Search results for: content accuracy

Authors: Rabia Bashir, Sajjad Akbar

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There is an inevitable demand of web mining due to rapid increase of huge information on the Internet, but the striking variety of web structures has made required content retrieval a difficult task. To counter this issue, Web Content Mining (WCM) emerges as a potential candidate which extracts and integrates suitable resources of data to users. In past few years, research has been done on several extraction techniques for WCM i.e. agent-based, template-based, assumption-based, statistic-based, wrapper-based and machine learning. However, it is still unclear that either these approaches are efficiently tackling the significant challenges of WCM or not. To answer this question, this paper identifies these challenges such as language independency, structure flexibility, performance, automation, dynamicity, redundancy handling, intelligence, relevant content retrieval, and privacy. Further, mapping of these challenges is done with existing extraction mechanisms which helps to adopt the most suitable WCM approach, given some conditions and characteristics at hand.

Keywords: content mining challenges, web content mining, web content extraction approaches, web information retrieval

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Authors: Zhiwei Yan, Jong-Hyouk Lee, Yong-Jin Park, Xiaodong Lee

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In this paper, we analyze NEtwork MObility (NEMO) supporting problems in Content-Centric Networking (CCN), and propose the CCN-NEMO which can well support the deployment of the content-centric paradigm in large-scale mobile Internet. The CCN-NEMO extends the signaling message of the basic CCN protocol, to support the mobility discovery and fast trigger of Interest re-issuing during the network mobility. Besides, the Mobile Router (MR) is extended to optimize the content searching and relaying in the local subnet. These features can be employed by the nested NEMO to maximize the advantages of content retrieving with CCN. Based on the analysis, we compare the performance on handover latency between the basic CCN and our proposed CCN-NEMO. The results show that our scheme can facilitate the content-retrieving in the NEMO scenario with improved performance.

Keywords: NEMO, CCN, mobility, handover latency

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Authors: Xochilt Ramirez-Garcia, Mario Garcia-Valdez

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Contextual recommendations are implemented in Recommender Systems to improve user satisfaction, recommender system makes accurate and suitable recommendations for a particular situation reaching personalized recommendations. The context provides information relevant to the Recommender System and is used as a filter for selection of relevant items for the user. This paper presents a Context-aware Recommender System, which uses techniques based on Collaborative Filtering and Content-Based, as well as fuzzy rules, to recommend items inside the context. The dataset used to test the system is Trip Advisor. The accuracy in the recommendations was evaluated with the Mean Absolute Error.

Keywords: algorithms, collaborative filtering, intelligent systems, fuzzy logic, recommender systems

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Authors: Alise Senberga, Laila Dubova, Liene Strauta, Ina Alsina, Ieva Erdberga

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Legume symbiotic relationship with nitrogen fixating bacteria Rhizobim leguminosarum is an important factor used to improve the productivity of legumes, due to the fact that rhizobia can supply plant with the necessary amount of nitrogen. R. leguminosarum strains have shown different activity in fixing nitrogen. Depending on the chosen R. leguminosarum strain, host plant biochemical content can be altered. In this study we focused particularly on the changes in protein content in beans (using two different varieties) and peas (five different varieties) due to the use of several different R. leguminosarum strains (four strains for both beans and peas). Overall, the protein content increase was observed after seed inoculation with R. leguminosarum. Strain and plant cultivar interaction specification was observed. The effect of R. leguminosarum inoculation on the content of protein was dependent on the R. leguminosarum strain used. Plant cultivar also appeared to have a decisive role in protein content formation with the help of R. leguminosaru.

Keywords: legumes, protein content, rhizobia strains, soil

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Authors: Oksana Razina, Shakeel Ahmad, Jessie Qun Ren, Olufemi Isiaq

