Search results for: sequential pattern mining

Authors: Sukla Saha, Alok Sinha

Abstract:

Acid mine drainage (AMD) refers to the production of acidified water from abandoned mines and active mines as well. The reason behind the generation of this kind of acidified water is the oxidation of pyrites present in the rocks in and around mining areas. Thiobacillus ferrooxidans, which is a sulfur oxidizing bacteria, helps in the oxidation process. AMD is extremely acidic in nature, (pH 2-3) with high concentration of several trace and heavy metals such as Fe, Al, Zn, Mn, Cu and Co and anions such as chloride and sulfate. AMD has several detrimental effect on aquatic organism and environment. It can directly or indirectly contaminate the ground water and surface water as well. The present study considered the treatment of AMD with metallurgical slag, which is a waste material. Slag helped to enhance the pH of AMD to 8.62 from 1.5 with 99% removal of trace metals such as Fe, Al, Mn, Cu and Co. Metallurgical slag was proven as efficient neutralizing material for the treatment of AMD.

Keywords: acid mine drainage, Heavy metals, metallurgical slag, Neutralization

Procedia PDF Downloads 187

Authors: Amin Derakhshan, Mohammad Mikaili, Mohammad Ali Khalilzadeh, Amin Mohammadian

Abstract:

This paper proposes a stress recognition system from multi-modal bio-potential signals. For stress recognition, Support Vector Machines (SVM) and LDA are applied to design the stress classifiers and its characteristics are investigated. Using gathered data under psychological polygraph experiments, the classifiers are trained and tested. The pattern recognition method classifies stressful from non-stressful subjects based on labels which come from polygraph data. The successful classification rate is 96% for 12 subjects. It means that facial thermal imaging due to its non-contact advantage could be a remarkable alternative for psycho-physiological methods.

Keywords: stress, thermal imaging, face, SVM, polygraph

Procedia PDF Downloads 486

Authors: Virginia Melnyk

Abstract:

This paper explores the design for catenary structure using knitted textiles. Using the advantages of Grasshopper and Kangaroo parametric software to simulate and pre-design an overall form, the design is then translated to a pattern that can be made with hand manipulated stitches on a knitting machine. The textile takes advantage of the structure of knitted materials and the ability for it to stretch. Using different types of stitches to control the amount of stretch that can occur in portions of the textile generates an overall formal design. The textile is then hardened in an upside-down hanging position and then flipped right-side-up. This then becomes a structural catenary form. The resulting design is used as a small Cat House for a cat to sit inside and climb on top of.

Keywords: architectural materials, catenary structures, knitting fabrication, textile design

Procedia PDF Downloads 183

Authors: Seung-Hwan Ju, Yo-Han Choi, Hee-Suk Seo, Tae-Kyung Kim

Abstract:

This study investigates the permissions requested by Android applications, and the possibility of identifying suspicious applications based only on information presented to the user before an application is downloaded. The pattern analysis is based on a smaller data set consisting of confirmed malicious applications. The method is evaluated based on its ability to recognize malicious potential in the analyzed applications. In this study, we develop a system to monitor that mobile application permission at application update. This study is a service-based malware analysis. It will be based on the mobile security study.

Keywords: malware patterns, application permission, application analysis, security

Procedia PDF Downloads 524

Authors: Hugo Lefeuvre, Jerôme Donnard, Michael Descostes, Sophie Billon, Samuel Duval, Tugdual Oger, Herve Toubon, Paul Sardini

Abstract:

Spectroscopic autoradiography is a method of interest for geological sample analysis. Indeed, researchers may face different issues such as radioelement identification and quantification in the field of environmental studies. Imaging gaseous ionization detectors find their place in geosciences for conducting specific measurements of radioactivity to improve the monitoring of natural processes using naturally-occurring radioactive tracers, but also for the nuclear industry linked to the mining sector. In geological samples, the location and identification of the radioactive-bearing minerals at the thin-section scale remains a major challenge as the detection limit of the usual elementary microprobe techniques is far higher than the concentration of most of the natural radioactive decay products. The spatial distribution of each decay product in the case of uranium in a geomaterial is interesting for relating radionuclides concentration to the mineralogy. The present study aims to provide spectroscopic autoradiography analysis method for measuring the initial energy of alpha particles with a parallel ionization multiplier gaseous detector. The analysis method has been developed thanks to Geant4 modelling of the detector. The track of alpha particles recorded in the gas detector allow the simultaneous measurement of the initial point of emission and the reconstruction of the initial particle energy by a selection based on the linear energy distribution. This spectroscopic autoradiography method was successfully used to reproduce the alpha spectra from a 238U decay chain on a geological sample at the thin-section scale. The characteristics of this measurement are an energy spectrum resolution of 17.2% (FWHM) at 4647 keV and a spatial resolution of at least 50 µm. Even if the efficiency of energy spectrum reconstruction is low (4.4%) compared to the efficiency of a simple autoradiograph (50%), this novel measurement approach offers the opportunity to select areas on an autoradiograph to perform an energy spectrum analysis within that area. This opens up possibilities for the detailed analysis of heterogeneous geological samples containing natural alpha emitters such as uranium-238 and radium-226. This measurement will allow the study of the spatial distribution of uranium and its descendants in geo-materials by coupling scanning electron microscope characterizations. The direct application of this dual modality (energy-position) of analysis will be the subject of future developments. The measurement of the radioactive equilibrium state of heterogeneous geological structures, and the quantitative mapping of 226Ra radioactivity are now being actively studied.

