Search results for: reliable estimation

Authors: Roman Khanferyan

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Endurance exercises and strenuous muscle activity are accompanied by multiple immune dysfunctions due to the activation of cytokines and chemokines synthesis. This study assesses changes in the synthesis of immune regulatory mediators in elite athletes during endurance sports activity. The concentrations of cytokines/chemokines (IL-2, IL-6, IL-8, IL-10, IL-18, MIP-1 beta, GRO-alpha, RANTES, SDF-1a, VEGF) in sera of hockey athletes (n=33) and in supernatants of 24-h cultivated peripheral blood mononuclear cells (PBMC) of boxers (n=6) assayed by ELISA and Luminex xMAP multiplex assays. Estimation of body composition studied by using bioimpedance technology. The dietary energy consumption per person has been estimated using an album of different sizes of portions of the most frequently consumed foods. It has been demonstrated that endurance sports activity enhances the secretions of most pro- and anti-inflammatory cytokines and chemokines in more than 2-6 fold. The study demonstrated that the high increase of more than 3-4 times in the concentration of IL-18 in sera of athletes (327.86 + 45.67 pg/ml) didn’t correlate with BMI (p=0.040) but demonstrated a low correlation with MMI (p=0.234) and BMR (p=0,231). The opposite impact on the concentration of IL-10 has been demonstrated in athletes. It has been shown a negative correlation between its concentration and BMI (p= - 0.251), MMI (p= - 0.327), and BMR (p= - 0.301). In vitro studies in boxers showed greater amounts of chemokines in the PBMC supernatants, including MIP-1β, GRO-α, RANTES, SDF-1α, and IL-8 (P<0.05). At the same time, healthy controls had greater supernatant levels of MCP-1, Eotaxin, and MIP-1α. The study demonstrated a high correlation between physical activity, usual athletes' diet, and consumption of specialized sports nutrition products.

Keywords: sport nutrition, cytokines, chemokines, endurace exercises

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Authors: Yanto Santosa, Catharina Yudea

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The rapid growth of oil palm industry in Indonesia raised many negative accusations from various parties, who said that oil palm plantation is damaging the environment and biodiversity, including birds. Since research on oil palm plantation impacts on bird diversity is still limited, this study needs to be developed in order to gain further learning and understanding. Data on bird diversity were collected in March 2018 in KJNP Estate, Riau Province using strip transect method on five different land cover types (young, intermediate, and old growth of oil palm plantation, high conservation value area, and crops field or the baseline). The observations were conducted simultaneously, with three repetitions. The result shows that the baseline has 19 species of birds and land cover after the oil palm plantation has 39 species. HCV (high conservation value) area has the highest increase in diversity value. Oil palm plantation has changed the composition of bird species. The highest similarity index is shown by young growth oil palm land cover with total score 0.65, meanwhile the lowest similarity index with total score 0.43 is shown by HCV area. Overall, the existence of oil palm plantation made a positive impact by increasing bird species diversity, with total 23 species gained and 3 species lost.

Keywords: bird diversity, crops field, impact of oil palm plantation, KJNP estate

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Authors: Md. Qamruzzaman, Wei Jianguo

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Over the decade, it is observed that financial development, through financial innovation, not only accelerated development of efficient and effective financial system but also act as a catalyst in the economic development process. In this study, we try to explore insight about how financial innovation causes economic growth in Bangladesh by using Vector Error Correction Model (VECM) for the period of 1990-2014. Test of Cointegration confirms the existence of a long-run association between financial innovation and economic growth. For investigating directional causality, we apply Granger causality test and estimation explore that long-run growth will be affected by capital flow from non-bank financial institutions and inflation in the economy but changes of growth rate do not have any impact on Capital flow in the economy and level of inflation in long-run. Whereas, growth and Market capitalization, as well as market capitalization and capital flow, confirm feedback hypothesis. Variance decomposition suggests that any innovation in the financial sector can cause GDP variation fluctuation in both long run and short run. Financial innovation promotes efficiency and cost in financial transactions in the financial system, can boost economic development process. The study proposed two policy recommendations for further development. First, innovation friendly financial policy should formulate to encourage adaption and diffusion of financial innovation in the financial system. Second, operation of financial market and capital market should be regulated with implementation of rules and regulation to create conducive environment.

Keywords: financial innovation, economic growth, GDP, financial institution, VECM

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Authors: Tan Swee Liang

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This paper studies the two-way relationship between fintech credit and banking efficiency using the Generalized panel Method of Moment (GMM) estimation in structural equation modeling (SEM). Banking system efficiency, defined as its ability to produce the existing level of outputs with minimal inputs, is measured using input-oriented data envelopment analysis (DEA), where the whole banking system of an economy is treated as a single DMU. Banks are considered an intermediary between depositors and borrowers, utilizing inputs (deposits and overhead costs) to provide outputs (increase credits to the private sector and its earnings). Analysis of the interrelationship between fintech credit and bank efficiency is conducted to determine the impact in different country groupings (ASEAN, Asia and OECD), in particular the banking system response to fintech credit platforms. Our preliminary results show that banks do respond to the greater pressure caused by fintech platforms to enhance their efficiency, but differently across the different groups. The author’s earlier research on ASEAN-5 high bank overhead costs (as a share of total assets) as the determinant of economic growth suggests that expenses may not have been channeled efficiently to income-generating activities. One practical implication of the findings is that policymakers should enable alternative financing, such as fintech credit, as a warning or encouragement for banks to improve their efficiency.

