Search results for: 3D plant data

Authors: Ayman Baklizi

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Based on type II censored data, we consider interval estimation of the quantiles of the two-parameter exponential distribution and the difference between the quantiles of two independent two-parameter exponential distributions. We derive asymptotic intervals, Bayesian, as well as intervals based on the generalized pivot variable. We also include some bootstrap intervals in our comparisons. The performance of these intervals is investigated in terms of their coverage probabilities and expected lengths.

Keywords: asymptotic intervals, Bayes intervals, bootstrap, generalized pivot variables, two-parameter exponential distribution, quantiles

Procedia PDF Downloads 402

Authors: L. Al-Mulla, B. M. Thomas, N. R. Bhat, M. K. Suleiman, P. George

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Mangroves are halophytic shrubs habituated in the intertidal zones in the tropics and subtropics, forming a complex and highly dynamic coastal ecosystem. Historical evidence indicating the existence followed by the extinction of mangrove in Kuwait; hence, continuous projects have been established to reintroduce this plant to the marine ecosystem. One of the major challenges in establishing large-scale mangrove plantations in Kuwait is the very high rate of seedling mortality, which should ideally be less than 20%. This study was conducted at three selected locations in the Kuwait bay during 2016-2017, to evaluate the effect of four planting techniques on mangrove seedling establishment. Coir-pillow planting technique, comp-mat planting technique, and anchored container planting technique were compared with the conventional planting method. The study revealed that the planting techniques significantly affected the establishment of mangrove seedlings in the initial stages of growth. Location-specific difference in seedling establishment was also observed during the course of the study. However, irrespective of the planting techniques employed, high seedling mortality was observed in all the planting locations towards the end of the study; which may be attributed to the physicochemical characteristics of the mudflats selected.

Keywords: Avicennia marina (Forsk.) Vierh, coastal pollution, heavy metal accumulation, marine ecosystem, sedimentation, tidal inundation

Procedia PDF Downloads 142

Authors: Nihar Bheda

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Protecting digital assets such as networks, systems, and data from advanced cyber threats is the aim of Digital Immunity Systems (DIS), which are a subset of cybersecurity. With features like continuous monitoring, coordinated reactions, and long-term adaptation, DIS seeks to mimic biological immunity. This minimizes downtime by automatically identifying and eliminating threats. Traditional security measures, such as firewalls and antivirus software, are insufficient for enterprises, such as healthcare providers, given the rapid evolution of cyber threats. The number of medical record breaches that have occurred in recent years is proof that attackers are finding healthcare data to be an increasingly valuable target. However, obstacles to enhancing security include outdated systems, financial limitations, and a lack of knowledge. DIS is an advancement in cyber defenses designed specifically for healthcare settings. Protection akin to an "immune system" is produced by core capabilities such as anomaly detection, access controls, and policy enforcement. Coordination of responses across IT infrastructure to contain attacks is made possible by automation and orchestration. Massive amounts of data are analyzed by AI and machine learning to find new threats. After an incident, self-healing enables services to resume quickly. The implementation of DIS is consistent with the healthcare industry's urgent requirement for resilient data security in light of evolving risks and strict guidelines. With resilient systems, it can help organizations lower business risk, minimize the effects of breaches, and preserve patient care continuity. DIS will be essential for protecting a variety of environments, including cloud computing and the Internet of medical devices, as healthcare providers quickly adopt new technologies. DIS lowers traditional security overhead for IT departments and offers automated protection, even though it requires an initial investment. In the near future, DIS may prove to be essential for small clinics, blood banks, imaging centers, large hospitals, and other healthcare organizations. Cyber resilience can become attainable for the whole healthcare ecosystem with customized DIS implementations.

Keywords: digital immunity system, cybersecurity, healthcare data, emerging technology

Procedia PDF Downloads 52

Authors: Jirathan Pongchababnapa

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Polyphenols are the most common antioxidant found in plants and are efficient in capturing oxidative free radicals. Antioxidants are substances found in medicinal plants which may have a protective role to play in certain conditions such as heart disease, stroke and some cancers. By relying on these benefits, we have traced out the presence of antioxidant in Camellia sinensis leaves extract. This study aims to evaluate flavonoids content in C. sinensisextract and investigate antioxidant activities by using DPPH and ABTS radical scavenging capacity assay. The total flavonoid content of C. Sinensis extract was determined and expressed as quercetin equivalents (QE)/g measured by the aluminum chloride colorimetric method. The results showed that the IC₅₀ of C. Sinensis leaves extract were 40.90 μg/mL ± 0.755 and32.96 μg/mL ± 0.679 for DPPH and ABTS, respectively. C. Sinensis extract at increasing concentration showed antioxidant activities as a concentration dependent manner. In the DPPH assay, vitamin C was used as a positive control, whereas Trolox was used as a positive control in the ABTS assay. In conclusion, C. Sinensis extract consisted of a high amount of flavonoids content which possesses potent antioxidant activity. However, further investigation on the identification of pure compound of this plant and molecular antioxidant assays are still required.

