it to a low-index substrate for waveguiding measurements. One consideration when using a low-density material like GaAs (~5.32 g/cm³) as a stopping medium is the matrix thickness in the dimension of radiation collection. Therefore, luminescence properties of very thick (4-20 microns) waveguides with up to 100 QD layers were studied. The optimization of the medium included QD shape, density, doping, and AlGaAs barriers at the waveguide surfaces to prevent non-radiative recombination. To characterize the efficiency of QD luminescence, low temperature photoluminescence (PL) (77-450 K) was measured and fitted using a kinetic model. The PL intensity degrades by only 40% at RT, with an activation energy for electron escape from QDs to the barrier of ~60 meV. Attenuation within the waveguide (WG) is a limiting factor for the lateral size of a scintillation detector, so PL spectroscopy in the waveguiding configuration was studied. Spectra were measured while the laser (630 nm) excitation point was scanned away from the collecting fiber coupled to the edge of the WG. The QD ground state PL peak at 1.04 eV (1190 nm) was inhomogeneously broadened with FWHM of 28 meV (33 nm) and showed a distinct red-shift due to self-absorption in the QDs. Attenuation stabilized after traveling over 1 mm through the WG, at about 3 cm⁻¹. Finally, a scintillator sample was used to test detection and evaluate timing characteristics using 5.5 MeV alpha particles. With a 2D waveguide and a small area of integrated PD, the collected charge averaged 8.4 x10⁴ electrons, corresponding to a collection efficiency of about 7%. The scintillation response had 80 ps noise-limited time resolution and a QD decay time of 0.6 ns. The data confirms unique properties of this scintillation detector which can be potentially much faster than any currently used inorganic scintillator.

Keywords: GaAs, InAs, molecular beam epitaxy, quantum dots, III-V semiconductor

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Authors: Rabah Bensaha, Badreddine Toubal

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We investigate the structural, optical and magnetic properties of TiO2, Co-doped TiO2, Ni-doped TiO2 and Co-Ni co-doped TiO2 thin films prepared by the sol-gel dip coating method. Fully anatase phase was obtained by adding metal ions without any detectable impurity phase or oxide formed. AFM and SEM micrographs clearly confirm that the addition of Co-Ni affects the shape of anatase nanoparticles. The crystallite sizes and surface roughness of TiO2 films increase with Co-doping, Ni-doping and Co–Ni co-doping, respectively. The refractive index, thickness and optical band gap values of the films were obtained by means of optical transmittance spectra measurements. The band gap of TiO2 sample was decreased by Co-doping, Ni-doping and Co–Ni co-doping TiO2 films. Both undoped and Co-Ni co-doped films were found to be ferromagnetic at room temperature may due to the presence of oxygen vacancy defect and the probable formation of metal clusters Co-Ni.

Keywords: Co-Ni co-doped, anatase TiO2, ferromagnetic, sol-gel method, thin films

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Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

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Authors: Aliyu Ahmad Aliyu, Abubakar Ahmad, Muhammad Umar Bello, Rozilah Kasim, David Martin

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The article studied the application of facilities management practice in high rise commercial properties. Convenience sampling technique was used in administering questionnaires to the 60 respondents who responded to the survey. It was found out that the extent of application of facilities management in the subject properties is better described as below average. Similarly, the most frequently tools of facilities management in use and employed in the properties were outsourcing and in-house sourcing. This was influenced by the level of their familiarity with the tools. Planned and Preventive maintenance should be taken regularly in other to enhance the effectiveness of the facilities management and to satisfy both the owner and customers of the organization.

Keywords: commercial properties, facilities management, high-rise buildings, Jos metropolis and outsourcing

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Authors: Bernadette F. De La Cruz, Susan Marie R. Dela Cruz, Georgia D. Demavibas

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Pantawid Pamilyang Pilipino Program (4P) is a conditional cash transfer program in the Philippines pay extremely poor household-beneficiaries in order to fulfill the country’s commitment to the number one of the Millennium Development Goals (MDG). 4P's send 10,235,256 school children aged 6-18 from a total of 4,353,597 registered households with an average of two to three children. We analyze this program in Iloilo, Philippines. We show that this program can be made efficient by selecting beneficiaries and calibrating transfer for a maximum breaking of intergenerational poverty cycle of hunger, health and achieve higher education.