Keywords: fintech lending, banking efficiency, data envelopment analysis, structural equation modeling

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Authors: Recep Keşli, Onur Türkyılmaz, Hayriye Tokay, Kasım Demir

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Objective: Coeliac disease (CD) is a primary small intestine disorder caused by high sensitivity to gluten which is present in the crops, characterized by inflammation in the small intestine mucosa. The goal of this study was to determine and to compare the sensitivity and specificity values of anti-endomysial IgA (EMA IgA) (IFA) and anti-tissue transglutaminase IgA (anti-tTG IgA) (ELISA) antibodies in the diagnosis of patients suspected with the CD. Methods: One thousand two hundred seventy three patients, who have applied to gastroenterology and pediatric disease polyclinics of Afyon Kocatepe University ANS Research and Practice Hospital were included into the study between 23.09.2010 and 30.05.2016. Sera samples were investigated by immunofluorescence method for EMA positiveness (Euroimmun, Luebeck, Germany). In order to determine quantitative value of Anti-tTG IgA (EIA) (Orgentec Mainz, Germany) fully automated ELISA device (Alisei, Seac, Firenze, Italy) were used. Results: Out of 1273 patients, 160 were diagnosed with coeliac disease according to ESPGHAN 2012 diagnosis criteria. Out of 160 CD patients, 120 were female, 40 were male. The EMA specificity and sensitivity were calculated as 98% and 80% respectively. Specificity and sensitivity of Anti-tTG IgA were determined as 99% and 96% respectively. Conclusion: The specificity of EMA for CD was excellent because all EMA-positive patients (n = 144) were diagnosed with CD. The presence of human anti-tTG IgA was found as a reliable marker for diagnosis and follow-up the CD. Diagnosis of CD should be established on both the clinical and serologic profiles together.

Keywords: anti-endomysial antibody, anti-tTG IgA, coeliac disease, immunofluorescence assay (IFA)

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Authors: Kang Huang, Wanting Zhou, Shiwei Yuan, Lei Li

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Since information technology develops rapidly, the security issue has become an increasingly critical for computer system. In particular, as cloud computing and the Internet of Things (IoT) continue to gain widespread adoption, computer systems need to new security threats and attacks. The Root of Trust (RoT) is the foundation for providing basic trusted computing, which is used to verify the security and trustworthiness of other components. Design a reliable Root of Trust and guarantee its own security are essential for improving the overall security and credibility of computer systems. In this paper, we discuss the implementation of self-security technology based on the RISC-V Root of Trust at the hardware level. To effectively safeguard the security of the Root of Trust, researches on security safeguard technology on the Root of Trust have been studied. At first, a lightweight and secure boot framework is proposed as a secure mechanism. Secondly, two kinds of memory protection mechanism are built to against memory attacks. Moreover, hardware implementation of proposed method has been also investigated. A series of experiments and tests have been carried on to verify to effectiveness of the proposed method. The experimental results demonstrated that the proposed approach is effective in verifying the integrity of the Root of Trust’s own boot rom, user instructions, and data, ensuring authenticity and enabling the secure boot of the Root of Trust’s own system. Additionally, our approach provides memory protection against certain types of memory attacks, such as cache leaks and tampering, and ensures the security of root-of-trust sensitive information, including keys.

Keywords: root of trust, secure boot, memory protection, hardware security

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Authors: Ali Jahanfar, Brajesh Dubey, Bahram Gharabaghi, Saber Bayat Movahed

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Ever increasing population growth of major urban centers and environmental challenges in siting new landfills have resulted in a growing trend in design of mega-landfills some with extraordinary heights and dangerously steep slopes. Landfill failure mobility risk analysis is one of the most uncertain types of dynamic rheology models due to very large inherent variabilities in the heterogeneous solid waste material shear strength properties. The waste flow of three historic dumpsite and two landfill failures were back-analyzed using run-out modeling with DAN-W model. The travel distances of the waste flow during landfill failures were calculated approach by taking into account variability in material shear strength properties. The probability distribution function for shear strength properties of the waste material were grouped into four major classed based on waste material compaction (landfills versus dumpsites) and composition (high versus low quantity) of high shear strength waste materials such as wood, metal, plastic, paper and cardboard in the waste. This paper presents a probabilistic method for estimation of the spatial extent of waste avalanches, after a potential landfill failure, to create maps of vulnerability scores to inform property owners and residents of the level of the risk.

Keywords: landfill failure, waste flow, Voellmy rheology, friction coefficient, waste compaction and type

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Authors: Panagiotis Karadimos, Leonidas Anthopoulos

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Predicting the actual cost and duration in construction projects concern a continuous and existing problem for the construction sector. This paper addresses this problem with modern methods and data available from past public construction projects. 39 bridge projects, constructed in Greece, with a similar type of available data were examined. Considering each project’s attributes with the actual cost and the actual duration, correlation analysis is performed and the most appropriate predictive project variables are defined. Additionally, the most efficient subgroup of variables is selected with the use of the WEKA application, through its attribute selection function. The selected variables are used as input neurons for neural network models through correlation analysis. For constructing neural network models, the application FANN Tool is used. The optimum neural network model, for predicting the actual cost, produced a mean squared error with a value of 3.84886e-05 and it was based on the budgeted cost and the quantity of deck concrete. The optimum neural network model, for predicting the actual duration, produced a mean squared error with a value of 5.89463e-05 and it also was based on the budgeted cost and the amount of deck concrete.