Keywords: alpha spectroscopy, digital autoradiography, mining activities, natural decay products

Procedia PDF Downloads 151

Authors: Ying Bo Xie, Hisa Yuki Kurokawa

Abstract:

Due to the fast development, China's express delivery industry has involved in a dilemma that the service quality are keeping decreasing while the construction rate of delivery network cannot meet the customers’ demand. In order to get out of this dilemma and enjoy a succession development rate, it is necessary to understand the current situation of China's express delivery industry. Firstly, the evolution of China's express delivery industry was systematical presented. Secondly, according to the number of companies and the amount of parcels they has dealt each year, the merits and faults of tow kind of operating pattern was analyzed. Finally, based on the characteristics of these express companies, the problems of China's express delivery industry was divided into several types and the countermeasures were given out respectively.

Keywords: China, express delivery industry, status, problem

Procedia PDF Downloads 363

Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

Abstract:

Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

Procedia PDF Downloads 488

Authors: Mohamed Adel Sennouni, Jamal Zbitou, Benaissa Abboud, Abdelwahed Tribak, Hamid Bennis, Mohamed Latrach

Abstract:

A compact UWB planar antenna fed with a microstrip-line is proposed. The new design is composed of a rectangular patch with symmetric L-shaped slots and fed by 50 Ω microstrip transmission line and a reduced ground-plane which have a periodic slots with an overall size of 47 mm x 20 mm. It is intended to be used in wireless applications that cover the ultra-wideband (UWB) frequency band. A wider impedance bandwidth of around 116.5% (1.875

Keywords: UWB planar antenna, L-shaped slots, wireless applications, impedance band-width, radiation pattern, CST

Procedia PDF Downloads 487

Authors: Kunal Shah, Swati Patel

Abstract:

Many real world problems involve data which can be considered as multi-label data streams. Efficient methods exist for multi-label classification in non streaming scenarios. However, learning in evolving streaming scenarios is more challenging, as the learners must be able to adapt to change using limited time and memory. Classification is used to predict class of unseen instance as accurate as possible. Multi label classification is a variant of single label classification where set of labels associated with single instance. Multi label classification is used by modern applications, such as text classification, functional genomics, image classification, music categorization etc. This paper introduces the task of multi-label classification, methods for multi-label classification and evolution measure for multi-label classification. Also, comparative analysis of multi label classification methods on the basis of theoretical study, and then on the basis of simulation was done on various data sets.

Keywords: binary relevance, concept drift, data stream mining, MLSC, multiple window with buffer

Procedia PDF Downloads 584

Authors: Narin Ozturk, Xiao-Mei Li, Sylvie Giachetti, Francis Levi, Alper Okyar

Abstract:

P-glycoprotein (P-gp, MDR1, ABCB1) is a transmembrane protein acting as an ATP-dependent efflux pump and functions as a biological barrier by extruding drugs and xenobiotics out of cells in healthy tissues especially in intestines, liver and brain as well as in tumor cells. The circadian timing system controls a variety of biological functions in mammals including xenobiotic metabolism and detoxification, proliferation and cell cycle events, and may affect pharmacokinetics, toxicity and efficacy of drugs. Selective mTOR (mammalian target of rapamycin) inhibitor everolimus is an immunosuppressant and anticancer drug that is active against many cancers, and its pharmacokinetics depend on P-gp. The aim of this study was to investigate the dosing time-dependent toxicity of everolimus with respect to the intestinal P-gp expression rhythms in mdr1a::Luc mice using Real Time-Biolumicorder (RT-BIO) System. Mdr1a::Luc male mice were synchronized with 12 h of Light and 12 h of Dark (LD12:12, with Zeitgeber Time 0 – ZT0 – corresponding Light onset). After 1-week baseline recordings, everolimus (5 mg/kg/day x 14 days) was administered orally at ZT1-resting period- and ZT13-activity period- to mdr1a::Luc mice singly housed in an innovative monitoring device, Real Time-Biolumicorder units which let us monitor real-time and long-term gene expression in freely moving mice. D-luciferin (1.5 mg/mL) was dissolved in drinking water. Mouse intestinal mdr1a::Luc oscillation profile reflecting P-gp gene expression and locomotor activity pattern were recorded every minute with the photomultiplier tube and infrared sensor respectively. General behavior and clinical signs were monitored, and body weight was measured every day as an index of toxicity. Drug-induced body weight change was expressed relative to body weight on the initial treatment day. Statistical significance of differences between groups was validated with ANOVA. Circadian rhythms were validated with Cosinor Analysis. Everolimus toxicity changed as a function of drug timing, which was least following dosing at ZT13, near the onset of the activity span in male mice. Mean body weight loss was nearly twice as large in mice treated with 5 mg/kg everolimus at ZT1 as compared to ZT13 (8.9% vs. 5.4%; ANOVA, p < 0.001). Based on the body weight loss and clinical signs upon everolimus treatment, tolerability for the drug was best following dosing at ZT13. Both rest-activity and mdr1a::Luc expression displayed stable 24-h periodic rhythms before everolimus and in both vehicle-treated controls. Real-time bioluminescence pattern of mdr1a revealed a circadian rhythm with a 24-h period with an acrophase at ZT16 (Cosinor, p < 0.001). Mdr1a expression remained rhythmic in everolimus-treated mice, whereas down-regulation was observed in P-gp expression in 2 of 4 mice. The study identified the circadian pattern of intestinal P-gp expression with an unprecedented precision. The circadian timing depending on the P-gp expression rhythms may play a crucial role in the tolerability/toxicity of everolimus. The circadian changes in mdr1a genes deserve further studies regarding their relevance for in vitro and in vivo chronotolerance of mdr1a-transported anticancer drugs. Chronotherapy with P-gp-effluxed anticancer drugs could then be applied according to their rhythmic patterns in host and tumor to jointly maximize treatment efficacy and minimize toxicity.