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The modern life of businesses is categorically reliant on their established position online, where digital (and particularly website) content plays a significant role as the first point of information. Digital content, therefore, becomes essential – from making the first impression to the building and development of client relationships. Despite a number of valuable papers suggesting a strategic approach when dealing with digital data, other sources often do not view or accept the approach to digital content as a holistic or continuous process. Associations are frequently made with merely a one-off marketing campaign or similar. The challenge is to establish an agreed definition for the notion of Digital Content Strategy, which currently does not exist, as DCS is viewed from an excessive number of different angles. A strategic approach to content, nonetheless, is required, both practically and contextually. The researchers, therefore, aimed at attempting to identify the key content components comprising a digital content strategy to ensure all the aspects were covered and strategically applied – from the company’s understanding of the content value to the ability to display flexibility of content and advances in technology. This conceptual project evaluated existing literature on the topic of Digital Content Strategy (DCS) and related aspects, using the PRISMA Systematic Review Method, Document Analysis, Inclusion and Exclusion Criteria, Scoping Review, Snow-Balling Technique and Thematic Analysis. The data was collected from academic and statistical sources, government and relevant trade publications. Based on the suggestions from academics and trading sources related to the issues discussed, the researchers revealed the key actions for content creation and attempted to define the notion of DCS. The major finding of the study presented Key Content Components of Digital Content Strategy and can be considered for implementation in a business retail setting.

Keywords: digital content strategy, key content components, websites, digital marketing strategy

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Authors: Hooriya Sadr Dadras, Shiva Seyed Erfani

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Speaking skills merit meticulous attention both on the side of the learners and the teachers. In particular, accuracy is a critical component to guarantee the messages to be conveyed through conversation because a wrongful change may adversely alter the content and purpose of the talk. Different types of tasks have served teachers to meet numerous educational objectives. Besides, negotiation of meaning and the use of different strategies have been areas of concern in socio-cultural theories of SLA. Negotiation of meaning is among the conversational processes which have a crucial role in facilitating the understanding and expression of meaning in a given second language. Conversational strategies are used during interaction when there is a breakdown in communication that leads to the interlocutor attempting to remedy the gap through talk. Therefore, this study was an attempt to investigate if there was any significant difference between the effect of reasoning gap tasks and information gap tasks on the frequency of conversational strategies used in negotiation of meaning in classrooms on one hand, and on the accuracy in speaking of Iranian intermediate EFL learners on the other. After a pilot study to check the practicality of the treatments, at the outset of the main study, the Preliminary English Test was administered to ensure the homogeneity of 87 out of 107 participants who attended the intact classes of a 15 session term in one control and two experimental groups. Also, speaking sections of PET were used as pretest and posttest to examine their speaking accuracy. The tests were recorded and transcribed to estimate the percentage of the number of the clauses with no grammatical errors in the total produced clauses to measure the speaking accuracy. In all groups, the grammatical points of accuracy were instructed and the use of conversational strategies was practiced. Then, different kinds of reasoning gap tasks (matchmaking, deciding on the course of action, and working out a time table) and information gap tasks (restoring an incomplete chart, spot the differences, arranging sentences into stories, and guessing game) were manipulated in experimental groups during treatment sessions, and the students were required to practice conversational strategies when doing speaking tasks. The conversations throughout the terms were recorded and transcribed to count the frequency of the conversational strategies used in all groups. The results of statistical analysis demonstrated that applying both the reasoning gap tasks and information gap tasks significantly affected the frequency of conversational strategies through negotiation. In the face of the improvements, the reasoning gap tasks had a more significant impact on encouraging the negotiation of meaning and increasing the number of conversational frequencies every session. The findings also indicated both task types could help learners significantly improve their speaking accuracy. Here, applying the reasoning gap tasks was more effective than the information gap tasks in improving the level of learners’ speaking accuracy.

Keywords: accuracy in speaking, conversational strategies, information gap tasks, reasoning gap tasks

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Authors: Norhanim Nordin, Rosnah Shamsudin, Azrina Azlan, Mohammad Effendy Ya’acob

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An environmental friendly approach for disposal of voluminous durian husk waste could be implemented by substituting them into various valuable commodities, such as healthcare and biofuel products. Thus, the study of composition value in each segment of durian husk was very crucial to determine the suitable proportions of nutrients that need to be added and mixed in the product. A total of 12 ‘Durian Kampung’ fruits from Sg Ruan, Pahang were selected and each fruit husk was divided into four segments and labelled as P-L (thin neck area of white inner husk), P-B (thick bottom area of white inner husk), H (green and thorny outer husk) and W (whole combination of P-B and H). Four experiments have been carried out to determine the dry matter, moisture, ash and crude fibre content. The results show that the H segment has the highest dry matter content (30.47%), while the P-B segment has the highest percentage in moisture (81.83%) and ash (6.95%) content. It was calculated that the ash content of the P-B segment has a higher rate of moisture level which causes the ash content to increase about 2.89% from the P-L segment. These data have proven that each segment of durian husk has a significant difference in terms of composition value, which might be useful information to fully utilize every part of the durian husk in the future.