Keywords: actual cost and duration, attribute selection, bridge construction, neural networks, predicting models, FANN TOOL, WEKA

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Authors: Esther Chiramal, Kelvin Soh Boon Kai

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Explainable AI is a strong strategy implemented to understand complex black-box model predictions in a human-interpretable language. It provides the evidence required to execute the use of trustworthy and reliable AI systems. On the other hand, however, it also opens the door to locating possible vulnerabilities in an AI model. Traditional adversarial text attack uses word substitution, data augmentation techniques, and gradient-based attacks on powerful pre-trained Bidirectional Encoder Representations from Transformers (BERT) variants to generate adversarial sentences. These attacks are generally white-box in nature and not practical as they can be easily detected by humans e.g., Changing the word from “Poor” to “Rich”. We proposed a simple yet effective Grey-box cum Black-box approach that does not require the knowledge of the model while using a set of surrogate Transformer/BERT models to perform the attack using Explainable AI techniques. As Transformers are the current state-of-the-art models for almost all Natural Language Processing (NLP) tasks, an attack generated from BERT1 is transferable to BERT2. This transferability is made possible due to the attention mechanism in the transformer that allows the model to capture long-range dependencies in a sequence. Using the power of BERT generalisation via attention, we attempt to exploit how transformers learn by attacking a few surrogate transformer variants which are all based on a different architecture. We demonstrate that this approach is highly effective to generate semantically good sentences by changing as little as one word that is not detectable by humans while still fooling other BERT models.

Keywords: BERT, explainable AI, Grey-box text attack, transformer

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Authors: Vinod K. Singh, S. G. Chung

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The degree of structuration of Busan clays at the mouth of Nakdong River mouth was highly influenced by the depositional environment, i.e., flow of the river stream, marine regression, and transgression during the sedimentation process. As a result, the geotechnical properties also varies along the depth with change in degree of structuration. Thus, the in-situ tests such as cone penetration test (CPT) could not be used to predict various geotechnical properties properly by using the conventional empirical methods. In this paper, the shear wave velocity (Vs) was measured from the field using the seismic dilatometer. The Vs was also measured in the laboratory from high quality undisturbed and remolded samples using bender element method to evaluate the degree of structuration. The degree of structuration was quantitatively defined by the modulus ratio of undisturbed to remolded soil samples which is found well correlated with the normalized void ratio (e0/eL) where eL is the void ratio at the liquid limit. It is revealed that the empirical method based on laboratory results incorporating e0/eL can predict Vs from the field more accurately. Thereafter, the CPT based empirical method was developed to estimate the shear wave velocity taking the effect of structuration in the consideration. The developed method was found to predict shear wave velocity reasonably for Busan clays.

Keywords: level of structuration, normalized modulus, normalized void ratio, shear wave velocity, site characterization

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Authors: Apostolos Lagarias, Anastasia Stratigea

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Coastal urbanization is heavily affecting the Mediterranean, taking the form of linear urban sprawl along the coastal zone. This process is posing extreme pressure on ecosystems, leading to an unsustainable model of growth. The aim of this research is to analyze coastal urbanization patterns in the Mediterranean using High-resolution multi-temporal data provided by the Global Human Settlement Layer (GHSL) database. Methodology involves the estimation of a set of spatial metrics characterizing the density, aggregation/clustering and dispersion of built-up areas. As case study areas, the Spanish Coast and the Adriatic Italian Coast are examined. Coastalization profiles are examined and selected sub-areas massively affected by tourism development and suburbanization trends (Costa Blanca/Murcia, Costa del Sol, Puglia, Emilia-Romagna Coast) are analyzed and compared. Results show that there are considerable differences between the Spanish and the Italian typologies of spatial development, related to the land use structure and planning policies applied in each case. Monitoring and analyzing spatial patterns could inform integrated Mediterranean strategies for coastal areas and redirect spatial/environmental policies towards a more sustainable model of growth

Keywords: coastalization, Mediterranean, multi-temporal, urban sprawl, spatial metrics

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Authors: Mohammad Sharifi Bohlouli, Elnaz Sharifi Bohlouli

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Turkish language with many dialects is native or official language of great number of people all around the world. The Qashqaie dialect of Turkish language is spoken by the Qashqaie tribe mostly scattered in the southern part of Iran. This paper aims at analyzing the tense system of this dialect to detect the type and number of tense and aspects available to its speakers. To collect a reliable data, a group of 50 old native speakers were randomly chosen as the informants and different techniques such as; Shuy et al interviews, selective listening ,and eavesdropping were used. The results of data analysis showed that the tense system in the Qashqaie dialect of Turkish language includes 3 absolute tenses, 6 aspectual, and 2 subjunctive ones. The interesting part of the study is that Qashqaie dialect enables its speakers to make a kind of aspectual opposition through verb structure which seems to be almost impossible through verb forms in any other nonturkish languages. For example in the following examples sentences 1&2 and 3&4 have the same translation In English although they are different in both meaning and structure. 1. Ali ensha yazirdi. 2. Ali ensha yazirmush. (Ali was writing a composition.) 3. Ali yadmishdi. 4. Ali yadmishimish. (Ali had slept.). The changes in the verb structure in Qashqaie dialect enables its speakers to say that whether the doer of the action remembers the process of doing the action or not. So, it presents a new aspectual opposition as Observed /nonobserved. The research findings reveal many other regularities and linguistic features that can be useful for linguists interested in Turkish in general and for those interested in tense and aspect and also they can be helpful for different pedagogical purposes including teaching and translating.

