Search results for: extracting rules

Authors: Nutthapat Kaewrattanapat, Wannarat Bunchongkien

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The purposes of this research are to study and develop the algorithm of Thai spoonerism words by semi-automatic computer programs, that is to say, in part of data input, syllables are already separated and in part of spoonerism, the developed algorithm is utilized, which can establish rules and mechanisms in Thai spoonerism words for bi-syllables by utilizing analysis in elements of the syllables, namely cluster consonant, vowel, intonation mark and final consonant. From the study, it is found that bi-syllable Thai spoonerism has 1 case of spoonerism mechanism, namely transposition in value of vowel, intonation mark and consonant of both 2 syllables but keeping consonant value and cluster word (if any). From the study, the rules and mechanisms in Thai spoonerism word were applied to develop as Thai spoonerism word software, utilizing PHP program. the software was brought to conduct a performance test on software execution; it is found that the program performs bi-syllable Thai spoonerism correctly or 99% of all words used in the test and found faults on the program at 1% as the words obtained from spoonerism may not be spelling in conformity with Thai grammar and the answer in Thai spoonerism could be more than 1 answer.

Keywords: algorithm, spoonerism, computational linguistics, Thai spoonerism

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Authors: Yindi Zhao, Yun Zhang, Silu Xia, Lixin Wu

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The contours and areas of water surfaces, especially lakes, often change due to natural disasters and construction activities. It is an effective way to extract and update water contours from satellite images using image processing algorithms. However, to produce optimal water surface contours that are close to true boundaries is still a challenging task. This paper compares the performances of three different level set models, including the Chan-Vese (CV) model, the signed pressure force (SPF) model, and the region-scalable fitting (RSF) energy model for extracting lake contours. After experiment testing, it is indicated that the RSF model, in which a region-scalable fitting (RSF) energy functional is defined and incorporated into a variational level set formulation, is superior to CV and SPF, and it can get desirable contour lines when there are “holes” in the regions of waters, such as the islands in the lake. Therefore, the RSF model is applied to extracting lake contours from Landsat satellite images. Four temporal Landsat satellite images of the years of 2000, 2005, 2010, and 2014 are used in our study. All of them were acquired in May, with the same path/row (121/036) covering Xuzhou City, Jiangsu Province, China. Firstly, the near infrared (NIR) band is selected for water extraction. Image registration is conducted on NIR bands of different temporal images for information update, and linear stretching is also done in order to distinguish water from other land cover types. Then for the first temporal image acquired in 2000, lake contours are extracted via the RSF model with initialization of user-defined rectangles. Afterwards, using the lake contours extracted the previous temporal image as the initialized values, lake contours are updated for the current temporal image by means of the RSF model. Meanwhile, the changed and unchanged lakes are also detected. The results show that great changes have taken place in two lakes, i.e. Dalong Lake and Panan Lake, and RSF can actually extract and effectively update lake contours using multi-temporal satellite image.

Keywords: level set model, multi-temporal image, lake contour extraction, contour update

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Authors: Hamid Vahidkia

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Purview has customarily been considered in worldwide law as simply an address of the rights and powers of states. Conceived in this way, the rules onward serve the imperative work of delimiting (whereas tolerating a few covers of) state administrative specialist – the address of when an individual or occasion may be subject to national direction – a work which is shared with the cognate teach of private worldwide law. This article proposes that the thought and the rules of locale in worldwide law require reconceptualization in light of three advancements. The primary is the developing acknowledgment that in an extend of circumstances, the work out of national locale may, beneath worldwide law, be an address of duty or commitment instead of right. The moment advancement is the expanded acknowledgment that such jurisdictional obligations may, in a few circumstances, be owed not as it were to other states but also to private parties, especially through the rise and fortifying of the teachings of refusal of equity and get to equity. The third improvement is the broadly perceived wonder known as party independence, beneath which private parties in the gracious debate have the control to bestow locale on national courts and to decide themselves which law administers their connections. In combination, these improvements propose the need to reexamine the concept of ward in worldwide law to reflect the more complex substances of a worldwide lawful arrangement beneath which states possess both jurisdictional rights and commitments and are not the elite on-screen characters.