Keywords: durian husk, crude fibre content, dry matter content, moisture content

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Authors: A. K. M. Kamrul Islam, Abdelhamid Bouchachia, Suang Cang, Hongnian Yu

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Forecasting model has a great impact in terms of prediction and continues to do so into the future. Although many forecasting models have been studied in recent years, most researchers focus on different forecasting methods based on fuzzy time series to solve forecasting problems. The forecasted models accuracy fully depends on the two terms that are the length of the interval in the universe of discourse and the content of the forecast rules. Moreover, a hybrid forecasting method can be an effective and efficient way to improve forecasts rather than an individual forecasting model. There are different hybrids forecasting models which combined fuzzy time series with evolutionary algorithms, but the performances are not quite satisfactory. In this paper, we proposed a hybrid forecasting model which deals with the first order as well as high order fuzzy time series and particle swarm optimization to improve the forecasted accuracy. The proposed method used the historical enrollments of the University of Alabama as dataset in the forecasting process. Firstly, we considered an automatic clustering algorithm to calculate the appropriate interval for the historical enrollments. Then particle swarm optimization and fuzzy time series are combined that shows better forecasting accuracy than other existing forecasting models.

Keywords: fuzzy time series (fts), particle swarm optimization, clustering algorithm, hybrid forecasting model

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Authors: Mourad Ben Bennani

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Views of language and language learning have undergone a tremendous change over the last decades. Language is no longer seen as a set of structured rules. It is rather viewed as a tool of interaction and communication. This shift in views has resulted in change in viewing language learning, which gave birth to various approaches and methodologies of language teaching. Two of these approaches are content-based instruction and content and language integrated learning (CLIL). These are similar approaches which integrate content and foreign/second language learning through various methodologies and models as a result of different implementations around the world. This presentation deals with sociocultural view of CBI and CLIL. It also defines language and content as vital components of CBI and CLIL. Next it reviews the origins of CBI and the continuum perspectives and CLIL definitions and models featured in the literature. Finally it summarizes current aspects around research in program evaluation with a focus on the benefits and challenges of these innovative approaches for second language teaching.

Keywords: CBI, CLIL, CBI continuum, CLIL models

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Authors: Aleksandrs Kovalcuks

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Egg yolk oil is a natural source of bioactive compounds such as unsaturated fatty acids, oil soluble vitamins, pigments and others. Bioactive compound content in egg yolk oil depends from its content in eggs, from which oil was extracted. Many studies show that bioactive compound content in egg is correlated to the content of these compounds in hen feed, but there is also an opinion that hen housing systems also have influence on egg chemical content. The aim of this study was to determine which factor, laying hen housing system or hen diet, has a primary influence on bioactive compound content in egg yolk oil. The egg yolk oil was extracted from eggs obtained from 4 different hen housing systems: cage, barn and two groups of free range. All hens were fed with commercially produced compound feed except one group of free range hens which get free diet – pastured hens. Extracted egg yolk oils were analyzed for fatty acids, oil soluble vitamins and β-carotene content. α-tocopherol, ergocalcipherol and polyunsaturated fatty acid content in egg yolk oil was higher from eggs obtained from all housing systems where hens were fed with commercial compound feed. β-carotene and retinol content in egg yolk oils from free range free diet eggs was significantly (p>0.05) higher that from other eggs because hens have access to green forage. Hen physical activity in free range housing systems decreases content of some bioactive compound in egg yolk oil.