Keywords: circadian rhythm, chronotoxicity, everolimus, mdr1a::Luc mice, p-glycoprotein

Procedia PDF Downloads 342

Authors: N. Khodarahmi, L. Ford

Abstract:

Decades of research on the impact of trauma in early childhood suggest severe risks to the mental health, emotional, social and physical development of a young child. Trauma-exposed students can pose a variety of different levels of challenges to schools and educators of young children and to date, few studies have addressed ECE teachers’ role in providing trauma support. The present study aims to contribute to this literature by exploring the beliefs of British Columbia’s (BC) early childhood education (ECE) teachers in their level of readiness and capability to work within a trauma-informed practice (TIP) framework to support their trauma-exposed students. Through a sequential, mix-methods approach, a self-report questionnaire and semi-structured interviews will be used to gauge BC ECE teachers’ knowledge of TIP, their preparedness, and their ability in using this framework to support their most vulnerable students. Teacher participants will be recruited through the ECEBC organization and various school districts in the Greater Vancouver Area. Questionnaire data will be primarily collected through an online survey tool whereas interviews will be taking place in-person and audio-recorded. Data analysis of survey responses will be largely descriptive, whereas interviews, once transcribed, will be employing thematic content analysis to generate themes from teacher responses. Ultimately, this study hopes to highlight the necessity of utilizing the TIP framework in BC ECE classrooms in order to support both trauma-exposed students and provide essential resources to compassionate educators of young children.

Keywords: early childhood education, early learning classrooms, refugee students, trauma-exposed students, trauma-informed practice

Procedia PDF Downloads 141

Authors: Kangana Sengar, Sanjay Deb, Ramesh Dawar

Abstract:

Introduction: Ki-67 can be a useful marker in determining proliferative activity in patients with multiple myeloma (MM). However, using Ki-67 alone results in the erroneous inclusion of non-myeloma cells leading to false high counts. We have used Dual IHC (immunohistochemistry) staining with Ki-67 and CD138 to enhance specificity in assessing proliferative activity of bone marrow plasma cells. Aims and objectives: To estimate the proportion of proliferating (Ki-67 expressing) plasma cells in patients with MM and correlation of Ki-67 with other known prognostic parameters. Materials and Methods: Fifty FFPE (formalin fixed paraffin embedded) blocks of trephine biopsies of cases diagnosed as MM from 2010 to 2015 are subjected to H & E staining and Dual IHC staining for CD 138 and Ki-67. H & E staining is done to evaluate various histological parameters like percentage of plasma cells, pattern of infiltration (nodular, interstitial, mixed and diffuse), routine parameters of marrow cellularity and hematopoiesis. Clinical data is collected from patient records from Medical Record Department. Each of CD138 expressing cells (cytoplasmic, red) are scored as proliferating plasma cells (containing a brown Ki¬67 nucleus) or non¬proliferating plasma cells (containing a blue, counter-stained, Ki-¬67 negative nucleus). Ki-67 is measured as percentage positivity with a maximum score of hundred percent and lowest of zero percent. The intensity of staining is not relevant. Results: Statistically significant correlation of Ki-67 in D-S Stage (Durie & Salmon Stage) I vs. III (p=0.026) and ISS (International Staging System) Stage I vs. III (p=0.019), β2m (p=0.029) and percentage of plasma cells (p < 0.001) is seen. No statistically significant correlation is seen between Ki-67 and hemoglobin, platelet count, total leukocyte count, total protein, albumin, S. calcium, S. creatinine, S. LDH, blood urea and pattern of infiltration. Conclusion: Ki-67 index correlated with other known prognostic parameters. However, it is not determined routinely in patients with MM due to little information available regarding its relevance and paucity of studies done to correlate with other known prognostic factors in MM patients. To the best of our knowledge, this is the first study in India using Dual IHC staining for Ki-67 and CD138 in MM patients. Routine determination of Ki-67 will help to identify patients who may benefit with more aggressive therapy. Recommendation: In this study follow up of patients is not included, and the sample size is small. Studying with larger sample size and long follow up is advocated to prognosticate Ki-67 as a marker of survival in patients with multiple myeloma.