Keywords: international law, jurisdiction, purview, preconceptions, commitment

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Authors: Kanika Kalra, Harmeet Kaur, Dinesh Goyal

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Total phenolics were extracted from waste orange peels by solvent extraction and alkali hydrolysis method. The most efficient solvents for extracting phenolic compounds from waste biomass were methanol (60%) > dimethyl sulfoxide > ethanol (60%) > distilled water. The extraction yields were significantly impacted by solvents (ethanol, methanol, and dimethyl sulfoxide) due to varying polarity and concentrations. Extraction of phenolics using 60% methanol yielded the highest phenolics (in terms of gallic acid equivalent (GAE) per gram of biomass) in orange peels. Alkali hydrolyzed extract from orange peels contained 7.58±0.33 mg GAE g⁻¹. By using the solvent extraction technique, it was observed that 60% methanol is comparatively the best-suited solvent for extracting polyphenolic compounds and gave the maximum yield of 4.68 ± 0.47 mg GAE g⁻¹ in orange peel extracts. DPPH radical scavenging activity and reducing the power of orange peel extract were checked, where 60% methanolic extract showed the highest antioxidant activity, 85.50±0.009% for DPPH, and dimethyl sulfoxide (DMSO) extract gave the highest yield of 1.75±0.01% for reducing power ability of the orange peels extract. Characterization of the polyphenolic compounds was done by using Fourier transformation infrared (FTIR) spectroscopy. Solvent and alkali hydrolysed extracts were evaluated for antibacterial activity using the agar well diffusion method against Gram-positive Bacillus subtilis MTCC441 and Gram-negative Escherichia coli MTCC729. Methanolic extract at 300µl concentration showed an inhibition zone of around 16.33±0.47 mm against Bacillus subtilis, whereas, for Escherichia coli, it was comparatively less. Broth-based turbidimetric assay revealed the antibacterial effect of different volumes of orange peel extracts against both organisms.

Keywords: orange peels, total phenolic content, antioxidant, antibacterial

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Authors: Libena Cernohorska, Barbora Sutorova, Petr Teply

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There are pending discussions over an impact of global regulatory efforts on banks. In this paper we present a literature review on the profitability-risk-capital relationship in banking. Research papers dealing with this topic can be divided into two groups: the first group focusing on a capital-risk relationship and the second group analyzing a capital-profitability relationship. The first group investigates whether the imposition of stricter capital requirements reduces risk-taking incentives of banks based on a simultaneous equations model. Their model pioneered the idea that the changes in both capital and risk have endogenous and exogenous components. The results obtained by the authors indicate that changes in the capital level are positively related to the changes in asset risk. The second group of the literature concentrating solely on the relationship between the level of held capital and bank profitability is limited. Nevertheless, there are a lot of studies dealing with the banks’ profitability as such, where bank capital is very often included as an explanatory variable. Based on the literature review of dozens of relevant papers in this study, an empirical research on banks’ profitability and risk adjustment decisions under new banking rules Basel III rules can be easily undertaken.

Keywords: bank, Basel III, capital, decision making, profitability, risk, simultaneous equations model

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Authors: Y. Long, L. Liu, K. V. Branin

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One challenge faced by procurement decision-maker during the acquisition process is how to compare similar products from different suppliers and allocate orders among different products or services. This work focuses on allocating orders among multiple suppliers considering rebate. The objective function is to minimize the total acquisition cost including purchasing cost and rebate benefit. Rebate benefit is complex and difficult to estimate at the ordering step. Rebate rules vary for different suppliers and usually change over time. In this work, we developed a system to collect the rebate policies, standardized the rebate policies and developed two-stage optimization models for ordering allocation. Rebate policy with multi-tiers is considered in modeling. The discontinuous cost function of rebate benefit is formulated for different scenarios. A piecewise linear function is used to approximate the discontinuous cost function of rebate benefit. And a Mixed Integer Programing (MIP) model is built for order allocation problem with multi-tier rebate. A case study is presented and it shows that our optimization model can reduce the total acquisition cost by considering rebate rules.