Keywords: qashqaie dialect, tense, aspect, linguistics, Turkish language

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Authors: Somayeh Akrami, Habib Onsori, Elham Tahmassebian

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Species of Anemone narcissiflora is belonged to Anemone genus of Ranunculaceae family. This species has two subspecies named narcissiflora and willdenowii which the latest is recorded in Iran in 2010. Some samples of A. narcissiflora is gathered from kuhkamar-zonouz region of East -Azerbaijan province, Iran to study the genetic diversity of the species by using RAPD molecular markers, and estimation of genetic diversity were evaluated with the using 10mer RAPD primers by PCR-RAPD method. 39 polymorphic bands were produced from the six primers used in this technique that the maximum band is related to the RP1 primer, the lowest band is related to the RP7 and the average band for all primers were 6.5 polymorphic bands. Cluster analysis of samples in done by UPGMA method in NTSYSpc 2.02 software. Dendrogram resulting from migrating bands showed that the studied samples can be divided into two groups. The first group includes samples with 1-2 flowers and the second group consists of two sub-groups which the first subgroup consists of samples with 3-5 flowers, and the second subgroup consists of samples with 6-7 flowers. The results of the comparison and analysis of the data obtained from RAPD technique and similarity matrix represents the genetic variation between collected samples. This study shows that RAPD markers can determine the polymorphisms between different genotypes of A. narcissiflora and their hybrids. So RAPD technique can serve as a suitable molecular method to determine the genetic diversity of samples.

Keywords: Anemone narcissiflora, genetic diversity, RAPD-PCR

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Authors: Ramutė Miseikienė, Saulius Tusas

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Somatic cell count and bacteria count are the main indicators of cow milk quality. The aim of this study was to analyze and compare parameters of milk quality in different-sized cows herds. Milk quality of ten dairy cows farms during one year period was analyzed. Dairy farms were divided into five groups according to number of cows in the farm (under 50 cows, 51–100 cows, 101–200 cows, 201–400 cows and more than 400 cows). The averages of somatic cells bacteria count in milk and milk freezing temperature were analyzed. Also, these parameters of milk quality were compared during outdoor (from May to September) and indoor (from October to April) periods. The largest number of SCC was established in the smallest farms, i.e., in farms under 50 cows and 51-100 cows (respectively 264±9,19 and 300±10,24 thousand/ml). Reliable link between the smallest and largest dairy farms and farms with 101-200 and 201-400 cows and count of somatic cells in milk has not been established (P > 0.05). Bacteria count had a low tendency to decrease when the number of cows in farms increased. The highest bacteria number was determined in the farms with 51-100 cows and the the lowest bacteria count was in milk when 201-400 and more than 401 cows were kept. With increasing the number of cows milk maximal freezing temperature decreases (significant negative trend), i. e, indicator is improving. It should be noted that in all farms milk freezing point never exceeded requirements (-0.515 °C). The highest difference between SCC in milk during the indoor and outdoor periods was established in farms with 201-400 cows (respectively 218.49 thousand/ml and 268.84 thousand/ml). However, the count of SC was significantly higher (P < 0.05) during outdoor period in large farms (201-400 and more cows). There was no significant difference between bacteria count in milk during both – outdoor and indoor – periods (P > 0.05).

Keywords: bacteria, cow, farm size, somatic cell count

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Authors: Jin Fan, M. Ala Saadeghvaziri

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Unmanned aerial vehicles (UAVs), also referred to as drones, equipped with various kinds of advanced detecting or surveying systems, are effective and low-cost in data acquisition, data delivery and sharing, which can benefit the building of infrastructures. This paper will give an overview of applications of drones in planning, designing, construction and maintenance of infrastructures. The drone platform, detecting and surveying systems, and post-data processing systems will be introduced, followed by cases with details of the applications. Challenges from different aspects will be addressed. Opportunities of drones in infrastructure include but not limited to the following. Firstly, UAVs equipped with high definition cameras or other detecting equipment are capable of inspecting the hard to reach infrastructure assets. Secondly, UAVs can be used as effective tools to survey and map the landscape to collect necessary information before infrastructure construction. Furthermore, an UAV or multi-UVAs are useful in construction management. UVAs can also be used in collecting roads and building information by taking high-resolution photos for future infrastructure planning. UAVs can be used to provide reliable and dynamic traffic information, which is potentially helpful in building smart cities. The main challenges are: limited flight time, the robustness of signal, post data analyze, multi-drone collaboration, weather condition, distractions to the traffic caused by drones. This paper aims to help owners, designers, engineers and architects to improve the building process of infrastructures for higher efficiency and better performance.