Keywords: ESGP-PA, millennium development goals, house hold beneficiaries, cash transfer

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Authors: Razieh Esfandiarisedgh

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Community architecture has been proposed as an alternative approach in architecture, with three political, sociological, and psychological approaches. In community architecture, the psychological approach, as the only approach related to community design, has an important index called a sense of community. Changes in today's modern society, such as the shrinking of families, cause a decrease in the sense of community and unwillingness of people. It has become a residential complex to be present in public spaces. This issue can be increased by creating motivation with the help of design for the presence and participation of people in public spaces and taking advantage of the facilities and quality of these spaces. This research used the qualitative research method, studied and collected information, and used observation and interviews in the selected sample. Through targeted sampling and matching it with the extracted design table, it was concluded that climate and culture are known as two important factors in the collective view of housing in Hamedan.

Keywords: community architecture, sense of community, environmental psychology, architecture

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Authors: Arlene López-Sampson, Tony Page, Betsy Jackes

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Aquilaria genus produces a highly valuable fragrant oleoresin known as agarwood. Agarwood forms in a few trees in the wild as a response to injure or pathogen attack. The resin is used in perfume and incense industry and medicine. Cultivation of Aquilaria species as a sustainable source of the resin is now a common strategy. Physiological traits are frequently used as a proxy of crop and tree productivity. Aquilaria species growing in Queensland, Australia were studied to investigate relationship between leaf-productivity traits with tree growth. Specifically, 28 trees, representing 12 plus trees and 16 trees from yield plots, were selected to conduct carbon isotope analysis (δ13C) and monitor six leaf attributes. Trees were grouped on four diametric classes (diameter at 150 mm above ground level) ensuring the variability in growth of the whole population was sampled. Model averaging technique based on the Akaike’s information criterion (AIC) was computed to identify whether leaf traits could assist in diameter prediction. Carbon isotope values were correlated with height classes and leaf traits to determine any relationship. In average four leaves per shoot were recorded. Approximately one new leaf per week is produced by a shoot. Rate of leaf expansion was estimated in 1.45 mm day-1. There were no statistical differences between diametric classes and leaf expansion rate and number of new leaves per week (p > 0.05). Range of δ13C values in leaves of Aquilaria species was from -25.5 ‰ to -31 ‰ with an average of -28.4 ‰ (± 1.5 ‰). Only 39% of the variability in height can be explained by δ13C in leaf. Leaf δ13C and nitrogen content values were positively correlated. This relationship implies that leaves with higher photosynthetic capacities also had lower intercellular carbon dioxide concentrations (ci/ca) and less depleted values of 13C. Most of the predictor variables have a weak correlation with diameter (D). However, analysis of the 95% confidence of best-ranked regression models indicated that the predictors that could likely explain growth in Aquilaria species are petiole length (PeLen), values of δ13C (true13C) and δ15N (true15N), leaf area (LA), specific leaf area (SLA) and number of new leaf produced per week (NL.week). The model constructed with PeLen, true13C, true15N, LA, SLA and NL.week could explain 45% (R2 0.4573) of the variability in D. The leaf traits studied gave a better understanding of the leaf attributes that could assist in the selection of high-productivity trees in Aquilaria.