Keywords: discontinuous cost function, mixed integer programming, optimization, procurement, rebate

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Authors: Mehran Asadi, Afrand Agah

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In data mining, partitioning is used as a fundamental tool for classification. With the help of partitioning, we study the structure of data, which allows us to envision decision rules, which can be applied to classification trees. In this research, we used online social network dataset and all of its attributes (e.g., Node features, labels, etc.) to determine what constitutes an above average chance of being a divergent node. We used the R statistical computing language to conduct the analyses in this report. The data were found on the UC Irvine Machine Learning Repository. This research introduces the basic concepts of classification in online social networks. In this work, we utilize overfitting and describe different approaches for evaluation and performance comparison of different classification methods. In classification, the main objective is to categorize different items and assign them into different groups based on their properties and similarities. In data mining, recursive partitioning is being utilized to probe the structure of a data set, which allow us to envision decision rules and apply them to classify data into several groups. Estimating densities is hard, especially in high dimensions, with limited data. Of course, we do not know the densities, but we could estimate them using classical techniques. First, we calculated the correlation matrix of the dataset to see if any predictors are highly correlated with one another. By calculating the correlation coefficients for the predictor variables, we see that density is strongly correlated with transitivity. We initialized a data frame to easily compare the quality of the result classification methods and utilized decision trees (with k-fold cross validation to prune the tree). The method performed on this dataset is decision trees. Decision tree is a non-parametric classification method, which uses a set of rules to predict that each observation belongs to the most commonly occurring class label of the training data. Our method aggregates many decision trees to create an optimized model that is not susceptible to overfitting. When using a decision tree, however, it is important to use cross-validation to prune the tree in order to narrow it down to the most important variables.

Keywords: online social networks, data mining, social cloud computing, interaction and collaboration

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Authors: Kim Nolte, Ben J. M. Steyn, Pieter E. Krüger, Lizelle Fletcher

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Objective: The primary aim of this research was to determine the attitudes, beliefs and knowledge of talented young South African athletes regarding prohibited performance-enhancing drugs (PEDs) and anti-doping rules and regulations. Methods: This was a survey study and a quantitative research approach was used. South African TuksSport academy athletes at the High Performance Centre, University of Pretoria and competitive high school athletes at four private high schools in Gauteng completed the survey. A self-determined structured questionnaire was used to establish the attitudes, beliefs and knowledge of the athletes. Results: A total of 346 (208 males, 138 females) athletes, age (mean ± SD) 16.9 ±1.41 years participated in the survey. According to this survey, 3.9% of the athletes in this survey admitted to be using a prohibited PED and more than 14% of the athletes said they would consider using a prohibited PED if they knew they would not get caught out. Ambition (46%) and emotional pressure (22.5%) was the primary reasons why the athletes would consider using prohibited PEDs. Even though coaches appear to be the main source of information (PEDs and anti-doping rules), only 42.1% of the athletes felt they were well informed. Conclusion: Controlling doping by means of testing is important. However, it is not sufficient and interventions should include psychosocial programmes planned and developed focusing on changing attitudes towards doping and doping culture, as well as the appropriate education specifically on the health risks of using PEDs.

Keywords: doping, anti-doping, attitudes, athletes and sport

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Authors: Esther Robert, Romanus Aboh

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This paper undertakes a socio-pragmatic investigation of gender enactment in new month text messages. This study employs Gumperz’s Interactional Sociolinguistics as its theoretical point of reference to investigate how people create meaning through social interaction. This theory attempts to analyse any social interaction based on contextualization cues and presuppositions. This study explores the appropriateness of language used in texting. The text messages are collected from different mobile phones from different genders, which form the data for this paper. The study observes remarkable differences between genders in the use of informal language. The study reveals that men and women differ remarkably in conversational interaction as well as in writing. While it is observed that women are emotional, orderly, and meticulous, detailed and observed certain grammatical rules, men are casual, brief and appear to show evidence that less attention is paid to grammatical rules. Also, the study shows women as relaxing, showing love, care, concern with their emotive, spirit-raising and touching language, while mean are direct, short, and straight to the point. It is discovered through the study that women behave this way because of their brain-wiring. That is why language and communication matter more to women than to men and this reflects in their new month text messages.