Keywords: bridge, construction, drones, infrastructure, information

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Authors: Omid Ataei Nia, Karim Salahshoor

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In this paper, a new precise and reliable sensor network methodology is introduced for unit processes and operations using the Constriction Coefficient Particle Swarm Optimization (CPSO) method. CPSO is introduced as a new search engine for optimal sensor network design purposes. Furthermore, a Square Root Unscented Kalman Filter (SRUKF) algorithm is employed as a new data reconciliation technique to enhance the stability and accuracy of the filter. The proposed design procedure incorporates precision, cost, observability, reliability together with importance-of-variables (IVs) as a novel measure in Instrumentation Criteria (IC). To the best of our knowledge, no comprehensive approach has yet been proposed in the literature to take into account the importance of variables in the sensor network design procedure. In this paper, specific weight is assigned to each sensor, measuring a process variable in the sensor network to indicate the importance of that variable over the others to cater to the ultimate sensor network application requirements. A set of distinct scenarios has been conducted to evaluate the performance of the proposed methodology in a simulated Continuous Stirred Tank Reactor (CSTR) as a highly nonlinear process plant benchmark. The obtained results reveal the efficacy of the proposed method, leading to significant improvement in accuracy with respect to other alternative sensor network design approaches and securing the definite allocation of sensors to the most important process variables in sensor network design as a novel achievement.

Keywords: constriction coefficient PSO, importance of variable, MRMSE, reliability, sensor network design, square root unscented Kalman filter

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Authors: Deokho Kim, Wonwoo Lee, Jaewoong Lee, Teresa Ng, Gun-Ill Lee, Jiwon Jeong

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This paper presents a method for improving object search accuracy using a deep learning model. A major limitation to provide accurate similarity with deep learning is the requirement of huge amount of data for training pairwise similarity scores (metrics), which is impractical to collect. Thus, similarity scores are usually trained with a relatively small dataset, which comes from a different domain, causing limited accuracy on measuring similarity. For this reason, this paper proposes a deep learning model that can be trained with a significantly small amount of data, a clustered data which of each cluster contains a set of visually similar images. In order to measure similarity distance with the proposed method, visual features of two images are extracted from intermediate layers of a convolutional neural network with various pooling methods, and the network is trained with pairwise similarity scores which is defined zero for images in identical cluster. The proposed method outperforms the state-of-the-art object similarity scoring techniques on evaluation for finding exact items. The proposed method achieves 86.5% of accuracy compared to the accuracy of the state-of-the-art technique, which is 59.9%. That is, an exact item can be found among four retrieved images with an accuracy of 86.5%, and the rest can possibly be similar products more than the accuracy. Therefore, the proposed method can greatly reduce the amount of training data with an order of magnitude as well as providing a reliable similarity metric.

Keywords: visual search, deep learning, convolutional neural network, machine learning

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Authors: Swati Srivastava, Ashish Kumar Upadhyay

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Haemophilus influenzae Type B (Hib) cause infections of pneumonia, meningitis, epiglottises and other invasive disease exclusively among children under age five. Occurrence of these infections may impair child growth by causing micronutrient deficiency. Using longitudinal data from first and second waves of Young Lives Study conducted in India during 2002 and 2006-07 respectively and multivariable logistic regression models (using generalised estimation equation to take into account the cluster nature of sample), this study aims to examine the impact of Hib vaccination on child anthropometric outcomes (stunting, underweight and wasting) in India. Bivariate result shows that, a higher percent of children were stunted and underweight among those who were not vaccinated against Hib (39% & 48% respectively) as compare to those who were vaccinated (31% and 39% respectively).The risk of childhood stunting and underweight was significantly lower among children who were vaccinated against Hib (odds ratio: 0.77, 95% CI: 0.62-0.96 and odds ratio: 0.79, 95% C.I: 0.64-0.98 respectively) as compare to the unvaccinated children. No significant association was found between vaccination status against Hib and childhood wasting. Moreover, in the statistical models, about 13% of stunting and 12% of underweight could be attributable to lack of vaccination against Hib in India. Study concludes that vaccination against Hib- in addition to being a major intervention for reducing childhood infectious disease and mortality- can be consider as a potential tool for reducing the burden of undernutrition in India. Therefore, the Government of India must include the vaccine against Hib into the Universal Immunization Programme in India.

Keywords: Haemophilus influenzae Type-B, Stunting, Underweight, Wasting, Young Lives Study (YLS), India