Keywords: egg yolk oil, vitamins, caged eggs, free range

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Authors: Bilal Bhat, M. Masroor A. Khan, Moin Uddin, M. Naeem

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Aromatic herb, peppermint (Mentha piperita L.), is a natural hybrid (M. aquatica × M. spicata) with immense therapeutic uses, apart from other potential uses. Peppermint oil is one of the most popular and widely used essential oil (EO), because of its main components menthol and menthone. In view of enhancing growth, yield and quality of this medicinally important herb, a pot experiment was conducted in the net-house of the department. The experiment was aimed at studying the effect of graded levels of N, P, and K on growth, biochemical characteristics, and content and composition of EO in Mentha piperita L. Six NPK treatments (viz. N0P0K0, N20P20K20, N40P40K40, N20+20 P20+20 K20+20, N60P60K60, and N30+30 P30+30 K30+30) were tested. The plants were harvested 150 days after transplanting. The crop performance was assessed in terms of growth attributes, physiological activities, herbage yield and content as well as yield of active constituents of Mentha piperita L. Biochemical parameters were analyzed spectrophotometrically. The EO was extracted using Clevenger’s apparatus and the active constituents of the oil were determined using Gas Chromatography. Split-dose application of N, P and K (N30+30 P30+30 K30+30) ameliorated most of the parameters significantly including, fresh and dry weight of plant, NPK content, chlorophyll and carotenoids content, and the activities of carbonic anhydrase and nitrate reductase in the leaves. It also enhanced the EO content (44.0%), EO yield (91.0%), menthol content (14.1%), menthone content (34.0%), menthyl acetate content (16.9%) and 1, 8-cineole content (43.7%) but decreased the pulegone content (36.8%). Conclusively, the fertilization proved useful in enhancing the EO content, yield and other EO components of the plant. Thus, the yield and quality of EO of peppermint may be improved by this agricultural strategy.

Keywords: mentha piperita, menthol, menthone, EO

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Authors: Vincent Liu

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Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

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Authors: Jason Chen, Jennifer Chen, Shiyu Li

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We examine whether managerial ability (MA), the passing of Sarbanes-Oxley in 2002 (SOX), and corporate operational complexity affect the accuracy of environmental capital expenditure projections of the environmentally sensitive industries (ESI). Prior studies found that firms in the ESI manipulated their projected environmental capital expenditures as a tool to achieve corporate legitimation and suggested that human factors must be examined to determine whether they are part of the determinants. We use MA to proxy for the latent human factors to examine whether MA affects the accuracy of financial disclosures in the ESI. To expand Chen and Chen (2020), we further investigate whether (1) SOX and (2) firms with complex operations and financial reporting in conjunction with MA affect firms’ projection accuracy. We find, overall, that MA is positively correlated with firm’s projection accuracy in the annual 10-Ks. Furthermore, results suggest that SOX has a positive, yet temporary, effect on MA, and that leads to better accuracy. Finally, MA matters for firms with more complex operations and financial reporting to make less projection errors than their less-complex counterparts. These results suggest that MA is a determinant that affects the accuracy of environmental capital expenditure projections for the firms in the ESI.

Keywords: managerial ability, environmentally sensitive industries, sox, corporate operational complexity

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Authors: Syed Umair Aziz, Muhammad Faheem, Sameer Hussain, Faraz Idris

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Content centric network is the network based on the mechanism of sending and receiving the data based on the interest and data request to the specified node (which has cached data). In this network, the security is bind with the content not with the host hence making it host independent and secure. In this network security is applied by taking content’s MAC (message authentication code) and encrypting it with the public key of the receiver. On the receiver end, the message is first verified and after verification message is saved and decrypted using the receiver's private key.

Keywords: content centric network, client-server, host security threats, message authentication code, named data network, network caching, peer-to-peer

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Authors: Gyoutae Park, Seungho Han, Byungduk Kim, Youngdo Jo, Yongsop Shim, Yeonjae Lee, Sangguk Ahn, Hiesik Kim, Jungil Park

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In this paper, we presented not only development technology of an explosion proof type and portable combustible gas leak detector but also algorithm to improve accuracy for measuring gas concentrations. The presented techniques are to apply the flame-proof enclosure and intrinsic safe explosion proof to an infrared gas leak detector at first in Korea and to improve accuracy using linearization recursion equation and Lagrange interpolation polynomial. Together, we tested sensor characteristics and calibrated suitable input gases and output voltages. Then, we advanced the performances of combustible gaseous detectors through reflecting demands of gas safety management fields. To check performances of two company's detectors, we achieved the measurement tests with eight standard gases made by Korea Gas Safety Corporation. We demonstrated our instruments better in detecting accuracy other than detectors through experimental results.