Keywords: ABTS assay, antioxidant, camellia sinensis, DPPH assay, total flavonoid content

Procedia PDF Downloads 190

Authors: Javier Donoso-Bravo, Camila Cortés-Zambrano

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In this paper, we analyze socioterritorial inequalities in the region of Valparaiso (Chile) using secondary data to account for these inequalities drawing on economic, social, educational, and environmental dimensions regarding the thirty-six municipalities of the region. We looked over a wide-ranging set of secondary data from public sources regarding economic activities, poverty, employment, income, years of education, post-secondary education access, green areas, access to potable water, and others. We found sharp socioterritorial inequalities especially based on the economic performance in each territory. Analysis show, on the one hand, the existence of a dual and unorganized development model in some territories with a strong economic activity -especially in the areas of finance, real estate, mining, and vineyards- but, at the same time, with poor social indicators. On the other hand, most of the territories show a dispersed model with very little dynamic economic activities and very poor social development. Finally, we discuss how socioterritorial inequalities in the region of Valparaiso reflect the level of globalization of the economic activities carried on in every territory.

Keywords: socioterritorial inequalities, development model, Chile, secondary data, Region of Valparaiso

Procedia PDF Downloads 83

Authors: M. A. Okezue, K. L. Clase, S. R. Byrn

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The requirement for maintaining data integrity in laboratory operations is critical for regulatory compliance. Automation of procedures reduces incidence of human errors. Quality control laboratories located in low-income economies may face some barriers in attempts to automate their processes. Since data from quality control tests on pharmaceutical products are used in making regulatory decisions, it is important that laboratory reports are accurate and reliable. Zinc Sulphate (ZnSO₄) tablets is used in treatment of diarrhea in pediatric population, and as an adjunct therapy for COVID-19 regimen. Unfortunately, zinc content in these formulations is determined titrimetrically; a manual analytical procedure. The assay for ZnSO4 tablets involves time-consuming steps that contain mathematical formulae prone to calculation errors. To achieve consistency, save costs, and improve data integrity, validated spreadsheets were developed to simplify the two critical steps in the analysis of ZnSO4 tablets: standardization of 0.1M Sodium Edetate (EDTA) solution, and the complexometric titration assay procedure. The assay method in the United States Pharmacopoeia was used to create a process flow for ZnSO₄ tablets. For each step in the process, different formulae were input into two spreadsheets to automate calculations. Further checks were created within the automated system to ensure validity of replicate analysis in titrimetric procedures. Validations were conducted using five data sets of manually computed assay results. The acceptance criteria set for the protocol were met. Significant p-values (p < 0.05, α = 0.05, at 95% Confidence Interval) were obtained from students’ t-test evaluation of the mean values for manual-calculated and spreadsheet results at all levels of the analysis flow. Right-first-time analysis and principles of data integrity were enhanced by use of the validated spreadsheet calculators in titrimetric evaluations of ZnSO₄ tablets. Human errors were minimized in calculations when procedures were automated in quality control laboratories. The assay procedure for the formulation was achieved in a time-efficient manner with greater level of accuracy. This project is expected to promote cost savings for laboratory business models.

Keywords: data integrity, spreadsheets, titrimetry, validation, zinc sulphate tablets

Procedia PDF Downloads 156

Authors: Mehdi Basirat, Mohammad Rouhani, Shahla Borzouei, Majid Zarangi, Asma Abolghasemi, Mohammad Fazel Soltani, Mohammad Gorji, Mohammad Amin Samih

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The common pistachio psylla, Agonoscena pistaciae Burckhardt and Lauterer (Hemiptera: Aphalaridae), as one of the most detrimental pests in all pistachio producing regions, causes great economic damages to pistachio trees. Nowadays, various pesticides are used to control the common pistachio psylla and robust pesticide exposure has occurred in orchards. In this study, field experiments were conducted during 2018–2021 to assess the effects of sulfur on A. pistaciae. This study compared sulfur with asafoetida extract and pesticide (acetamiprid) on A. pistaciae based on complete randomized blocks with three replications. The analysis results of variance showed that the effect of treatments on egg (F2,24 = 17.61, P = 0.00) and nymphs (F2,24 = 18.29, P = 0.00) had a significant difference at a 1% level. The results demonstrated that sulfur had the highest measure of control on eggs and nymphs significantly compared to the plant extract and pesticide (negative control). These results provide support to the potential use of sulfur as an alternative pest management tool against A. pistaciae. The results clearly indicated that sulfur could control the common pistachio psylla population for six weeks at least.