Keywords: 13C, petiole length, specific leaf area, tree growth

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Authors: Watheq Mansour, Waleed Bin Owais, Mohammad Basheer Kotit, Khaled Khan

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Efficient query processing is one of the utmost requisites in any business environment to satisfy consumer needs. This paper investigates the various types of indexing models, viz. primary, secondary, and multi-level. The investigation is done under the ambit of various types of queries to which each indexing model performs with efficacy. This study also discusses the inherent advantages and disadvantages of each indexing model and how indexing models can be chosen based on a particular environment. This paper also draws parallels between various indexing models and provides recommendations that would help a Database administrator to zero-in on a particular indexing model attributed to the needs and requirements of the production environment. In addition, to satisfy industry and consumer needs attributed to the colossal data generation nowadays, this study has proposed two novel indexing techniques that can be used to index highly unstructured and structured Big Data with efficacy. The study also briefly discusses some best practices that the industry should follow in order to choose an indexing model that is apposite to their prerequisites and requirements.

Keywords: indexing, hashing, latent semantic indexing, B-tree

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Authors: Ayesha Mushtaq

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Asthma is a pulmonary disease in which blockade of the airway takes place due to inflammation as a response to certain allergens. Breathing troubles, cough, and dyspnea are one of the few symptoms. Several studies have indicated a significant effect on asthma due to changes in dietary routines. Certain food items, such as oily foods and other materials, are known to cause an increase in the symptoms of asthma. Low dietary intake of fruits and vegetables may be important in relation to asthma prevalence. The objective of this study is to assess and compare the nutritional status of asthmatic and non-asthmatic patients. The significance of this study lies in the factor that it will help nutritionists to arrange a feasible dietary routine for asthmatic patients. This research was conducted at the Pulmonology Department of the Pakistan Institute of Medical Science Islamabad. About thirty hundred thirty-four million people are affected by asthma worldwide. Pakistan is on the verge of being an uplifted urban population and asthma cases are increasingly high these days. Several studies suggest an increase in the Asthmatic patient population due to improper diet. This is a cross-sectional study aimed at assessing the nutritious standing of Asthmatic and non-asthmatic patients. This research took place at the Pakistan Institute of Medical Sciences (PIMS), Islamabad, Pakistan. The research included asthmatic and non-asthmatic patients coming to the pulmonology department clinic at the Pakistan Institute of Medical Sciences (PIMS). These patients were aged between 20-60 years. A questionnaire was developed for these patients to estimate their dietary plans in these patients. The methodology included four sections. The first section was the Socio-Demographic profile, which included age, gender, monthly income and occupation. The next section was anthropometric measurements which included the weight, height and body mass index (BMI) of an individual. The next section, section three, was about the biochemical attributes, such as for biochemical profiling, pulmonary function testing (PFT) was performed. In the next section, Dietary habits were assessed by a food frequency questionnaire (FFQ) through food habits and consumption pattern was assessed. The next section life style data, in which the person's level of physical activity, sleep and smoking habits were assessed. The next section was statistical analysis. All the data obtained from the study were statistically analyzed and assessed. Most of the asthma Patients were females, with weight more than normal or even obese. Body Mass Index (BMI) was higher in asthma Patients than those in non-Asthmatic ones. When the nutritional Values were assessed, we came to know that these patients were low on certain nutrients and their diet included more junk and oily food than healthy vegetables and fruits. Beverages intake was also included in the same assessment. It is evident from this study that nutritional status has a contributory effect on asthma. So, patients on the verge of developing asthma or those who have developed asthma should focus on their diet, maintain good eating habits and take healthy diets, including fruits and vegetables rather than oily foods. Proper sleep may also contribute to the control of asthma.

Keywords: BMI, nutrition, PAL, diet

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Authors: Safaa M. Hassan; Safwat S. Gabr, Mohamed F. Sadek