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Authors: Halefom Kidane

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This study aims to assess the wind resource potential and characterize the urban area wind patterns in Hawassa City, Ethiopia. The estimation and characterization of wind resources are crucial for sustainable urban planning, renewable energy development, and climate change mitigation strategies. A secondary data collection method was used to carry out the study. The collected data at 2 meters was analyzed statistically and extrapolated to the standard heights of 10-meter and 30-meter heights using the power law equation. The standard deviation method was used to calculate the value of scale and shape factors. From the analysis presented, the maximum and minimum mean daily wind speed at 2 meters in 2016 was 1.33 m/s and 0.05 m/s in 2017, 1.67 m/s and 0.14 m/s in 2018, 1.61m and 0.07 m/s, respectively. The maximum monthly average wind speed of Hawassa City in 2016 at 2 meters was noticed in the month of December, which is around 0.78 m/s, while in 2017, the maximum wind speed was recorded in the month of January with a wind speed magnitude of 0.80 m/s and in 2018 June was maximum speed which is 0.76 m/s. On the other hand, October was the month with the minimum mean wind speed in all years, with a value of 0.47 m/s in 2016,0.47 in 2017 and 0.34 in 2018. The annual mean wind speed was 0.61 m/s in 2016,0.64, m/s in 2017 and 0.57 m/s in 2018 at a height of 2 meters. From extrapolation, the annual mean wind speeds for the years 2016,2017 and 2018 at 10 heights were 1.17 m/s,1.22 m/s, and 1.11 m/s, and at the height of 30 meters, were 3.34m/s,3.78 m/s, and 3.01 m/s respectively/Thus, the site consists mainly primarily classes-I of wind speed even at the extrapolated heights.

Keywords: artificial neural networks, forecasting, min-max normalization, wind speed

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Authors: Mershack O. Tetteh, Albert P. C. Chan, Amos Darko, Gabriel Nani

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International construction joint ventures (ICJVs) have evolved as an effective approach to sustainable development, given their myriad socio-economic and environmental benefits. Yet, they are not free of barriers and risks. In many studies, it is termed as risks for convenience’s sake. While the barriers and risks continue to affect the success of ICJVs, a systematic and reliable approach for managing them has yet to be developed. This study aims to identify and classify the barriers and risks factors affecting ICJVs through a systematic literature review. Based on a critical review of 54 papers published in peer-reviewed journals from 1990 to 2019, a conceptual framework was proposed for managing the barriers and risks in ICJV operations. The review showed that the barriers can be grouped into six including inter-organizational differences, lack of expertise and confidence, lack of effective planning and strategies, lack of knowledge of ICJV’s fundamentals, conflicts among ICJV entities, and management difficulties. The risks were also categorized into six: policy and political risks, legal risks, financial risks, management risks, project and technical risks, and market risks. The developed model would help practitioners achieve more efficient resource allocation and bring new perspectives for managerial practices in ICJVs. Moreover, it is positioned to alleviate the negligence of previous studies that combined the barriers and risks factors as one checklist.

Keywords: barriers, construction, international construction joint venture, risks, sustainable development

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Authors: Omotayo Abidemi Funmilayo

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Skill acquisition in professional fields has been prioritized and considered important to demonstrate the mastery of subject matter and present oneself as an expert in such profession. The ability to acquire skills in different fields, however calls for different method from the instructor or teacher during training. Music is not an exception of such profession, where there exist different area of skills acquisition require practical performance. This paper, however, focused on the impact and effects of different methods on acquisition of practical knowledge in the handling of some musical instruments among the students of Emmanuel Alayande College of Education, Oyo. In this study, 30 students were selected and divided into two groups based on the selected area of learning, further division were made on each of the two major groups to consist of five students each, to be trained using different methodology for two months and three hours per week. Comparison of skill acquired were made using standard research instrument at reliable level of significance, test were carried out on the thirty students considered for the study based on area of skill acquisition. The students that were trained on the keyboard and saxophone using play way method, followed by the students that were trained using demonstration method while the set of students that received teaching instruction through lecture method performed below average. In conclusion, the study reveals that ability to acquire professional skill on handling musical instruments are better enhanced using play way method.

Keywords: music education, skill acquisition, keyboard, saxophone

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Authors: S. J. M. Mohd Saleh, S. Guo

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Composite materials have become an important option for the primary structure of aircraft due to their design flexibility and ability to improve the overall performance. At present, the option for composite usage in aircraft component is largely based on experience, knowledge, benchmarking and partly market driven. An inevitable iterative design during the design stage and validation process will increase the development time and cost. This paper aims at presenting the correlation between laminate and composite thin-wall beam structure, which contains the theoretical and numerical investigations on stiffness estimation of composite aerostructures with applications to aircraft wings. Classical laminate theory and thin-walled beam theory were applied to define the correlation between 1-dimensional composite laminate and 2-dimensional composite beam structure, respectively. Then FE model was created to represent the 3-dimensional structure. A detailed study on stiffness matrix of composite laminates has been carried out to understand the effects of stacking sequence on the coupling between extension, shear, bending and torsional deformation of wing box structures for 1-dimensional, 2-dimensional and 3-dimensional structures. Relationships amongst composite laminates and composite wing box structures of the same material have been developed in this study. These correlations will be guidelines for the design engineers to predict the stiffness of the wing box structure during the material selection process and laminate design stage.