Keywords: Agonoscena pistaciae, pesticide exposure, pistachio, sulfur

Procedia PDF Downloads 149

Authors: Sonalee Das, Smita Mohanty, S. K. Nayak

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Recent years has witnessed the increasing demand for natural resources and products in polyurethane synthesis because of global warming, sustainable development and oil crisis. For this purpose, different plant oils such as soybean oil, castor oil and linseed oil are extensively used. Moreover, the isocyanate used for the synthesis of polyurethane is derived from petroleum resources. In this present work attempts have been made for the successful synthesis of biobased isocyanate from castor oil with partially biobased isocyanate in presence of catalyst dibutyltin dilaurate (DBTDL). The goal of the present study was to investigate the thermal, mechanical, morphological and chemical properties of the synthesized polyurethane in terms of castor oil modification. The transesterified polyol shows broad and higher hydroxyl value as compared to castor oil which was confirmed by FTIR studies. The FTIR studies also revealed the successful synthesis of bio based polyurethane by showing characteristic peaks at 3300cm-1, 1715cm-1 and 1532cm-1 respectively. The TGA results showed three step degradation mechanism for the synthesized polyurethane from modified and unmodified castor oil. However, the modified polyurethane exhibited higher degradation temperature as compared to unmodified one. The mechanical properties also demonstrated higher tensile strength for modified polyurethane as compared to unmodified one.

Keywords: castor oil, partially biobased Isocyanate, polyurethane synthesis, FTIR

Procedia PDF Downloads 334

Authors: Carolina Silva, João Nuno Oliveira, Rui Sousa, João Paulo Silva

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This study uses genetic algorithms to solve a job scheduling problem in a weaving factory. The underline problem regards an NP-Hard problem concerning unrelated parallel machines, with sequence-dependent setup times. This research uses real data regarding a weaving industry located in the North of Portugal, with a capacity of 96 looms and a production, on average, of 440000 meters of fabric per month. Besides, this study includes a high level of complexity once most of the real production constraints are applied, and several real data instances are tested. Topics such as data analyses and algorithm performance are addressed and tested, to offer a solution that can generate reliable and due date results. All the approaches will be tested in the operational environment, and the KPIs monitored, to understand the solution's impact on the production, with a particular focus on the total number of weeks of late deliveries to clients. Thus, the main goal of this research is to develop a solution that allows for the production of automatically optimized production plans, aiming to the tardiness minimizing.

Keywords: genetic algorithms, textile industry, job scheduling, optimization

Procedia PDF Downloads 140

Authors: Lima Priscila, Gianotto Raiza, Arruda Leonan, Magalhães Filho Fernando

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Industrialization and especially the accentuated population growth in developing countries and the lack of drainage, public cleaning, water and sanitation services has caused concern about the need for expansion of water treatment units and sewage. However, these units have been generating by-products, such as the sludge. This paper aims to investigate aspects of operation and maintenance of sludge from a wastewater treatment plant (WWTP - 90 L.s-1) and two water treatment plants (WTPs; 1.4 m3.s-1 and 0.5 m3.s-1) for the purpose of proper disposal and reuse, evaluating their qualitative and quantitative characteristics, the Brazilian legislation and standards. It was concluded that the sludge from the water treatment plants is directly related to the quality of raw water collected, and it becomes feasible for use in construction materials, and to dispose it in the sewage system, improving the efficiency of the WWTP regarding precipitation of phosphorus (35% of removal). The WTP Lageado had 55,726 kg/month of sludge production, more than WTP Guariroba (29,336 kg/month), even though the flow of WTP Guariroba is 1,400 L.s-1 and the WTP Lagedo 500 L.s-1, being explained by the quality that influences more than the flow. The WWTP sludge have higher concentrations of organic materials due to their origin and could be used to improve the fertility of the soil, crop production and recovery of degraded areas. The volume of sludge generated at the WWTP was 1,760 ton/month, with 5.6% of solid content in the raw sludge and in the dewatered sludge it increased its content to 23%.