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This study is proposed for the lithological and iron oxides detection in the old mine areas of El-Bahariya Depression, Western Desert, using ASTER and Landsat-8 remote sensing data. Four old iron ore occurrences, namely; El-Gedida, El-Haraa, Ghurabi, and Nasir mine areas found in the El-Bahariya area. This study aims to find new high potential areas for iron mineralization around El-Baharyia depression. Image processing methods such as principle component analysis (PCA) and band ratios (b4/b5, b5/b6, b6/b7, and 4/2, 6/7, band 6) images were used for lithological identification/mapping that includes the iron content in the investigated area. ASTER and Landsat-8 visible and short-wave infrared data found to help mapping the ferruginous sandstones, iron oxides as well as the clay minerals in and around the old mines area of El-Bahariya depression. Landsat-8 band ratio and the principle component of this study showed well distribution of the lithological units, especially ferruginous sandstones and iron zones (hematite and limonite) along with detection of probable high potential areas for iron mineralization which can be used in the future and proved the ability of Landsat-8 and ASTER data in mapping these features. Minimum Noise Fraction (MNF), Mixture Tuned Matched Filtering (MTMF), pixel purity index methods as well as Spectral Ange Mapper classifier algorithm have been successfully discriminated the hematite and limonite content within the iron zones in the study area. Various ASTER image spectra and ASD field spectra of hematite and limonite and the surrounding rocks are compared and found to be consistent in terms of the presence of absorption features at range from 1.95 to 2.3 μm for hematite and limonite. Pixel purity index algorithm and two sub-pixel spectral methods, namely Mixture Tuned Matched Filtering (MTMF) and matched filtering (MF) methods, are applied to ASTER bands to delineate iron oxides (hematite and limonite) rich zones within the rock units. The results are validated in the field by comparing image spectra of spectrally anomalous zone with the USGS resampled laboratory spectra of hematite and limonite samples using ASD measurements. A number of iron oxides rich zones in addition to the main surface exposures of the El-Gadidah Mine, are confirmed in the field. The proposed method is a successful application of spectral mapping of iron oxides deposits in the exposed rock units (i.e., ferruginous sandstone) and present approach of both ASTER and ASD hyperspectral data processing can be used to delineate iron-rich zones occurring within similar geological provinces in any parts of the world.

Keywords: Landsat-8, ASTER, lithological mapping, iron exploration, western desert

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Authors: Khadidja Bellifa, Sidi Mohamed Mekelleche

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Phenols and especially halogenated phenols represent a substantial part of the chemicals produced worldwide and are known as aquatic pollutants. Quantitative structure–toxicity relationship (QSTR) models are useful for understanding how chemical structure relates to the toxicity of chemicals. In the present study, the acute toxicities of 45 halogenated phenols to Tetrahymena Pyriformis are estimated using no cost semi-empirical quantum chemistry methods. QSTR models were established using the multiple linear regression technique and the predictive ability of the models was evaluated by the internal cross-validation, the Y-randomization and the external validation. Their structural chemical domain has been defined by the leverage approach. The results show that the best model is obtained with the AM1 method (R²= 0.91, R²CV= 0.90, SD= 0.20 for the training set and R²= 0.96, SD= 0.11 for the test set). Moreover, all the Tropsha’ criteria for a predictive QSTR model are verified.

Keywords: halogenated phenols, toxicity mechanism, hydrophobicity, electrophilicity index, quantitative stucture-toxicity relationships

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Authors: Daijun Chen

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Affordable housing is subsidized by the government to meet the housing demand of low and middle-income urban residents in the process of urbanization and to alleviate the housing inequality caused by market-based housing reforms. It is a recognized fact that the living conditions of the insured have been improved while constructing the subsidized housing. However, the choice of affordable housing is mostly in the suburbs, where the surrounding urban functions and infrastructure are incomplete, resulting in the spatial mismatch of "jobs-housing" in affordable housing. The main reason for this problem is that the residents of affordable housing are more sensitive to the spatial location of their residence, but their selectivity and controllability to the housing location are relatively weak, which leads to higher commuting costs. Their real cost of living has not been effectively reduced. In this regard, 92 subsidized housing communities in Nanjing, China, are selected as the research sample in this paper. The residents of the affordable housing and their commuting Spatio-temporal behavior characteristics are identified based on the LBS (location-based service) data. Based on the spatial mismatch theory, spatial mismatch indicators such as commuting distance and commuting time are established to measure the spatial mismatch degree of subsidized housing in different districts of Nanjing. Furthermore, the geographically weighted regression model is used to analyze the influencing factors of the spatial mismatch of affordable housing in terms of the provision of employment opportunities, traffic accessibility and supporting service facilities by using spatial, functional and other multi-source Spatio-temporal big data. The results show that the spatial mismatch of affordable housing in Nanjing generally presents a "concentric circle" pattern of decreasing from the central urban area to the periphery. The factors affecting the spatial mismatch of affordable housing in different spatial zones are different. The main reasons are the number of enterprises within 1 km of the affordable housing district and the shortest distance to the subway station. And the low spatial mismatch is due to the diversity of services and facilities. Based on this, a spatial optimization strategy for different levels of spatial mismatch in subsidized housing is proposed. And feasible suggestions for the later site selection of subsidized housing are also provided. It hopes to avoid or mitigate the impact of "spatial mismatch," promote the "spatial adaptation" of "jobs-housing," and truly improve the overall welfare level of affordable housing residents.