Keywords: difference, emotionalised expressions, gender, texting

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Authors: M. Orefice, V. Di Vito

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This paper provides a description of a Collision Avoidance algorithm that has been developed starting from the mathematical modeling of the flight of insects, in terms of spirals and conchospirals geometric paths. It is able to calculate a proper avoidance manoeuver aimed to prevent the infringement of a predefined distance threshold between ownship and the considered intruder, while minimizing the ownship trajectory deviation from the original path and in compliance with the aircraft performance limitations and dynamic constraints. The algorithm is designed in order to be suitable for real-time applications, so that it can be considered for the implementation in the most recent airborne automatic collision avoidance systems using the traffic data received through an ADS-B IN device. The presented approach is able to take into account the rules-of-the-air, due to the possibility to select, through specifically designed decision making logic based on the consideration of the encounter geometry, the direction of the calculated collision avoidance manoeuver that allows complying with the rules-of-the-air, as for instance the fundamental right of way rule. In the paper, the proposed collision avoidance algorithm is presented and its preliminary design and software implementation is described. The applicability of this method has been proved through preliminary simulation tests performed in a 2D environment considering single intruder encounter geometries, as reported and discussed in the paper.

Keywords: ADS-B Based Application, Collision Avoidance, RPAS, Spiral Geometry.

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Authors: Mona Maria Mombeck

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Social participation in heterogeneous classrooms is one of the main goals in inclusive education. Children with special educational needs (SEN) and children with learning difficulties, or behavioural problems not diagnosed as SEN, are more likely to be excluded by other children than others. It is proven that the presence of dogs, as well as contact with dogs, increases the likelihood of positive social behaviour between humans. Therefore, animal-assisted pedagogy may be presumed to be a constructive way of inclusive teaching and facing the challenges of social inclusion in school classes. This study investigates the presence of a friendly dog in heterogeneous groups of pupils in order to evaluate the influence of dogs on facets of social participation of children in school. 30 German pupils, aged from 10 to 14, in four classes were questioned about their social participation before and after they were educated for a year in school with animal-assisted-pedagogy, using the problem-concerned interview method. In addition, the post-interview includes some general questions about the putative differences or similarities of being educated with and without a dog. The interviews were analysed with the qualitative-content-analysis using QDA software. The results showed that a dog has a positive impact on the atmosphere, student relationships, and well-being in class. Regarding the atmosphere, the pupils mainly argued that the improvement was caused by taking into account the dog’s well-being, respecting the dog-related rules, and by emotional self-regulation. It can be supposed that children regard the rules concerning the dog as more relevant to them than rules, not concerning the dog even if they require the same behaviour and goal. Furthermore, a dog has a positive impact on emotional self-regulation and, therefore, on pupil’s behaviour in class and the atmosphere. In terms of the statements about relationships, the dog’s presence was mainly seen to provide both a unifying aim and a uniting topic to talk about. The improved well-being was described as a feeling of joy and peace of mind. Moreover, the teacher was evaluated as more friendly and trustworthy after animal-assisted teaching. Nevertheless, animal-assisted pedagogy can, rarely, cause problems as well, such as jealousy, distraction, or concerns about the well-being of the dog. The study could prove the relevance of animal-assisted pedagogy for facing the challenges of social participation in inclusive education.

Keywords: animal-assisted-pedagogy, inclusive education, human-animal-interactions, social participation

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Authors: Rodrigo Arnaldo Scarpel

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Trend following is a widely accepted investment strategy that adopts a rule-based trading mechanism that rather than striving to predict market direction or on information gathering to decide when to buy and when to sell a stock. Thus, in trend following one must respond to market’s movements that has recently happen and what is currently happening, rather than on what will happen. Optimally, in trend following strategy, is to catch a bull market at its early stage, ride the trend, and liquidate the position at the first evidence of the subsequent bear market. For applying the trend following strategy one needs to find the trend and identify trade signals. In order to avoid false signals, i.e., identify fluctuations of short, mid and long terms and to separate noise from real changes in the trend, most academic works rely on moving averages and other technical analysis indicators, such as the moving average convergence divergence (MACD) and the relative strength index (RSI) to uncover intelligible stock trading rules following trend following strategy philosophy. Recently, some works has applied machine learning techniques for trade rules discovery. In those works, the process of rule construction is based on evolutionary learning which aims to adapt the rules to the current environment and searches for the global optimum rules in the search space. In this work, instead of focusing on the usage of machine learning techniques for creating trading rules, a time series trend classification employing a semi-supervised approach was used to early identify both the beginning and the end of upward and downward trends. Such classification model can be employed to identify trade signals and the decision-making procedure is that if an up-trend (down-trend) is identified, a buy (sell) signal is generated. Semi-supervised learning is used for model training when only part of the data is labeled and Semi-supervised classification aims to train a classifier from both the labeled and unlabeled data, such that it is better than the supervised classifier trained only on the labeled data. For illustrating the proposed approach, it was employed daily trade information, including the open, high, low and closing values and volume from January 1, 2000 to December 31, 2022, of the São Paulo Exchange Composite index (IBOVESPA). Through this time period it was visually identified consistent changes in price, upwards or downwards, for assigning labels and leaving the rest of the days (when there is not a consistent change in price) unlabeled. For training the classification model, a pseudo-label semi-supervised learning strategy was used employing different technical analysis indicators. In this learning strategy, the core is to use unlabeled data to generate a pseudo-label for supervised training. For evaluating the achieved results, it was considered the annualized return and excess return, the Sortino and the Sharpe indicators. Through the evaluated time period, the obtained results were very consistent and can be considered promising for generating the intended trading signals.