Keywords: disposal, sludge, water treatment, wastewater treatment

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Authors: Francisco M. Silva

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Technology is evolving, creating an impact on our everyday lives and the telehealth industry. Telehealth encapsulates the provision of healthcare services and information via a technological approach. There are several benefits of using web-based methods to provide healthcare help. Nonetheless, few health and psychological help approaches combine this method with wearable sensors. This paper aims to create an online platform for users to receive self-care help and information using wearable sensors. In addition, researchers developing a similar project obtain a solid foundation as a reference. This study provides descriptions and analyses of the software and hardware architecture. Exhibits and explains a heart rate dynamic and efficient algorithm that continuously calculates the desired sensors' values. Presents diagrams that illustrate the website deployment process and the webserver means of handling the sensors' data. The goal is to create a working project using Arduino compatible hardware. Heart rate sensors send their data values to an online platform. A microcontroller board uses an algorithm to calculate the sensor heart rate values and outputs it to a web server. The platform visualizes the sensor's data, summarizes it in a report, and creates alerts for the user. Results showed a solid project structure and communication from the hardware and software. The web server displays the conveyed heart rate sensor's data on the online platform, presenting observations and evaluations.

Keywords: Arduino, heart rate BPM, microcontroller board, telehealth, wearable sensors, web-based healthcare

Procedia PDF Downloads 112

Authors: Runglaksamee Rodkam

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The purpose of this research was to study the influence of accountants’ potential performance on their working process, a case study of Government Savings Banks in the northeast of Thailand. The independent variables included accounting knowledge, accounting skill, accounting value, accounting ethics, and accounting attitude, while the dependent variable included the success of the working process. A total of 155 accountants working for Government Savings Banks were selected by random sampling. A questionnaire was used as a tool for collecting data. Descriptive statistics in this research included percentage, mean, and multiple regression analyses. The findings revealed that the majority of accountants were female with an age between 35-40 years old. Most of the respondents had an undergraduate degree with ten years of experience. Moreover, the factors of accounting knowledge, accounting skill, accounting a value and accounting ethics and accounting attitude were rated at a high level. The findings from regression analysis of observation data revealed a causal relationship in that the observation data could explain at least 51 percent of the success in the accountants’ working process.

Keywords: influence, potential performance, success, working process

Procedia PDF Downloads 240

Authors: Ahmed El-Banbi, Ahmed El-Maraghi

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PVT properties are needed as input data in all reservoir, production, and surface facilities engineering calculations. In the absence of PVT reports on valid reservoir fluid samples, engineers rely on PVT correlations to generate the required PVT data. The accuracy of PVT correlations varies, and no correlation group has been found to provide accurate results for all oil types. The effect of inaccurate PVT data can be significant in engineering calculations and is well documented in the literature. Bubble point pressure can sometimes be obtained from external sources. In this paper, we show how to utilize the known bubble point pressure to improve the accuracy of calculated PVT properties from correlations. We conducted a systematic study using around 250 reservoir oil samples to quantify the effect of pre-knowledge of bubble point pressure. The samples spanned a wide range of oils, from very volatile oils to black oils and all the way to low-GOR oils. A method for shifting both undersaturated and saturated sections of the PVT properties curves to the correct bubble point is explained. Seven PVT correlation families were used in this study. All PVT properties (e.g., solution gas-oil ratio, formation volume factor, density, viscosity, and compressibility) were calculated using the correct bubble point pressure and the correlation estimated bubble point pressure. Comparisons between the calculated PVT properties and actual laboratory-measured values were made. It was found that pre-knowledge of bubble point pressure and using the shifting technique presented in the paper improved the correlation-estimated values by 10% to more than 30%. The most improvement was seen in the solution gas-oil ratio and formation volume factor.

Keywords: PVT data, PVT properties, PVT correlations, bubble point pressure

Procedia PDF Downloads 48

Authors: J. Name, S. Bumroongsook

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The laboratory and field studies was conducted at King Monkut’s Institute of Technology Ladkrabang to determine biological and morphological aspects of a sweet potato bug ( Physomerus grossipes F.)(Heteroptera). It belongs to the family Coreidae. This insect lays eggs underside of leaves or on the stem of water convolvulus ( Ipomoea aquatic Forsk ) naturally grown in asiatic pennywort plantations. Male and female adults, aged 12-16 day, are known to have multiple mating. Its copulatory position was observed as end to end position which was lasted as long as for 9-60 hours. Groups of eggs were attached to parts of host plants. The egg normally hatches in 16.00-17.50 days(mean 16.63±0.53days). They have 5 nymphal stages and pass through 5 molts before reaching maturity as follows:the first instar 3.83-4.25 days(mean 4.09±0.13 days), the second instar 15.25-27.63 days(mean 20.86± 3.24 days), the third nymphs instar 15.25-27.63 days(mean 20.86±4.42 days), the fourth nymphs 7.29-14.25 days(mean 10.42±2.64 day) and the fifth nymphs 12.58-18.00 days(mean 14.88±1.53 days).These nymphs tend to stay together and suck plant sap from stolons and stems of water convolvulus. The fifth nymps are morphologically similar to adults and they have small wing pads. Adult bugs have full grown wings which cover the abdomen. Total developmental time from egg to adult takes about 104-123 days.