Keywords: affordable housing, spatial mismatch, commuting characteristics, spatial adaptation, welfare benefits

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Authors: Kristina Pflug, Markus Busch

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Being able to predict polymer properties and processing behavior based on the applied operating reaction conditions in one of the key challenges in modern polymer reaction engineering. Especially, for cost-intensive processes such as the high-pressure polymerization of low-density polyethylene (LDPE) with high safety-requirements, the need for simulation-based process optimization and product design is high. A multi-scale modelling approach was set-up and validated via a series of high-pressure mini-plant autoclave reactor experiments. The approach starts with the numerical modelling of the complex reaction network of the LDPE polymerization taking into consideration the actual reaction conditions. While this gives average product properties, the complex polymeric microstructure including random short- and long-chain branching is calculated via a hybrid Monte Carlo-approach. Finally, the processing behavior of LDPE -its melt flow behavior- is determined in dependence of the previously determined polymeric microstructure using the branch on branch algorithm for randomly branched polymer systems. All three steps of the multi-scale modelling approach can be independently validated against analytical data. A triple-detector GPC containing an IR, viscosimetry and multi-angle light scattering detector is applied. It serves to determine molecular weight distributions as well as chain-length dependent short- and long-chain branching frequencies. 13C-NMR measurements give average branching frequencies, and rheological measurements in shear and extension serve to characterize the polymeric flow behavior. The accordance of experimental and modelled results was found to be extraordinary, especially taking into consideration that the applied multi-scale modelling approach does not contain parameter fitting of the data. This validates the suggested approach and proves its universality at the same time. In the next step, the modelling approach can be applied to other reactor types, such as tubular reactors or industrial scale. Moreover, sensitivity analysis for systematically varying process conditions is easily feasible. The developed multi-scale modelling approach finally gives the opportunity to predict and design LDPE processing behavior simply based on process conditions such as feed streams and inlet temperatures and pressures.

Keywords: low-density polyethylene, multi-scale modelling, polymer properties, reaction engineering, rheology

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Authors: Mohammadamin Hashemi, Mohammadreza Kashizadeh