Keywords: bone marrow, dual IHC, Ki-67, multiple myeloma

Procedia PDF Downloads 155

Authors: Josef Steinberger, Vanni Zavarella, Hristo Tanev

Abstract:

Natural disasters cause tens of thousands of victims and massive material damages. We refer to all those events caused by natural disasters, such as damage on people, infrastructure, vehicles, services and resource supply, as micro events. This paper addresses the problem of micro - event detection in online media sources. We present a natural language grammar learning algorithm and apply it to online news. The algorithm in question is based on distributional clustering and detection of word collocations. We also explore the extraction of micro-events from social media and describe a Twitter mining robot, who uses combinations of keywords to detect tweets which talk about effects of disasters.

Keywords: online news, natural language processing, machine learning, event extraction, crisis computing, disaster effects, Twitter

Procedia PDF Downloads 478

Authors: Burak Oksuzoglu, Savas Yildirim, Ferhat Kutlu

Abstract:

Opinion mining (OM) is one of the natural language processing (NLP) problems to determine the polarity of opinions, mostly represented on a positive-neutral-negative axis. The data for OM is usually collected from various social media platforms. In an era where social media has considerable control over companies’ futures, it’s worth understanding social media and taking actions accordingly. OM comes to the fore here as the scale of the discussion about companies increases, and it becomes unfeasible to gauge opinion on individual levels. Thus, the companies opt to automize this process by applying machine learning (ML) approaches to their data. For the last two decades, OM or sentiment analysis (SA) has been mainly performed by applying ML classification algorithms such as support vector machines (SVM) and Naïve Bayes to a bag of n-gram representations of textual data. With the advent of deep learning and its apparent success in NLP, traditional methods have become obsolete. Transfer learning paradigm that has been commonly used in computer vision (CV) problems started to shape NLP approaches and language models (LM) lately. This gave a sudden rise to the usage of the pretrained language model (PTM), which contains language representations that are obtained by training it on the large datasets using self-supervised learning objectives. The PTMs are further fine-tuned by a specialized downstream task dataset to produce efficient models for various NLP tasks such as OM, NER (Named-Entity Recognition), Question Answering (QA), and so forth. In this study, the traditional and modern NLP approaches have been evaluated for OM by using a sizable corpus belonging to a large private company containing about 76,000 comments in Turkish: SVM with a bag of n-grams, and two chosen pre-trained models, multilingual universal sentence encoder (MUSE) and bidirectional encoder representations from transformers (BERT). The MUSE model is a multilingual model that supports 16 languages, including Turkish, and it is based on convolutional neural networks. The BERT is a monolingual model in our case and transformers-based neural networks. It uses a masked language model and next sentence prediction tasks that allow the bidirectional training of the transformers. During the training phase of the architecture, pre-processing operations such as morphological parsing, stemming, and spelling correction was not used since the experiments showed that their contribution to the model performance was found insignificant even though Turkish is a highly agglutinative and inflective language. The results show that usage of deep learning methods with pre-trained models and fine-tuning achieve about 11% improvement over SVM for OM. The BERT model achieved around 94% prediction accuracy while the MUSE model achieved around 88% and SVM did around 83%. The MUSE multilingual model shows better results than SVM, but it still performs worse than the monolingual BERT model.

Keywords: BERT, MUSE, opinion mining, pretrained language model, SVM, Turkish

Procedia PDF Downloads 146

Authors: Shalini TV, Gangadharan GG, Sriranjini S Jaideep, ASN Seshasayee, Awadhesh Pandit

Abstract:

Introduction: Prakriti (body-mind constitution of an individual) is a conventional, customized and unique understanding of which is essential for the personalized medicine described in Ayurveda, Indian System of Medicine. Based on the Doshas( functional, bio humoral unit in the body), individuals are categorized into three major Prakriti- Vata, Pitta, and Kapha. The human gut microbiome hosts plenty of highly diverse and metabolically active microorganisms, mainly dominated by the bacteria, which are known to influence the physiology of an individual. Few researches have shown the correlation between the Prakriti and the biochemical parameters. In this study, an attempt was made to explore any correlation between the Prakriti (phenotype of an individual) with the Genetic makeup of the gut microbiome in healthy individuals. Materials and methods: 270 multi-ethnic, healthy volunteers of both sex with the age group between 18 to 40 years, with no history of antibiotics in the last 6 months were recruited into three groups of Vata, Pitta, and Kapha. The Prakriti of the individual was determined using Ayusoft, a software designed by CDAC, Pune, India. The volunteers were subjected to initial screening for the assessment of their height, weight, Body Mass Index, Vital signs and Blood investigations to ensure they are healthy. The stool and saliva samples of the recruited volunteers were collected as per the standard operating procedure developed, and the bacterial DNA was isolated using Qiagen kits. The extracted DNA was subjected to 16s rRNA sequencing using the Illumina kits. The sequencing libraries are targeting the variable V3 and V4 regions of the 16s rRNA gene. Paired sequencing was done on the MiSeq system and data were analyzed using the CLC Genomics workbench 11. Results: The 16s rRNA sequencing of the V3 and V4 regions showed a diverse pattern in both the oral and stool microbial DNA. The study did not reveal any specific pattern of bacterial flora amongst the Prakriti. All the p-values were more than the effective alpha values for all OTUs in both the buccal cavity and stool samples. Therefore, there was no observed significant enrichment of an OTU in the patient samples from either the buccal cavity or stool samples. Conclusion: In healthy volunteers of multi-ethnicity, due to the influence of the various factors, the correlation between the Prakriti and the gut microbiome was not seen.