Keywords: morphological aspects, sweet potato bugs (Physomerus grossipes F.), water convolvulus

Procedia PDF Downloads 301

Authors: Khlood F. Salman, Richard Zoucha, Hani Nawafleh

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Introduction: Jordan ranks the fourth highest breast cancer prevalence after Lebanon, Bahrain, and Kuwait. Considerable evidence showed that cultural, ethnic, and economic differences influence a woman’s practice to early detection and prevention of breast cancer. Objectives: To understand women’s health beliefs and values in relation to early detection of breast cancer; and to explore the impact of these beliefs on their decisions regarding reluctance or acceptance of early detection measures such as mammogram screening. Design: A qualitative focused ethnography was used to collect data for this study. Settings: The study was conducted in the second largest city surrounded by a large rural area in Ma’an- Jordan. Participants: A total of twenty seven women, with no history of breast cancer, between the ages of 18 and older, who had prior health experience with health providers, and were willing to share elements of personal health beliefs related to breast health within the larger cultural context. The participants were recruited using the snowball method and words of mouth. Data collection and analysis: A short questionnaire was designed to collect data related to socio demographic status (SDQ) from all participants. A Semi-structured interviews guide was used to elicit data through interviews with the informants. Nvivo10 a data manager was utilized to assist with data analysis. Leininger’s four phases of qualitative data analysis was used as a guide for the data analysis. The phases used to analyze the data included: 1) Collecting and documenting raw data, 2) Identifying of descriptors and categories according to the domains of inquiry and research questions. Emic and etic data is coded for similarities and differences, 3) Identifying patterns and contextual analysis, discover saturation of ideas and recurrent patterns, and 4) Identifying themes and theoretical formulations and recommendations. Findings: Three major themes were emerged within the cultural and religious context; 1. Fear, denial, embarrassment and lack of knowledge were common perceptions of Ma’anis’ women regarding breast health and screening mammography, 2. Health care professionals in Jordan were not quick to offer information and education about breast cancer and screening, and 3. Willingness to learn about breast health and cancer prevention. Conclusion: The study indicated the disparities between the infrastructure and resourcing in rural and urban areas of Jordan, knowledge deficit related to breast cancer, and lack of education about breast health may impact women’s decision to go for a mammogram screening. Cultural beliefs, fear, embarrassments as well as providers lack of focus on breast health were significant contributors against practicing breast health. Health providers and policy makers should provide resources for the establishment health education programs regarding breast cancer early detection and mammography screening. Nurses should play a major role in delivering health education about breast health in general and breast cancer in particular. A culturally appropriate health awareness messages can be used in creating educational programs which can be employed at the national levels.

Keywords: breast health, beliefs, cultural context, ethnography, mammogram screening

Procedia PDF Downloads 279

Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

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Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

Procedia PDF Downloads 363

Authors: Vishwa Joshi

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The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques and many audio features contributing considerably to analyze and identify the relation of mood plus music. In this paper we consider the same idea forward and come up with making an effort to build a system for automatic recognition of mood underlying the audio song’s clips by mining their audio features and have evaluated several data classification algorithms in order to learn, train and test the model describing the moods of these audio songs and developed an open source framework. Before classification, Preprocessing and Feature Extraction phase is necessary for removing noise and gathering features respectively.

Keywords: music, mood, features, classification

Procedia PDF Downloads 484

Authors: Soha A. Bahanshal, Vaibhav Verdhan, Bayong Kim

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Graduation rates at six-year colleges are becoming a more essential indicator for incoming fresh students and for university rankings. Predicting student graduation is extremely beneficial to schools and has a huge potential for targeted intervention. It is important for educational institutions since it enables the development of strategic plans that will assist or improve students' performance in achieving their degrees on time (GOT). A first step and a helping hand in extracting useful information from these data and gaining insights into the prediction of students' progress and performance is offered by machine learning techniques. Data analysis and visualization techniques are applied to understand and interpret the data. The data used for the analysis contains students who have graduated in 6 years in the academic year 2017-2018 for science majors. This analysis can be used to predict the graduation of students in the next academic year. Different Predictive modelings such as logistic regression, decision trees, support vector machines, Random Forest, Naïve Bayes, and KNeighborsClassifier are applied to predict whether a student will graduate. These classifiers were evaluated with k folds of 5. The performance of these classifiers was compared based on accuracy measurement. The results indicated that Ensemble Classifier achieves better accuracy, about 91.12%. This GOT prediction model would hopefully be useful to university administration and academics in developing measures for assisting and boosting students' academic performance and ensuring they graduate on time.