Keywords: accuracy improvement, IR gas sensor, gas leak, detector

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Authors: Bo Wang

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As the first high-resolution civil optical satellite, ZY-3 satellite is able to obtain high-resolution multi-view images with three linear array sensors. The images can be used to generate Digital Elevation Models (DEM) through dense matching of stereo images. However, due to the clouds, forest, water and buildings covered on the images, there are some problems in the dense matching results such as outliers and areas failed to be matched (matching holes). This paper introduced an algorithm to verify the accuracy of DEM that generated by ZY-3 satellite with Shuttle Radar Topography Mission (SRTM). Since the accuracy of SRTM (Internal accuracy: 5 m; External accuracy: 15 m) is relatively uniform in the worldwide, it may be used to improve the accuracy of ZY-3 DEM. Based on the analysis of mass DEM and SRTM data, the processing can be divided into two aspects. The registration of ZY-3 DEM and SRTM can be firstly performed using the conjugate line features and area features matched between these two datasets. Then the ZY-3 DEM can be refined by eliminating the matching outliers and filling the matching holes. The matching outliers can be eliminated based on the statistics on Local Vector Binning (LVB). The matching holes can be filled by the elevation interpolated from SRTM. Some works are also conducted for the accuracy statistics of the ZY-3 DEM.

Keywords: ZY-3 satellite imagery, DEM, SRTM, refinement

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Authors: Sally Salah El Menshawy, Ghada M. Ahmed GabAllah, Doaa Khedr M. Khedr

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Background: Our study aims to detect the diagnostic role of DTI in the differentiation of salivary glands benign and malignant lesions. Results: Our study included 50 patients (25males and 25 females) divided into 4 groups (benign lesions n=20, malignant tumors n=13, post-operative changes n=10 and normal n=7). 28 patients were with parotid gland lesions, 4 patients were with submandibular gland lesions and only 1 case with sublingual gland affection. The mean fractional anisotropy (FA) and apparent diffusion coefficient (ADC) of malignant salivary gland tumors (n = 13) (0.380±0.082 and 0.877±0.234× 10⁻³ mm² s⁻¹) were significantly different (P<0.001) than that of benign tumors (n = 20) (0.147±0.03 and 1.47±0.605 × 10⁻³ mm² s⁻¹), respectively. The mean FA and ADC of post-operative changes (n = 10) were (0.211±0.069 and 1.63±0.20× 10⁻³ mm² s⁻¹) while that of normal glands (n =7) was (0.251±0.034and 1.54±0.29× 10⁻³ mm² s⁻¹), respectively. Using ADC to differentiate malignant lesions from benign lesions has an (AUC) of 0.810, with an accuracy of 69.7%. ADC used to differentiate malignant lesions from post-operative changes has (AUC) of 1.0, and an accuracy of 95.7%. FA used to discriminate malignant from benign lesions has (AUC) of 1.0, and an accuracy of 93.9%. FA used to differentiate malignant from post-operative changes has (AUC) of 0.923, and an accuracy of 95.7%. Combined FA and ADC used to differentiate malignant from benign lesions has (AUC) of 1.0, and an accuracy of 100%. Combined FA and ADC used to differentiate malignant from post-operative changes has (AUC) of 1.0, and an accuracy of 100%. Conclusion: Combined FA and ADC can differentiate malignant tumors from benign salivary gland lesions.

Keywords: diffusion tensor imaging, MRI, salivary gland, tumors

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Authors: Wuon-Shik Kim, Hyoung-Min Choi, Jeonggeon Woo, Sun Jung Kwon, SeungHee Lee

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The research on attentional engagement (AE) in movies using physiological signals is rare and controversial. Therefore, whether physiological responses can be applied to evaluate AE in actual movies is unclear. To clarify this, we measured electrocardiogram and electroencephalogram (EEG) of 16 Japanese university students as they watched the American movie Iron Man. After the viewing, we evaluated the subjective AE and affection levels for 11 film content segments in Iron Man. Based on self-reports for AE, we selected two film content segments as stimuli: Film Content 9 describing Tony Stark (the main character) flying through the night sky (with the highest AE score) and Film Content 1, describing Tony Stark and his colleagues telling indecent jokes (with the lowest score). We divided these two content segments into two time intervals, respectively. Results indicated that the Film Content by Interval interaction for HR was significant, at F (1, 11)=35.64, p<.001, η2=.76; while HR in Film Content 1 decreased, that of in Film Content 9 increased. In Film Content 9, the main effects of the Interval for respiratory sinus arrhythmia (RSA) (F (1, 11)=5.91, p<.05, η2=.35) and for the attention index of EEG (F (1, 11)=5.23, p<.05, η2=.37) were significant. The increase in the RSA was significant (p<.05) as well, whereas that of the EEG attention index was nearly significant (p=.069). In conclusion, while RSA increases, HR decreases when people direct their attention toward normal films. However, while paying attention to a film evoking excitement, HR as well as RSA can increase.