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Droughts pose a significant threat to sustainable water resource management, agriculture, and socioeconomic sectors, particularly in the field of climate change. This study investigates drought simulation using rainfall-runoff modelling in the Cuneo district, Italy, over the past 60-year period. The study leverages the TUW model, a lumped conceptual rainfall-runoff model with a semi-distributed operation capability. Similar in structure to the widely used Hydrologiska Byråns Vattenbalansavdelning (HBV) model, the TUW model operates on daily timesteps for input and output data specific to each catchment. It incorporates essential routines for snow accumulation and melting, soil moisture storage, and streamflow generation. Multiple catchments' discharge data within the Cuneo district form the basis for thorough model calibration employing the Kling-Gupta Efficiency (KGE) metric. A crucial metric for reliable drought analysis is one that can accurately represent low-flow events during drought periods. This ensures that the model provides a realistic picture of water availability during these critical times. Subsequent validation of monthly discharge simulations thoroughly evaluates overall model performance. Beyond model development, the investigation delves into drought analysis using the robust Standardized Runoff Index (SRI). This index allows for precise characterization of drought occurrences within the study area. A meticulous comparison of observed and simulated discharge data is conducted, with particular focus on low-flow events that characterize droughts. Additionally, the study explores the complex interplay between land characteristics (e.g., soil type, vegetation cover) and climate variables (e.g., precipitation, temperature) that influence the severity and duration of hydrological droughts. The study's findings demonstrate successful calibration of the TUW model across most catchments, achieving commendable model efficiency. Comparative analysis between simulated and observed discharge data reveals significant agreement, especially during critical low-flow periods. This agreement is further supported by the Pareto coefficient, a statistical measure of goodness-of-fit. The drought analysis provides critical insights into the duration, intensity, and severity of drought events within the Cuneo district. This newfound understanding of spatial and temporal drought dynamics offers valuable information for water resource management strategies and drought mitigation efforts. This research deepens our understanding of drought dynamics in the Cuneo region. Future research directions include refining hydrological modelling techniques and exploring future drought projections under various climate change scenarios.

Keywords: hydrologic extremes, hydrological drought, hydrological modelling, machine learning, rainfall-runoff modelling

Procedia PDF Downloads 37

Authors: O. G. Onuk, L. S. Taura, C. M. Eze, S. M. Ngaram

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The decay chain of radioactive elements in the laboratory and the verification of natural radioactivity of the human body was investigated using the High Purity Germanium (HPGe) detector. Properties of the HPGe detectors were also investigated. The efficiency and energy resolution of HPGe detector used in the laboratory was found to be excellent. The detector was calibrated three times so as to cover a wider energy range. Also the Centroid C of the detector was found to have a linear relationship with the energies of the known gamma-rays. Using the three calibrations of the detector, the energy of an unknown radionuclide was found to follow the decay chain of thorium-232 (232Th) and it was also found that an average adult has about 2.5g Potasium-40 (40K) in the body.

Keywords: detector, efficiency, energy, radionuclides, resolution

Procedia PDF Downloads 245

Authors: Sultan Z. Mahmud, Emily C. Graff, Adil Bashir

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Phosphoprotein enriched in astrocytes 15 kDa (PEA-15) is a multifunctional adapter protein which is associated with the regulation of apoptotic cell death. Recently it has been discovered that PEA-15 is crucial in normal neurodevelopment of domestic cats, a gyrencephalic animal model, although the exact function of PEA-15 in neurodevelopment is unknown. This study investigates how PEA-15 affects the blood-brain barrier (BBB) permeability in cat brain, which can cause abnormalities in tissue metabolite and energy supplies. Severe polymicrogyria and microcephaly have been observed in cats with a loss of function PEA-15 mutation, affecting the normal neurodevelopment of the cat. This suggests that the vital role of PEA-15 in neurodevelopment is associated with gyrification. Neurodevelopment is a highly energy demanding process. The mammalian brain depends on glucose as its main energy source. PEA-15 plays a very important role in glucose uptake and utilization by interacting with phospholipase D1 (PLD1). Mitochondria also plays a critical role in bioenergetics and essential to supply adequate energy needed for neurodevelopment. Cerebral blood flow regulates adequate metabolite supply and recent findings also showed that blood plasma contains mitochondria as well. So the BBB can play a very important role in regulating metabolite and energy supply in the brain. In this study the blood-brain permeability in cat brain was measured using MRI magnetization transfer (MT) effect on the perfusion signal. Perfusion is the tissue mass normalized supply of blood to the capillary bed. Perfusion also accommodates the supply of oxygen and other metabolites to the tissue. A fraction of the arterial blood can diffuse to the tissue, which depends on the BBB permeability. This fraction is known as water extraction fraction (EF). MT is a process of saturating the macromolecules, which has an effect on the blood that has been diffused into the tissue while having minimal effect on intravascular blood water that has not been exchanged with the tissue. Measurement of perfusion signal with and without MT enables to estimate the microvascular blood flow, EF and permeability surface area product (PS) in the brain. All the experiments were performed with Siemens 7T Magnetom with 32 channel head coil. Three control cats and three PEA-15 mutant cats were used for the study. Average EF in white and gray matter was 0.9±0.1 and 0.86±0.15 respectively, perfusion in white and gray matter was 85±15 mL/100g/min and 97±20 mL/100g/min respectively, PS in white and gray matter was 201±25 mL/100g/min and 225±35 mL/100g/min respectively for control cats. For PEA-15 mutant cats, average EF in white and gray matter was 0.81±0.15 and 0.77±0.2 respectively, perfusion in white and gray matter was 140±25 mL/100g/min and 165±18 mL/100g/min respectively, PS in white and gray matter was 240±30 mL/100g/min and 259±21 mL/100g/min respectively. This results show that BBB is compromised in PEA-15 mutant cat brain, where EF is decreased and perfusion as well as PS are increased in the mutant cats compared to the control cats. This findings might further explain the function of PEA-15 in neurodevelopment.