Keywords: prediction, decision trees, machine learning, support vector machine, ensemble model, student graduation, GOT graduate on time

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Authors: Eden Teshome Hunde

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Wireless sensor and actuator networks (WSANs) are of great significance in the realm of industrial automation systems. However, the aspect of security in WSANs has been somewhat overlooked. One particular security concern is the rank attack, where malicious actors actively manipulate the transmission of messages from neighboring nodes. This undermines the entire network's data collection and routing operations, resulting in a significant degradation of network performance. This attack adversely affects crucial metrics such as packet delivery ratio (PDR), latency, and power consumption, ultimately reducing the network's overall lifespan. In order to foster trust among nodes, ensure accurate delivery of data to end users, safeguard shared data in the cloud from security breaches, and prevent rank attacks within the network, it is crucial to protect the network against such malicious activities. This research paper aims to introduce an enhanced version of the Routing Protocol for Low-Power and Lossy Networks (RPL) protocol, specifically tailored to identify and eliminate rank attacks within existing WSANs. The effectiveness of the new protocol will be assessed through experimentation using Zolertia (Z1) sensors in the Cooja network simulator. To minimize network overhead on the sensors' side, the proposed scheme limits cryptographic operations to symmetric key-based mechanisms such as XORing, hash functions, and encryption. These operations will be implemented using a C-compiler and verified through the ModelSIM Altera SE edition 11.0 simulator.

Keywords: ModelSIM Altera SE, RPL, WSANs, Zolertia

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Authors: Syed Basit Ali Shah Bukhari, Yan Qiang, Saad Abdul Rauf, Syed Saqlaina Bukhari

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Text Classification is the methodology to classify any given text into the respective category from a given set of categories. It is highly important and vital to use proper set of pre-processing , feature selection and classification techniques to achieve this purpose. In this paper we have used different ensemble techniques along with variance in feature selection parameters to see the change in overall accuracy of the result and also on some other individual class based features which include precision value of each individual category of the text. After subjecting our data through pre-processing and feature selection techniques , different individual classifiers were tested first and after that classifiers were combined to form ensembles to increase their accuracy. Later we also studied the impact of decreasing the classification categories on over all accuracy of data. Text classification is highly used in sentiment analysis on social media sites such as twitter for realizing people’s opinions about any cause or it is also used to analyze customer’s reviews about certain products or services. Opinion mining is a vital task in data mining and text categorization is a back-bone to opinion mining.

Keywords: Natural Language Processing, Ensemble Classifier, Bagging Classifier, AdaBoost

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Authors: Mukesh Kumar, Mahendra Pal Sharma

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Depleting fossil fuel resources coupled with serious environmental degradation has led to the search for alternative resources for biodiesel production as a substitute of Petro-diesel. Currently, edible, non-edible oils and microalgal plant species are cultivated for biodiesel production. Looking at the demerits of edible and non-edible oil resources, the focus is being given to grow microalgal species having high oil productivities, less maturity time and less land requirement. Out of various microalgal species, Chlorella protothecoides is considered as the most promising species for biodiesel production owing to high oil content (58 %), faster growth rate (24–48 h) and high biomass productivity (1214 mg/l/day). The present paper reports the results of optimization of reaction parameters of transesterification process as well as the kinetics of transesterification with 97% yield of biodiesel. The measurement of fuel quality of microalgal biodiesel shows that the biodiesel exhibit very good oxidation stability (O.S) of 7 hrs, more than ASTM D6751 (3 hrs) and EN 14112 (6 hrs) specifications. The CP and PP of 0 and -3 °C are finding as per ASTM D 2500-11 and ASTM D 97-12 standards. These results show that the microalgal biodiesel does not need any enhancement in O.S & CFP and hence can be recommended to be directly used as MB100 or its blends into diesel engine operation. Further, scope is available for the production of binary blends using poor quality biodiesel for engine operation.

Keywords: fuel quality, methyl ester yield, microalgae, transesterification

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Authors: Qasim Kriri, Harsh B. Desai

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Water supply and sanitation in Saudi Arabia is portrayed by difficulties and accomplishments. One of the fundamental difficulties is water shortage. With a specific end goal to beat water shortage, significant ventures have been attempted in sea water desalination, water circulation, sewerage, and wastewater treatment. The motivation behind Statistical Process Control (SPC) is to decide whether the execution of a procedure is keeping up an acceptable quality level [AQL]. SPC is an analytical decision-making method. A fundamental apparatus in the SPC is the Control Charts, which follow the inconstancy in the estimations of the item quality attributes. By utilizing the suitable outline, administration can decide whether changes should be made with a specific end goal to keep the procedure in charge. The two most important quality factors in the distilled water which were taken into consideration were pH (Potential of Hydrogen) and TDS (Total Dissolved Solids). There were three stages at which the quality checks were done. The stages were as follows: (1) Water at the source, (2) water after chemical treatment & (3) water which is sent for packing. The upper specification limit, central limit and lower specification limit are taken as per Saudi water standards. The procedure capacity to accomplish the particulars set for the quality attributes of Berain water Factory chose to be focused by the proposed SPC system.