Keywords: gut microbiome, ayurveda Prakriti, sequencing, multi-ethnic urban population

Procedia PDF Downloads 135

Authors: Hui Li, Xiongqi Pang

Abstract:

In recent years, tight oil has become a hot spot for unconventional oil and gas exploration and development in the world. Dongpu Depression is a typical hydrocarbon-rich basin in the southwest of Bohai Bay Basin, in which tight sandstone oil and gas have been discovered in deep reservoirs, most of which are buried more than 3500m. The distribution and development characteristics of deep tight sandstone reservoirs need to be studied. The main source rocks in study area are dark mudstone and shale of the middle and lower third sub-member of Shahejie Formation. Total Organic Carbon (TOC) content of source rock is between 0.08-11.54%, generally higher than 0.6% and the value of S1+S2 is between 0.04–72.93 mg/g, generally higher than 2 mg/g. It can be evaluated as middle to fine level overall. The kerogen type of organic matter is predominantly typeⅡ1 andⅡ2. Vitrinite reflectance (Ro) is mostly greater than 0.6% indicating that the source rock entered the hydrocarbon generation threshold. The physical property of reservoir was poor, the most reservoir has a porosity lower than 12% and a permeability of less than 1×10⁻³μm. The rocks in this area showed great heterogeneity, some areas developed desserts with high porosity and permeability. According to SEM, thin section image, inclusion test and so on, the reservoir was affected by compaction and cementation during early diagenesis stage (44-31Ma). The diagenesis caused the tight reservoir in Huzhuangji, Pucheng, Weicheng Area while the porosity in Machang, Qiaokou, Wenliu Area was still over 12%. In the process of middle diagenesis phase stage A (31-17Ma), the reservoir porosity in Machang, Pucheng, Huzhuangji Area increased due to dissolution; after that the oil generation window of source rock was achieved for the first phase hydrocarbon charging (31-23Ma), formed the conventional oil deposition in Machang, Qiaokou, Wenliu, Huzhuangji Area and unconventional tight reservoir in Pucheng, Weicheng Area. Then came to stage B of middle diagenesis phase (17-7Ma), in this stage, the porosity of reservoir continued to decrease after the dissolution and led to a situation that the reservoirs were generally compacted. And since then, the second hydrocarbon filling has been processing since 7Ma. Most of the pools charged and formed in this procedure are tight sandstone oil reservoir. In conclusion, tight sandstone oil was formed in two patterns in Dongpu Depression, which could be concluded as ‘density fist then accumulation’ pattern and ‘accumulation fist next density’ pattern.

Keywords: accumulation process, diagenesis, dongpu depression, tight sandstone oil

Procedia PDF Downloads 116

Authors: P. Halder, A. Zaman

Abstract:

It is estimated that heart disease accounts for one in ten deaths worldwide. United States deaths due to heart disease are among the leading causes of death according to the World Health Organization. Cardiovascular diseases (CVDs) account for one in four U.S. deaths, according to the Centers for Disease Control and Prevention (CDC). According to statistics, women are more likely than men to die from heart disease as a result of strokes. A 50% increase in men's mortality was reported by the World Health Organization in 2009. The consequences of cardiovascular disease are severe. The causes of heart disease include diabetes, high blood pressure, high cholesterol, abnormal pulse rates, etc. Machine learning (ML) can be used to make predictions and decisions in the healthcare industry. Thus, scientists have turned to modern technologies like Machine Learning and Data Mining to predict diseases. The disease prediction is based on four algorithms. Compared to other boosts, the Ada boost is much more accurate.

Keywords: heart disease, cardiovascular disease, coronary artery disease, feature selection, random forest, AdaBoost, SVM, decision tree

Procedia PDF Downloads 153

Authors: Daniela Panico

Abstract:

Framed by language socialization and family language policy theories, the present study explores the ways the language choice patterns of bilingual siblings contribute to the shaping of the language environment and the language practices of Italian/English families residing in Sydney. The main source of data is video recordings of naturally occurring parent-children and child-to-child interactions during everyday routines (i.e., family mealtimes and siblings playtime) in the home environment. Recurrent interactional practices are analyzed in detail through a conversational analytical approach. This presentation focuses on the interactional trajectories developing during the negotiation of language choices between all family members and between siblings in face-to-face interactions. Fine-grained analysis is performed on language negotiation sequences of multiparty bilingual conversations in order to uncover the sequential patterns through which a) the children respond to the parental strategies aiming to minority language maintenance, and b) the siblings influence each other’s language use and choice (e.g., older siblings positioning themselves as language teachers and language brokers, younger siblings accepting the role of apprentices). The findings show that, along with the parents, children are active socializing agents in the family and, with their linguistic behavior, they contribute to the establishment of a bilingual or a monolingual context in the home. Moreover, by orienting themselves towards the use of one or the other language in family talk, bilingual siblings are a major internal micro force in the language ecology of a bilingual family and can strongly support language maintenance or language shift processes in such domain. Overall, the study provides insights into the dynamic ways in which family language policy is interactionally negotiated and instantiated in bilingual homes as well as the challenges of intergenerational language transmission.