Keywords: attentional engagement, electroencephalogram, movie, respiratory sinus arrhythmia

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Authors: Cher Rong Matthew Kong, Edmund Tian, Seng Poon Ong, Chee Sian Gan

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Gamma-aminobutyric acid (GABA) is a non-protein amino acid that is a functional constituent of certain rice varieties. When consumed, it decreases blood pressure and reduces the risk of hypertension-related diseases. This has led to more research dedicated towards the development of functional food products (e.g. germinated brown rice) with enhanced GABA content, and the development of these functional food products has led to increased demand for instrument-based methods that can efficiently and effectively determine GABA content. Current analytical methods require analyte derivatisation, and have significant disadvantages such as being labour intensive and time-consuming, and being subject to analyte loss due to the increased complexity of the sample preparation process. To address this, an LC-MS-MS method for the determination of GABA in rice products has been developed and validated. This developed method involves a relatively simple sample preparation process before analysis using HILIC LC-MS-MS. This method eliminates the need for derivatisation, thereby significantly reducing the labour and time associated with such an analysis. Using LC-MS-MS also allows for better differentiation of GABA from any potential co-eluting compounds in the sample matrix. Results obtained from the developed method demonstrated high linearity, accuracy, and precision for the determination of GABA (1ng/L to 8ng/L) in a variety of brown rice products. The method can significantly simplify sample preparation steps, improve the accuracy of quantitation, and increase the throughput of analyses, thereby providing a quick but effective alternative to established instrumental analysis methods for GABA in rice.

Keywords: functional food, gamma-aminobutyric acid, germinated brown rice, method development

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Authors: Yasmeen Bassas, Sandra Kuebler, Allen Riddell

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Native language identification is one of the growing subfields in natural language processing (NLP). The task of native language identification (NLI) is mainly concerned with predicting the native language of an author’s writing in a second language. In this paper, we investigate the performance of two types of features; content-based features vs. content independent features, when they are evaluated on a different corpus (using social media data “Reddit”). In this NLI task, the predefined models are trained on one corpus (TOEFL), and then the trained models are evaluated on different data using an external corpus (Reddit). Three classifiers are used in this task; the baseline, linear SVM, and logistic regression. Results show that content-based features are more accurate and robust than content independent ones when tested within the corpus and across corpus.

Keywords: NLI, NLP, content-based features, content independent features, social media corpus, ML

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Authors: Perumalla Naveen Kumar

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Global Positioning System (GPS) is used for civilian and military user positioning applications. The accuracy of GPS is degrading mainly because of ionospheric error. It is very important to analyze the effects of ionosphere on the performance of satellite systems especially in the low latitude regions. These variations depend on the Total Electron Content (TEC) in the ionosphere. To investigate the variations in the atmosphere, a mini satellite known as YOUTHSAT is launched by India. This is the outcome of the collaboration between India and USSR. One of the YOUTHSAT Indian payload is RaBIT (Radio Beacon for Ionospheric Tomography). In this paper, YOUTHSAT RaBIT payload data for the three typical days of 2011 are considered. The analysis is carried out for four Indian stations. The variations of Slant TEC, elevation angle and azimuth angles are analyzed with respect to local time. The obtained results are encouraging.

Keywords: Global Positioning System (GPS), Total Electron Content (TEC), YOUTHSAT, Radio Beacon for Ionospheric Tomography (RaBIT)

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Authors: Mohamed Boualem Salah

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This work involves an experimental study of the behavior of chlef sand under effect of various parameters influencing on shear strength. Because of their distinct nature, sands, silts and clays exhibit completely different behavior (shear strength, the contracting and dilatancy, the angle of internal friction and cohesion etc.). By cons when these materials are mixed, their behavior will become different from each considered alone. The behavior of these mixtures (silty sands etc.) is currently the state of several studies to better use. We studied in this work: The influence of the following factors on the shear strength: (The density, the fines content, the water content). The apparatus used for the tests is the shear box casagrande. This device, although one may have some disadvantages and modern instrumentation is appropriate used to study the shear strength of soils.