Keywords: aircraft design, aircraft structures, classical lamination theory, composite structures, laminate theory, structural design, thin-walled beam theory, wing box design

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Authors: Donglian Sun, Yu Li, Paul Houser, Xiwu Zhan

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California experienced severe drought conditions in the past years. In this study, the drought conditions in California are analyzed using soil moisture anomalies derived from integrated optical and microwave satellite observations along with auxiliary land surface data. Based on the U.S. Drought Monitor (USDM) classifications, three typical drought conditions were selected for the analysis: extreme drought conditions in 2007 and 2013, severe drought conditions in 2004 and 2009, and normal conditions in 2005 and 2006. Drought is defined as negative soil moisture anomaly. To estimate soil moisture at high spatial resolutions, three approaches are explored in this study: the universal triangle model that estimates soil moisture from Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST); the basic model that estimates soil moisture under different conditions with auxiliary data like precipitation, soil texture, topography, and surface types; and the refined model that uses accumulated precipitation and its lagging effects. It is found that the basic model shows better agreements with the USDM classifications than the universal triangle model, while the refined model using precipitation accumulated from the previous summer to current time demonstrated the closest agreements with the USDM patterns.

Keywords: soil moisture, high resolution, regional drought, analysis and monitoring

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Authors: Chih-Chieh Yang, Chung-Neng Huang

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In power system, how to improve the fault diagnosis technology of transmission line has always been the primary goal of power grid operators. In recent years, due to the rise of green energy, the addition of all kinds of distributed power also has an impact on the stability of the power system. Because the smart meters are with the function of data recording and bidirectional transmission, the adaptive Fuzzy Neural inference system, ANFIS, as well as the artificial intelligence that has the characteristics of learning and estimation in artificial intelligence. For transmission network, in order to avoid misjudgment of the fault type and location due to the input of these unstable power sources, combined with the above advantages of smart meter and ANFIS, a method for identifying fault types and location of faults is proposed in this study. In ANFIS training, the bus voltage and current information collected by smart meters can be trained through the ANFIS tool in MATLAB to generate fault codes to identify different types of faults and the location of faults. In addition, due to the uncertainty of distributed generation, a wind power system is added to the transmission network to verify the diagnosis correctness of the study. Simulation results show that the method proposed in this study can correctly identify the fault type and location of fault with more efficiency, and can deal with the interference caused by the addition of unstable power sources.

Keywords: ANFIS, fault diagnosis, power system, smart meter

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Authors: Ismail Cengiz, Faruk Elaldi

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Within the scope of the study presented in this paper, load carrying capacity and buckling behavior of a stiffened aluminum panel designed by adopting current ‘buckle-resistant’ design application and ‘Post –Buckling’ design approach were investigated experimentally and numerically. The test specimen that is stabilized by Z-type stiffeners and manufactured from aluminum 2024 T3 Clad material was test under compression load. Buckling behavior was observed by means of 3 – dimensional digital image correlation (DIC) and strain gauge pairs. The experimental study was followed by developing an efficient and reliable finite element model whose ability to predict behavior of the stiffened panel used for compression test is verified by compering experimental and numerical results in terms of load – shortening curve, strain-load curves and buckling mode shapes. While finite element model was being constructed, non-linear behaviors associated with material and geometry was considered. Finally, applicability of aluminum stiffened panel in airframe design against to composite structures was evaluated thorough the concept of ‘Structural Efficiency’. This study reveals that considerable amount of weight saving could be gained if the concept of ‘post-buckling design’ is preferred to the already conventionally used ‘buckle resistant design’ concept in aircraft industry without scarifying any of structural integrity under load spectrum.

Keywords: post-buckling, stiffened panel, non-linear finite element method, aluminum, structural efficiency

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Authors: Noor Rizkiyah, Djoko Koestiono, Budi Setiawan, Nuhfil Hanani

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This research aims to identify the factors that affect the production of sugar cane, the level of technical efficiency of farming sugar cane ratooning and factors that affect technical inefficiency. Research carried out in Malang of East Java with sampling in a non random sampling stratified proportioned and obtained 172 household sugar cane farmers who are classified based on the level of ratooning i.e. ratooning I 3-4 times ratoning, ratooning II 5-10 times ratoning as well as ratooning III > 10 times ratoning. The method used is the Stochastic Production Frontier approach MLE (maximum likelihood estimation). From the results obtained by analysis of the factors affecting the production of sugar cane farming land, namely ratooning fertilizer use ZA petroganic, use of fertilizer and seeds of embroidery and labor. While the average level of sugar cane farmers ratooning efficiency of 0.78 and categorized yet efficient technically. For the factors that influence the technical inefficiency i.e. age, number of dependents and the frequency of family ratooning. Though not yet technically efficient but sugar cane farmers cultivate cultivation remains ratooning. But if it is done repeatedly ratooning will result in a decrease in the production of sugar cane. Whereas the results of the analysis of farming level of feasibility or RC ratooning sugar cane ratio of 1.15 so worth trying to accomplish. Thus with increased technology and combining the use of inputs is an attempt to let the technical efficiency can be achieved so that the more worthy to be organised.