Keywords: bilingual siblings, family interactions, family language policy, language maintenance

Procedia PDF Downloads 191

Authors: Amna Javed, Hisashi Masuda, Youji Kohda

Abstract:

This study examines the value analysis in Islamic and conventional banking services in Pakistan. Many scholars have focused on co-creation of values in services but mainly economic values not non-economic. As Islamic banking is based on Islamic principles that are more concerned with non-economic values (well-being, partnership, fairness, trust worthy, and justice) than economic values as money in terms of interest. This study is important to know the providers point of view about the co-created values, because, it may be more sustainable and appropriate for today’s unpredictable socioeconomic environment. Data were collected from 4 banks (2 Islamic and 2 conventional banks). Text mining technique is applied for data analysis, and values with 100% occurrences in Islamic banking are chosen. The results reflect that Islamic banking is more centric towards non-economic values than economic values and it promotes team work and partnership concept by applying Islamic spirit and trust worthiness concept.

Keywords: economic values, Islamic banking, non-economic values, value system

Procedia PDF Downloads 463

Authors: Malak Alqaydhi

Abstract:

A problem in the Saudi Arabia education system is that there is a lack of curriculum- based Social, emotional learning (SEL) teaching practices with the pedagogical concept of SEL yet to be practiced in the Kingdom of Saudi Arabia (KSA). Furthermore, voices of teachers and parents have not been captured regarding the use of SEL, particularly in preschools. The importance of this research is to help determine, with the input of teachers and mothers of preschoolers, the efficacy of a culturally adapted SEL program. The purpose of this research is to determine the most appropriate SEL intervention method to appropriately apply in the cultural context of the Saudi preschool classroom setting. The study will use a mixed method exploratory sequential research design, applying qualitative and quantitative approaches including semi-structured interviews with teachers and parents of preschoolers and an experimental research approach. The research will proceed in four phases beginning with a series of interviews with Saudi preschool teachers and mothers, whose voices and perceptions will help guide the second phase of selection and adaptation of a suitable SEL preschool program. The third phase will be the implementation of the intervention by the researcher in the preschool classroom environment, which will be facilitated by the researcher’s cultural proficiency and practical experience in Saudi Arabia. The fourth and final phase will be an evaluation to assess the effectiveness of the trialled SEL among the preschool student participants. The significance of this research stems from its contribution to knowledge about SEL in culturally appropriate Saudi preschools and the opportunity to support initiatives for Saudi early childhood educators to consider implementing SEL programs. The findings from the study may be useful to inform the Saudi Ministry of Education and its curriculum designers about SEL programs, which could be beneficial to trial more widely in the Saudi preschool curriculum.

Keywords: social emotional learning, preschool children, saudi Arabia, child behavior

Procedia PDF Downloads 157

Authors: Nurhafizah Md. Disa, Nurhayati Binti Abdullah, Muhammad Rabie Bin Omar

Abstract:

This research intends to identify the existing knowledge gap because of the lack of substantial studies to fabricate and characterize bio-graphene created from Oil Palm Shell (OPS) through the means of pre-treatment and slow pyrolysis. By fabricating bio-graphene through OPS, a novel material can be found to procure and used for graphene-based research. The characterization of produced bio-graphene is intended to possess a unique hexagonal graphene pattern and graphene properties in comparison to other previously fabricated graphene. The OPS will be fabricated by pre-treatment of zinc chloride (ZnCl₂) and iron (III) chloride (FeCl3), which then induced the bio-graphene thermally by slow pyrolysis. The pyrolizer's final temperature and resident time will be set at 550 °C, 5/min, and 1 hour respectively. Finally, the charred product will be washed with hydrochloric acid (HCL) to remove metal residue. The obtained bio-graphene will undergo different analyses to investigate the physicochemical properties of the two-dimensional layer of carbon atoms with sp2 hybridization hexagonal lattice structure. The analysis that will be taking place is Raman Spectroscopy (RAMAN), UV-visible spectroscopy (UV-VIS), Transmission Electron Microscopy (TEM), Scanning Electron Microscopy (SEM), and X-Ray Diffraction (XRD). In retrospect, RAMAN is used to analyze three key peaks found in graphene, namely D, G, and 2D peaks, which will evaluate the quality of the bio-graphene structure and the number of layers generated. To compare and strengthen graphene layer resolves, UV-VIS may be used to establish similar results of graphene layer from last layer analysis and also characterize the types of graphene procured. A clear physical image of graphene can be obtained by analyzation of TEM in order to study structural quality and layers condition and SEM in order to study the surface quality and repeating porosity pattern. Lastly, establishing the crystallinity of the produced bio-graphene, simultaneously as an oxygen contamination factor and thus pristineness of the graphene can be done by XRD. In the conclusion of this paper, this study is able to obtain bio-graphene through OPS as a novel material in pre-treatment by chloride ZnCl₂ and FeCl3 and slow pyrolization to provide a characterization analysis related to bio-graphene that will be beneficial for future graphene-related applications. The characterization should yield similar findings to previous papers as to confirm graphene quality.