Keywords: acceptable quality level, statistical quality control, control charts, process charts

Procedia PDF Downloads 172

Authors: Zahra Amirhosseini, Mahtab Nameni

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The aim of this study was to investigate the relationship between growth, beta, and Company's cash. We calculate cash as dependent variable and growth opportunity and beta as independent variables. This study was based on an analysis of panel data. Population of the study is the companies which listed in Tehran Stock exchange and a financial data of 215 companies during the period 2010 to 2015 have been selected as the sample through systematic sampling. The results of the first hypothesis showed there is a significant relationship between growth opportunities cash holdings. Also according to the analysis done in the second hypothesis, we determined that there is an inverse relation between company risk and cash holdings.

Keywords: growth, beta, liquidity, company

Procedia PDF Downloads 379

Authors: Diana Codat

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Tweets' analysis is part of text mining. Each document is a written text. It's possible to apply the usual text search techniques, in particular by switching to the bag-of-words representation. But the tweets induce peculiarities. Some may enrich the analysis. Thus, their length is calibrated (at least as far as public messages are concerned), special characters make it possible to identify authors (@) and themes (#), the tweet and retweet mechanisms make it possible to follow the diffusion of the information. Conversely, other characteristics may disrupt the analyzes. Because space is limited, authors often use abbreviations, emoticons to express feelings, and they do not pay much attention to spelling. All this creates noise that can complicate the task. The tweets carry a lot of potentially interesting information. Their exploitation is one of the main axes of the analysis of the social networks. We show how to access Twitter-related messages. We will initiate a study of the properties of the tweets, and we will follow up on the exploitation of the content of the messages. We will work under R with the package 'twitteR'. The study of tweets is a strong focus of analysis of social networks because Twitter has become an important vector of communication. This example shows that it is easy to initiate an analysis from data extracted directly online. The data preparation phase is of great importance.

Keywords: data mining, language R, social networks, Twitter

Procedia PDF Downloads 162

Authors: Fu-Pei Hsiao, Fung-Chung Tu, Chien-Kuo Chiu

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In this work, to develop a method for detailed assesses of post-earthquake seismic performance for RC buildings in Taiwan, experimental data for several column specimens with various failure modes (flexural failure, flexural-shear failure, and shear failure) are used to derive reduction factors of seismic capacity for specified damage states. According to the damage states of RC columns and their corresponding seismic reduction factors suggested by experimental data, this work applies the detailed seismic performance assessment method to identify the seismic capacity of earthquake-damaged RC buildings. Additionally, a post-earthquake emergent assessment procedure is proposed that can provide the data needed for decision about earthquake-damaged buildings in a region with high seismic hazard. Finally, three actual earthquake-damaged school buildings in Taiwan are used as a case study to demonstrate application of the proposed assessment method.

Keywords: seismic assessment, seismic reduction factor, residual seismic ratio, post-earthquake, reinforced concrete, building

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Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

Abstract:

Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

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Authors: R. Venkatesan, A. Sabari

Abstract:

Developments of social networking internet scenario are recommended for the requirements of scalable, authentic, secure group communication model like multicasting. Multicasting is an inter network service that offers efficient delivery of data from a source to multiple destinations. Even though multicast has been very successful at providing an efficient and best-effort data delivery service for huge groups, it verified complex process to expand other features to multicast in a scalable way. Separately, the requirement for secure electronic information had become gradually more apparent. Since multicast applications are deployed for mainstream purpose the need to secure multicast communications will become significant.

Keywords: multicasting, scalability, security, social network

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Authors: Rusnardi Rahmat Putra, Junji Kiyono, Aiko Furukawa

Abstract:

Several powerful earthquakes have struck Padang during recent years, one of the largest of which was an M 7.6 event that occurred on September 30, 2009 and caused more than 1000 casualties. Following the event, we conducted a 12-site microtremor array investigation to gain a representative determination of the soil condition of subsurface structures in Padang. From the dispersion curve of array observations, the central business district of Padang corresponds to relatively soft soil condition with Vs30 less than 400 m/s. because only one accelerometer existed, we simulated the 2009 Padang earthquake to obtain peak ground acceleration for all sites in Padang city. By considering the damage data of the 2009 Padang earthquake, we produced seismic risk vulnerability estimation of non-engineered houses for rock, medium and soft soil condition. We estimated the loss ratio based on the ground response, seismic hazard of Padang and the existing damaged to non-engineered structure houses due to Padang earthquake in 2009 data for several return periods of earthquake events.