Keywords: technical efficiency, production, sugarcane, frontier

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Authors: Sushil Kumar Singh, Vivek Tewarson, Sarvesh Kumar, Shobhit Kumar

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Objective: ‘Beating Heart coronary artery bypass grafting on Intermittent Pump Support’ is a more reliable method of coronary revascularization that takes advantage of off and on-pump CABG while eliminating the disadvantage of both techniques. Methods: From January 2015 to December 2021, a new technique, “Intermittent On pump beating heart CABG” using a suction stabilizer was used by putting aortic and venous cannulas electively in all the patients. Patients were supported by a pump intermittently, as and when required (Group 1, n=254). Retrospective data were collected from our record of the patients who underwent off-pump CABG electively by the same surgeon and team (Group 2, n=254). Results: Significant advantage was noted in Group 1 patients in terms of the number of grafts (3.31 ± 1.16 vs. 2.30 ±0.66), grafting of lateral vessels (316 vs.202), mean operating time (1.37 ± 0.23 hrs vs. 2.22 ± 0.45 hrs) and postoperative blood loss (406.30 ± 257.90 ml vs. 567.41 ± 265.20 ml).CPB support time was less than 15 minutes in the majority of patients (n=179, 70.37 %), with a mean of 16.81 minutes. It was required, particularly during the grafting of lateral vessels. A rise in enzymes level (CRP, CKMB, Trop I, and NTPro BNP) was noted in Group 1 patients. But, these did not affect the postoperative course in patients. There was no mortality in Group 1 patients, while four patients in Group 2 died. Coclusions: Intermittent on-pump CABG technique is a promising method of surgical revascularization for all patients requiring CABG. It has shown its superiority in terms of safety, the number of grafts, operating time, and better perioperative course.

Keywords: cardiopulmonary bypass, CABG, beating heart CABG, on-pump CABG

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Authors: Khushi Kashyap, Pratibha Singh

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In the recent years increasing interest in vegetarian diets has been observed, a major problem in this type of diet is to provide the appropriate amount of protein .Value addition of food is current most talked topic because of increasing nutritional awareness among consumers today. An investigation was conducted to develop protein rich multi-millet hemp seed khakhra. The seeds of cannabis sativa L. have been a significant source of food for thousand of year. In recent years, hemp has not been thoroughly explored for its nutritional potential due to the mistaken belief regarding the cannabis plants. Methodology- two variations was prepared referencing standard recipe. Variation 1 was prepared using 25g ragi, 25g bajra,40g whole wheat flour with 10g hemp seed powder, variation 2(RF-25g,BF25g,WWF-35g,HS-15g). The product was subjected to sensory evolution by semi trained panel members using 9 point hedonic on 50 panelists. Result- result of the sensory evaluation revealed that the product incorporated with 15g of hemp seed were similar to control I texture, taste and overall quality and was more acceptable by the panelist and was selected as final product seed. On estimation of the nutrient content 30g of khakhra provides 107kcal of energy,12g protein,75g carbohydrate, and 9.6g of fats with shelf life of 3 months. Conclusion- khakhras can be eaten as a snack at any time of the day. hemp seed powder incorporated in it enhances its nutritive value and makes it more nutritious. It is suitable for consumption of all the age group.

Keywords: cannabis sativa, hemp, protein, seed

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Authors: M. Devaki, K. B. Jayanthi

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The identification of water bodies from satellite images has recently received a great deal of attention. Different methods have been developed to distinguish water bodies from various satellite images that vary in terms of time and space. Urban water identification issues body manifests in numerous applications with a great deal of certainty. There has been a sharp rise in the usage of satellite images to map natural resources, including urban water bodies and forests, during the past several years. This is because water and forest resources depend on each other so heavily that ongoing monitoring of both is essential to their sustainable management. The relevant elements from satellite pictures have been chosen using a variety of techniques, including machine learning. Then, a convolution neural network (CNN) architecture is created that can identify a superpixel as either one of two classes, one that includes water or doesn't from input data in a complex metropolitan scene. The deep learning technique, CNN, has advanced tremendously in a variety of visual-related tasks. CNN can improve classification performance by reducing the spectral-spatial regularities of the input data and extracting deep features hierarchically from raw pictures. Calculate the water body using the satellite image's resolution. Experimental results demonstrate that the suggested method outperformed conventional approaches in terms of water extraction accuracy from remote-sensing images, with an average overall accuracy of 97%.

Keywords: water body, Deep learning, satellite images, convolution neural network

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Authors: Ofosuhene O. Apenteng, Noor Azina Ismail

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The human immunodeficiency virus (HIV) that causes acquired immune deficiency syndrome (AIDS) remains a global cause of morbidity and mortality. It has caused panic since its emergence. Relationships between migration and HIV/AIDS have become complex. In the absence of prospectively designed studies, dynamic mathematical models that take into account the migration movement which will give very useful information. We have explored the utility of mathematical models in understanding transmission dynamics of HIV and AIDS and in assessing the magnitude of how migration has impact on the disease. The model was calibrated to HIV and AIDS incidence data from Malaysia Ministry of Health from the period of 1986 to 2011 using Bayesian analysis with combination of Markov chain Monte Carlo method (MCMC) approach to estimate the model parameters. From the estimated parameters, the estimated basic reproduction number was 22.5812. The rate at which the susceptible individual moved to HIV compartment has the highest sensitivity value which is more significant as compared to the remaining parameters. Thus, the disease becomes unstable. This is a big concern and not good indicator from the public health point of view since the aim is to stabilize the epidemic at the disease-free equilibrium. However, these results suggest that the government as a policy maker should make further efforts to curb illegal activities performed by migrants. It is shown that our models reflect considerably the dynamic behavior of the HIV/AIDS epidemic in Malaysia and eventually could be used strategically for other countries.

Keywords: epidemic model, reproduction number, HIV, MCMC, parameter estimation

Procedia PDF Downloads 351