Keywords: oil palm shell, bio-graphene, pre-treatment, slow pyrolysis

Procedia PDF Downloads 84

Authors: I. Zahraoui, J. Terhzaz, A. Errkik, El. H. Abdelmounim, A. Tajmouati, L. Abdellaoui, N. Ababssi, M. Latrach

Abstract:

This paper presents a novel design of a microstrip fractal antenna based on the use of Sierpinski triangle shape, it’s designed and simulated by using FR4 substrate in the operating frequency bands (GPS, WiMAX), the design is a fractal antenna with a modified ground structure. The proposed antenna is simulated and validated by using CST Microwave Studio Software, the simulated results presents good performances in term of radiation pattern and matching input impedance.

Keywords: dual-band antenna, fractal antenna, GPS band, modified ground structure, sierpinski triangle, WiMAX band

Procedia PDF Downloads 445

Authors: Huda Al Shuaily, Karen Renaud

Abstract:

Databases comprise the foundation of most software systems. System developers inevitably write code to query these databases. The de facto language for querying is SQL and this, consequently, is the default language taught by higher education institutions. There is evidence that learners find it hard to master SQL, harder than mastering other programming languages such as Java. Educators do not agree about explanations for this seeming anomaly. Further investigation may well reveal the reasons. In this paper, we report on our investigations into how novices learn SQL, the actual problems they experience when writing SQL, as well as the differences between expert and novice SQL query writers. We conclude by presenting a model of SQL learning that should inform the instructional material design process better to support the SQL learning process.

Keywords: pattern, SQL, learning, model

Procedia PDF Downloads 254

Authors: Abejide Dorcas Ropo, Falusi Olamide Ahmed, Daudu Oladipupo Abdulazeez Yusuf, Muhammad Liman Muhammad, Gado Aishatu Adamu

Abstract:

Bambara groundnut is an indigenous African legume with great potential to tackle the problem of food insecurity in Nigeria. A germplasm collection mission was carried out in collaboration with the Agricultural Developments Project (ADP) Extension officers of Nigeria between October and December 2014. Bambara groundnut seeds were collected from farmers in different States in Nigeria, such as Kaduna, Niger, Kogi, Benue, Plateau, Adamawa, Nasarawa, Jigawa, Enugu, and Federal Capital Territoy (FCT) Abuja. Some seeds were also collected from National Centre for Genetic Resources and Biotechnology (NACGRAB). The seeds were phenotyped using the descriptor list of Vigna subterranea produced by the International Plant Genetic Resource Institute. A total of 45 original seed lots were collected, which comprised of mixed seeds having different seed coat colours (15) and pure seeded accessions having the same seed coat and eye colour (30). After sorting, a total of 83 accessions were derived from the 45 original seed lots collected, and a total of 24 distinct seed morphotypes with varying seed coat colours and eye colours were identified from the collections. They include cream ( cream ash eye, cream plain eye, and cream black eye), cream purplish spots, cream brown spots/stripe, cream black stripe, cream dark brown patches, cream light grey spots, cream black patches, black, red, light red, dark red, brownish red, brown speckled with black, red speckled with black, brown, brown with brown pattern below hilum, brown with black pattern below hilum, cream black, grey brown, grey black and variegated red. The highest number of accessions were collected from NACGRAB (11), followed by Niger State (10), and the lowest from Benue, Jigawa, and Adamawa States (2). Niger State also had the highest number of mixed seeds. The different seed phenotypes observed in the study are important for the field production of true-to-type lines and can be exploited for the genetic improvement of the Bambara groundnut.

Keywords: Bambara groundnut, characterization, collection, germplasm, phenotypic

Procedia PDF Downloads 142

Authors: Sherif M. A. S. Keshk, Hisham S. M. Abd-Rabboh, Mohamed S. Hamdy, Ibrahim H. A. Badr

Abstract:

Microwave radiation was applied to synthesize nanoparticles of nickel oxide supported on pretreated cellulose with metal acetate in the presence of NaOH. Optimization, in terms of irradiation time and metal concentration, was investigated. FT-IR spectrum of cellulose/NiO spectrum shows a band at 445 cm^-1 that is related to the Ni–O stretching vibration of NiO6 octahedral in the cubic NiO structure. cellulose/NiO showed similar XRD pattern of cellulose I and exhibited sharpened reflection peak at 2q = 29.8°, corresponding to (111) plane of NiO, with two weak broad peaks at 48.5°, and 49.2°, representing (222) planes of NiO. XPS spectrum of mercerized cellulose/NiO composite showed did not show any peaks corresponding to Na ion.

Keywords: cellulose, mercerized cellulose, cellulose/zinc and nickeloxides composite, FTIR, XRD, XPS, SEM, Raman spectrum

Procedia PDF Downloads 443

Authors: Anam Alam, Rahim Jamaluddin Kanji

Abstract:

With the rapid growth of event in everywhere, event extraction has now become an important matter to retrieve the information from the unstructured data. One of the challenging problems is to extract the event from it. An event is an observable occurrence of interaction among entities. The paper investigates the effectiveness of event extraction capabilities of three software tools that are Wandora, Nitro and SPSS. We performed standard text mining techniques of these tools on the data sets of (i) Afghan War Diaries (AWD collection), (ii) MUC4 and (iii) WebKB. Information retrieval measures such as precision and recall which are computed under extensive set of experiments for Event Extraction. The experimental study analyzes the difference between events extracted by the software and human. This approach helps to construct an algorithm that will be applied for different machine learning methods.