Keywords: profile, Padang earthquake, microtremor array, seismic vulnerability

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Authors: Ammar Alali, Mahmoud Abughaban, William Contreras Otalvora

Abstract:

Optimizing the drilling process for cost and efficiency requires the optimization of the rate of penetration (ROP). ROP is the measurement of the speed at which the wellbore is created, in units of feet per hour. It is the primary indicator of measuring drilling efficiency. Maximization of the ROP can indicate fast and cost-efficient drilling operations; however, high ROPs may induce unintended events, which may lead to nonproductive time (NPT) and higher net costs. The proposed ROP optimization solution is a hybrid, data-driven system that aims to improve the drilling process, maximize the ROP, and minimize NPT. The system consists of two phases: (1) utilizing existing geological and drilling data to train the model prior, and (2) real-time adjustments of the controllable dynamic drilling parameters [weight on bit (WOB), rotary speed (RPM), and pump flow rate (GPM)] that direct influence on the ROP. During the first phase of the system, geological and historical drilling data are aggregated. After, the top-rated wells, as a function of high instance ROP, are distinguished. Those wells are filtered based on NPT incidents, and a cross-plot is generated for the controllable dynamic drilling parameters per ROP value. Subsequently, the parameter values (WOB, GPM, RPM) are calculated as a conditioned mean based on physical distance, following Inverse Distance Weighting (IDW) interpolation methodology. The first phase is concluded by producing a model of drilling best practices from the offset wells, prioritizing the optimum ROP value. This phase is performed before the commencing of drilling. Starting with the model produced in phase one, the second phase runs an automated drill-off test, delivering live adjustments in real-time. Those adjustments are made by directing the driller to deviate two of the controllable parameters (WOB and RPM) by a small percentage (0-5%), following the Constrained Random Search (CRS) methodology. These minor incremental variations will reveal new drilling conditions, not explored before through offset wells. The data is then consolidated into a heat-map, as a function of ROP. A more optimum ROP performance is identified through the heat-map and amended in the model. The validation process involved the selection of a planned well in an onshore oil field with hundreds of offset wells. The first phase model was built by utilizing the data points from the top-performing historical wells (20 wells). The model allows drillers to enhance decision-making by leveraging existing data and blending it with live data in real-time. An empirical relationship between controllable dynamic parameters and ROP was derived using Artificial Neural Networks (ANN). The adjustments resulted in improved ROP efficiency by over 20%, translating to at least 10% saving in drilling costs. The novelty of the proposed system lays is its ability to integrate historical data, calibrate based geological formations, and run real-time global optimization through CRS. Those factors position the system to work for any newly drilled well in a developing field event.

Keywords: drilling optimization, geological formations, machine learning, rate of penetration

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Authors: Ayodele Adelusi Oyedeji

Abstract:

The study was carried out under a controlled environment with the aim of examining remediation of crude oil polluted soil. The germination rate, heights and girths, number of leaves and nodulation was determined following standard procedures. Some physicochemical (organic matter, pH, nitrogen, phosphorous, potassium, calcium, magnesium and sodium) characteristics of soil used were determined using standard protocols. Results showed that at varying concentration of crude oil i.e 0 ml, 25 ml, 50 ml, 75 ml and 100 ml, Leuceana leucocephala had germination rate of 92%, 90%, 84%, 62% and 56% respectively, mean height of 73.70cm, 58.30cm, 49.50cm, 46.45cm and 41.80cm respectively after 16 weeks after planting (WAP), mean girth of 0.54mm, 0.34mm, 0.33mm, 0.21mm and 0.19mm respectively at 16 WAP, number of nodules 18, 10, 10, 6 and 2 respectively and number of leaves 24.00, 16.00, 13.00, 10.00 and 6.00 respectively. The organic matter, pH, nitrogen, phosphorous, potassium, calcium, magnesium, and sodium decreased with the increase in the concentration of crude oil. Furthermore, as the concentration of crude oil increased the germination rate, height, girth, and number of leaves and nodules decreased, suggesting the effect of crude oil on Leuceana leucocephala. The plant withstands the varying concentration of the crude oil means that it could be used for the remediation of crude oil contaminated soil in the Niger Delta region of Nigeria.

Keywords: ecosystem conservation, Leuceana leucocephala, phytoremediation, soil pollution

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