Keywords: behavior, shear strength, sand, silt, friction angle, cohesion, fines content, moisture content

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Authors: Sarita Pinmanee, Saipan Krapbia, Rataya Yanaphan

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Hemp (Cannabis sativa L.) is multi-purpose crop delivering fibers, shives, and seed. The fiber is used today for special paper, insulation material, and biocomposites. This research was to improve low delta-9 Tetrahydrocannabinol (THC) hemp variety for high fiber contents. Mass selection for increased fiber content in four low THC Thai cultivars (including RPF1, RPF2, RPF3, and RPF4) was carried out in highland areas in the northern Thailand. Research work was conducted for three consecutive growing seasons during 2012 to 2014 at Pangda Royal Agricultural Station, Samoeng District, Chiang Mai Province, Thailand. Results of selection indicated that after selecting for three successive generations, the average fiber content of four low THC Thai cultivars increased to 28-36 %. The resulted of selection was found that fiber content of RPF1, RPF2, RPF3 and RPF4 increased to 20.6, 19.1, 19.9 and 22.8%, respectively. In addition, THC contents of these four varieties were 0.07, 0.138, 0.08 and 0.072 % respectively. As well, mass selection method was considered as an effective and suitable method for improving this fiber content.

Keywords: Hemp, mass selection, fiber content, low THC content

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Authors: Babak Moradi, Hassan Zare-Maivan

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A greenhouse investigation has been conducted to study the effect of crude oil on morphology and protein content of Avicennia marina plant. Avicennia marina seeds were sown in different concentrations of the crude oil mixed soil (i.e., 2.5, 5, 7.5, and 10 w/w). Controls and replicates were also set up. Morphological traits were recorded 4 months after plantation. Avicennia marina seedlings could tolerate up to 10% (w/w). Results demonstrated that there was a reduction in plant shoot and root biomass with the increase of crude oil concentration. Plant height, total leaf number and length reduced significantly with increase of crude oil contamination. Investigation revealed that there is a great impact of crude oil contamination on protein content of the roots of the experimental plant. Protein content of roots grown in different concentrations of crude oil were more than those of the control plant. Further, results also showed that protein content was increased with increased concentration of crude oil.

Keywords: Avicennia marina, morphology, oil contamination, protein content

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Authors: Sachin S. Patil, Mohan I. Mehta, Sandip J. Sutar, Akshay B. Patil, Shreyas S. Kirwai, Suresh Arangi

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MnS is the most commonly found inclusion in steel, which is desirable for machinability of alloy steels but only up to a certain limit, beyond which it weakens fatigue properties of steel. In present work, the effect of sulfur content and its inclusions on the fatigue behavior of AISI 4140 steel is studied (sulfur content 0.002% and 0.016%). Metallurgical analysis, Mechanical testing and Rotating Bending Fatigue (RBF) test were carried out. With the increase in sulfur content, ductility and toughness of the material decrease significantly and large scatter is observed in UTS and impact energy values. From the results of RBF testing, it can be observed that increase in sulfur content from 0.002% to 0.016% has a negligible effect on the endurance strength of AISI 4140 for similar hardness level. Fractography analysis was carried out to study the failure modes in testing.

Keywords: AISI 4140, sulfur content, MnS inclusion, rotating bending fatigue

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Authors: Gül Ebru Orhun

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A half diallel crossing design was carried out during 2011 and 2012 growing seasons under Çanakkale-Turkey ecological conditions. In this research, 20 F1 maize hybrids obtained by 6x6 half diallel crossing were used. Gene action for protein content and grain yield traits were explored in half set involving six elite inbred lines. According to the results diallel analysis dominance and additive gene variances were determined for protein content. Variance/Co-variance graphs revealed for grain yield and protein content traits. In this study, inheritance of grain yield and protein content demonstrated over-dominance type of gene action.