Keywords: event extraction, Wandora, nitro, SPSS, event analysis, extraction method, AFG, Afghan War Diaries, MUC4, 4 universities, dataset, algorithm, precision, recall, evaluation

Procedia PDF Downloads 596

Authors: Ben Tappin, Ryan McKay

Abstract:

The political left and right appear to disagree not only over questions of value but, also, over questions of fact—over what is true “out there” in society and the world. Alarmingly, a large body of survey data collected during the past decade suggests that this disagreement tends to be greatest among the most educated and most cognitively sophisticated opposing partisans. In other words, the data show that these individuals display the widest political polarization in their reported factual beliefs. Explanations of this polarization pattern draw heavily on cultural and political factors; yet, the large majority of the evidence originates from one cultural and political context—the United States, a country with a rather unique cultural and political history. One consequence is that widening political polarization conditional on education and cognitive sophistication may be due to idiosyncratic cultural, political or historical factors endogenous to US society—rather than a more general, international phenomenon. We examined widening political polarization conditional on education across Europe, over a topic that is culturally and politically contested; immigration. To do so, we analyzed data from the European Social Survey, a premier survey of countries in and around the European area conducted biennially since 2002. Our main results are threefold. First, we see widening political polarization conditional on education over beliefs about the economic impact of immigration. The foremost countries showing this pattern are the most influential in Europe: Germany and France. However, we also see heterogeneity across countries, with some—such as Belgium—showing no evidence of such polarization. Second, we find that widening political polarization conditional on education is a product of sorting. That is, highly educated partisans exhibit stronger within-group consensus in their beliefs about immigration—the data do not support the view that the more educated partisans are more polarized simply because the less educated fail to adopt a position on the question. Third, and finally, we find some evidence that shocks to the political climate of countries in the European area—for example, the “refugee crisis” of summer 2015—were associated with a subsequent increase in political polarization over immigration conditional on education. The largest increase was observed in Germany, which was at the centre of the so-called refugee crisis in 2015. These results reveal numerous insights: they show that widening political polarization conditional on education is not restricted to the US or native English-speaking culture; that such polarization emerges in the domain of immigration; that it is a product of within-group consensus among the more educated; and, finally, that exogenous shocks to the political climate may be associated with subsequent increases in political polarization conditional on education.

Keywords: beliefs, Europe, immigration, political polarization

Procedia PDF Downloads 147

Authors: Akbar Salimi, Mehdi Moghimi

Abstract:

Goal: The human resource empowerment is a new strategy in achieving a competitive advantage. The aim of the research is to understand crime management by the police by using this strategy. Method: The research is applied in terms of goal and it is a survey type research. The sample intended include all the police officers of a police station for as many as 52 people. The data were collected by a researcher made four choice questionnaire after the validity and reliability were confirmed. Findings: By regarding the Melhem pattern as the framework, four dimensions of empowerment were identified and the triangle of crime was explained and then four hypotheses proportionate to it were formulated. Results: Given the fact that the sample was all counted, all the four hypotheses were supported by using the average data received and by regarding the %50 as the criterion.

Keywords: management, empowerment, employees, police

Procedia PDF Downloads 373

Authors: Kenny Raharjo, Ramon Lawrence

Abstract:

Game designers have the challenging task of building games that engage players to spend their time and money on the game. There are an infinite number of game variations and design choices, and it is hard to systematically determine game design choices that will have positive experiences for players. In this work, we demonstrate how multi-arm bandits can be used to automatically explore game design variations to achieve improved player metrics. The advantage of multi-arm bandits is that they allow for continuous experimentation and variation, intrinsically converge to the best solution, and require no special infrastructure to use beyond allowing minor game variations to be deployed to users for evaluation. A user study confirms that applying multi-arm bandits was successful in determining the preferred game variation with highest play time metrics and can be a useful technique in a game designer's toolkit.

Keywords: game design, multi-arm bandit, design exploration and data mining, player metric optimization and analytics

Procedia PDF Downloads 510

Authors: Anuta Mukherjee, Saswati Mukherjee

Abstract:

Data is growing everyday. Social networking sites such as Twitter are becoming an integral part of our daily lives, contributing a large increase in the growth of data. It is a rich source especially for sentiment detection or mining since people often express honest opinion through tweets. However, although sentiment analysis is a well-researched topic in text, this analysis using Twitter data poses additional challenges since these are unstructured data with abbreviations and without a strict grammatical correctness. We have employed collision theory to achieve sentiment analysis in Twitter data. We have also incorporated discourse analysis in the collision theory based model to detect accurate sentiment from tweets. We have also used the retweet field to assign weights to certain tweets and obtained the overall weightage of a topic provided in the form of a query. Hadoop has been exploited for speed. Our experiments show effective results.

Keywords: sentiment analysis, twitter, collision theory, discourse analysis

Procedia PDF Downloads 535