Keywords: BBB, cat brain, magnetization transfer, PEA-15

Procedia PDF Downloads 137

Authors: Ratanavadee Takerngsukvatana

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The purposes of this research were to study reading behavior of undergraduate students at Suan Sunandha Rajabhat University. A stratified random sample of 380 participants was collected. A Likert five-scale questionnaire was developed to collect data and to obtain students’ opinions regarding their reading behavior. The findings revealed that the majority of respondents read mainly for academic purpose. They preferred to read magazines. The majority of respondents read an average of 3-7 pages a day. The places to read were home and library. Buying with their own money and borrowing from the library were two main sources of books. The suggested activity to promote is planning the curriculum to suit students’ reading behavior.

Keywords: reading, reading behavior, undergraduate students, Suan Sunandha Rajabhat University

Procedia PDF Downloads 293

Authors: Fatima Sohail, Faizan Iftikhar

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This paper studies the relationship between digital finance, renewable energy, and the economic development of Pakistan and least developed countries from 2000 to 2022. The paper used panel analysis and generalized method of moments Arellano-Bond approaches. The findings show that under the growth model, renewable energy (RE) has a strong and favorable link with fixed broadband and mobile subscribers. However, FB and MD have a strong but negative association with the uptake of renewable energy (RE) in the average and simple model. This paper provides valuable insights for policymakers, investors of the digital economy.

Keywords: digital finance, renewable energy, economic development, mobile subscription, fixed broadband

Procedia PDF Downloads 31

Authors: Shazia Bano

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Nanoconjugates that integrate photo-based therapeutics and diagnostics within a single platform promise great advances in revolutionizing cancer treatments. However, to achieve high therapeutic efficacy, designing functionally efficacious nanocarriers to tightly retain the drug, promoting selective drug localization and release, and the validation of the efficacy of these nanoconjugates is a great challenge. Here we have designed smart multiagent, liposome based targeted photoactivatable multiagent nanoconjugates, doped with a photoactivatable chromophore benzoporphyrin derivative (BPD) labelled with an active targeting ligand cetuximab to target the EGFR receptor (over expressed in various cancer cells) to deliver a combination of therapeutic agents. This study establishes a tunable nanoplatform for the delivery of the photoactivatable multiagent nanoconjugates for tumor-specific accumulation and targeted destruction of cancer cells in complex cancer model to enhance the therapeutic index of the administrated drugs.

Keywords: targeting, photodynamic therapy, photoactivatable, nanoconjugates

Procedia PDF Downloads 135

Authors: Emanuela Paranhos Lima, Vitaly Félix Rodríguez Esquerre

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In this work, efficient directional coupler composed of dielectric waveguides and metallic film has been analyzed in details by simulations using finite element method (FEM). The structure consists of a step-index fiber with dielectric core, silica cladding, and a metal nanowire parallel to the core. The results show that an efficient conversion of optical dielectric modes to long range plasmonic is possible. Low insertion losses in conjunction with short coupling length and a broadband operation can be achieved under certain conditions. This kind of couplers has potential applications for the design of photonic integrated circuits for signal routing between dielectric/plasmonic waveguides, sensing, lithography, and optical storage systems. A high efficient focusing of light in a very small region can be obtained.