Keywords: protein, maize, inheritance, gene action

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Authors: Nima Pirhadi, Yong Bo Shao, Xusheng Wa, Jianguo Lu

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Several models based on the simplified method introduced by Seed and Idriss (1971) have been developed to assess the liquefaction potential of saturated sandy soils. The procedure includes determining the cyclic resistance of the soil as the cyclic resistance ratio (CRR) and comparing it with earthquake loads as cyclic stress ratio (CSR). Of all methods to determine CRR, the methods using shear-wave velocity (Vs) are common because of their low sensitivity to the penetration resistance reduction caused by fine content (FC). To evaluate the capability of the models, based on the Vs., the new data from Bachu-Jianshi earthquake case history collected, then the prediction results of the models are compared to the measured results; consequently, the accuracy of the models are discussed via three criteria and graphs. The evaluation demonstrates reasonable accuracy of the models in the Banchu region.

Keywords: seismic liquefaction, banchu-jiashi earthquake, shear-wave velocity, liquefaction potential evaluation

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Authors: Zachary Pan

Abstract:

Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

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Authors: Jung Ae Park, Jooyong Park

Abstract:

Writing is an important learning activity that cultivates higher level thinking. Effective and immediate feedback is necessary to help improve students' writing skills. Peer assessment can be an effective method in writing tasks because it makes it possible for students not only to receive quick feedback on their writing but also to get a chance to examine different perspectives on the same topic. Peer assessment can be practiced frequently and has the advantage of immediate feedback. However, there is controversy about the accuracy of peer assessment. In this study, we tried to demonstrate experimentally how the accuracy of peer assessment could be improved. Participants (n=76) were randomly assigned to groups of 4 members. All the participant graded two sets of 4 essays on the same topic. They graded the first set twice, and the second set or the posttest once. After the first grading of the first set, each group in the experimental condition 1 (discussion group), were asked to discuss the results of the peer assessment and then to grade the essays again. Each group in the experimental condition 2 (reading group), were asked to read the assessment on each essay by an expert and then to grade the essays again. In the control group, the participants were asked to grade the 4 essays twice in different orders. Afterwards, all the participants graded the second set of 4 essays. The mean score from 4 participants was calculated for each essay. The accuracy of the peer assessment was measured by Pearson correlation with the scores of the expert. The results were analyzed by two-way repeated measure ANOVA. The main effect of grading was observed: Grading accuracy got better as the number of grading experience increased. Analysis of posttest accuracy revealed that the score variations within a group of 4 participants decreased in both discussion and reading conditions but not in the control condition. These results suggest that having students discuss their grading together can be an efficient means to improve peer assessment accuracy. By discussing, students can learn from others about what to consider in grading and whether their grading is too strict or lenient. Further research is needed to examine the exact cause of the grading accuracy.

Keywords: peer assessment, evaluation accuracy, discussion, score variations

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Authors: Murray Olowa

Abstract:

This article examines the studies investigating the Mathematical Knowledge for Teaching (MKT) of secondary preservice teachers in Papua New Guinea based on probabilities. This research was conducted due to the continuous issues faced in the country in both primary and secondary education, like changes in curriculum, emphasis on mathematics and science education, and a decline in mathematics performance. Moreover, the mathematics curriculum doesn’t capture Pedagogical Content Knowledge (PCK) or Subject Matter Knowledge (SMK). The two main domains that have been identified are SMK and PCK, which have been further sub-divided into Common Content Knowledge (CCK), Specialised Content Knowledge (SCK) and Horizon Content Knowledge (HCK), and Knowledge of Content and Students (KCS), Knowledge of Content and Teaching (KCT) and Knowledge of Content and Curriculum (KCC), respectively. The data collected from 15-_year-_ ones and 15-_year-_fours conducted at St Peter Chanel Secondary Teachers College revealed that there is no significant difference in subject matter knowledge between year one and year four since the P-value of 0.22>0.05. However, it was revealed that year fours have higher pedagogical content knowledge than year one since P-value was 0.007<0.05. Finally, the research has proven that year fours have higher MKT than year one. This difference occurred due to final year preservice teachers’ hard work and engagement in mathematics curriculum and teaching practice.

Keywords: mathematical knowledge for teaching, subject matter knowledge, pedagogical content knowledge, Papua New Guinea, preservice teachers, probability

Procedia PDF Downloads 80