Keywords: directional coupler, finite element method, metallic nanowire, plasmonic, surface plasmon polariton, superfocusing

Procedia PDF Downloads 268

Authors: Shatha A. Yousif, Qasim M. Zamil, Hasan Y. Al Muhi, Jamal A. Al Shammari

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Potato (Solanum tuberosum L.) is one of the major vegetable crops that are grown world wide because of its economic importance. This experiment investigated the effect of local sands (River Base, Al-Ekader and Karbala) on number and total weight of mini tubers. Statistical analysis revealed that there were no significant differences among sand cultures in number of stem/plant, chlorophyll index and tubers dry weight. River Base sand had the highest plant height (74.9 cm), leaf number/plant number (39.3), leaf area (84.4 dcm2⁄plant), dry weight/plant (26.31), tubers number/plant (8.5), tubers weight/plant (635.53 gm) and potato tuber yields/trove (28.60 kg), whereas the Karbala sand had lower performance. All the characters had positive and significant correlation with yields except the traits number of stem and tuber dry weight.

Keywords: correlation, potato, sand culture, yield

Procedia PDF Downloads 472

Authors: Kaoutar Abbahaddou, Mohammed Salah Chiadmi

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The need to find a relevant way to predict the next-day price of a stock index is a real concern for many financial stakeholders and researchers. We have known across years the proliferation of several methods. Nevertheless, among all these methods, the most controversial one is a machine learning algorithm that claims to be reliable, namely neural networks. Thus, the purpose of this article is to study the prediction power of neural networks in the particular case of Islamic finance as it is an under-looked area. In this article, we will first briefly present a review of the literature regarding neural networks and Islamic finance. Next, we present the architecture and principles of artificial neural networks most commonly used in finance. Then, we will show its empirical application on two Islamic stock indexes. The accuracy rate would be used to measure the performance of the algorithm in predicting the right price the next day. As a result, we can conclude that artificial neural networks are a reliable method to predict the next-day price for Islamic indices as it is claimed for conventional ones.

Keywords: Islamic finance, stock price prediction, artificial neural networks, machine learning

Procedia PDF Downloads 227

Authors: Musefiu Aderinola, F. A. Amuda

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Outages of GSM signals may be experienced at some indoor locations even when there are strong outdoor receptions. This is often traced to the building penetration loss, which account for increased attenuation of received GSM signals level when a mobile signal device is moved indoor from outdoor. In this work, measurement of two existing GSM operators signal level were made outside and inside two selected buildings- mud and block which represent the prevalent building types in Kazaure, Jigawa State, Nigeria. A gionee P2 mobile phone with RF signal tracker software installed in it was used and the result shows that an average loss of 10.62dBm and 4.25dBm for mud and block buildings respectively.

Keywords: penetration loss, outdoor reception, Gionee P2, RF signal tracker, mud and block building

Procedia PDF Downloads 300

Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

Procedia PDF Downloads 166

Authors: Nuwan Kuruwitaarachchi, M. K. M. Peiris, C. N. Madawala, K. M. A. R. Perera, V. U. N Perera

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Dealing with businesses with the foreign market always took a special place in a country’s economy. Political and social factors came into play making currency rate changes fluctuate rapidly. Currency rate prediction has become an important factor for larger international businesses since large amounts of money exchanged between countries. This research focuses on comparing the accuracy of mainly three models; Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Networks(ANN) and Support Vector Machines(SVM). series of data import, export, USD currency exchange rate respect to LKR has been selected for training using above mentioned algorithms. After training the data set and comparing each algorithm, it was able to see that prediction in SVM performed better than other models. It was improved more by combining SVM and SVR models together.

Keywords: ARIMA, ANN, FFNN, RMSE, SVM, SVR

Procedia PDF Downloads 200