Keywords: evolutionary learning, semi-supervised classification, time series data, trading signals generation

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Authors: Rami Al-Sadi

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The assignment of lexical stress in English to its correct syllable is an enormous challenge to EFL learners, especially if their first language (L1) phonology is very different from English phonology. Arabic-speaking EFL learners not only stumble very frequently when it comes to placing the lexical stress in a given word, but they also seem to relegate the role of lexical stress as unimportant, mainly because in Arabic, unlike in English, lexical stress is not phonemic. This study aims at exploring the possible benefits of utilizing spectrographic representations of English words correctly pronounced, for the purpose of finding out how these spectrograms can provide a visual aid to the learners and help them rectify their stress placement errors as they see in real time spectrograms of the correct pronunciations juxtaposed on a computer screen with spectrograms of their own pronunciations for easy comparison. The study involved 120 students from the English Department at Prince Sattam bin Abdulaziz University in Saudi Arabia. 60 participants were taught the English lexical stress rules and also received spectrographic guidance on pronunciation; the other 60 received only verbal instruction on the stress rules and verbal feedback on their pronunciations. Statistical results showed that when the learners had the opportunity to ‘see’ their pronunciation mistakes, they were three times more likely to rectify their placement of lexical stress.

Keywords: Arabic-speaking EFL learners, lexical stress, pronunciation, spectrographic representation, stress placement

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Authors: Noelia Collado-Rodriguez

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The Mortgage Credit Directive 2014/17/UE should have been transposed the 21st of March of 2016. However, in Spain not only we did not meet the deadline, but currently we just have a preliminary draft of the so-called Mortgage Credit Act. Before we analyze the preliminary draft from the standpoint of the responsible lending principle, we should point out that this preliminary draft is not a consumer law statute. Through the text of the preliminary draft we cannot see any reference to the consumer, but we see references to the borrower. Furthermore, and more important, the application of this statute would not be, according to its text, circumscribed to borrowers who address the credit to a personal purpose. Instead, it seems that the preliminary draft aims to be one more of the rules of banking transparency that already exists in the Spanish legislation. In this sense, we can also mention that the sanctions contained in the preliminary draft are referred to these laws of banking ordination and oversight – where the rules of banking transparency belong –. This might be against the spirit of the Mortgage Credit Directive, which allows the extension of its scope to credits aimed to acquire other immovable property beyond the residential one. However, the borrower has to be a consumer accordingly with the Directive. It is quite relevant that the prospective Spanish Mortgage Credit Act might not be a consumer protection statute; specially, from the perspective of the responsible lending principle. The responsible lending principle is a consumer law principle, which is based on the structural weakness of the consumer’s position in the relationship with the creditor. Therefore, it cannot surprise that the Spanish preliminary draft does not state any of the pre contractual conducts that express the responsible lending principle. We are referring to the lender’s duty to provide adequate explanations; the consumer’s suitability test; the lender’s duty to assess consumer’s creditworthiness; the consultation of databases to perform the creditworthiness assessment; and the most important, the lender’s prohibition to grant credit in case of a negative creditworthiness assessment. The preliminary draft just entitles the Economy Ministry to enact provisions related to those topics. Thus, the duties and rules derived from the responsible lending principle included in the EU Directive will not have legal character in Spain, being mere administrative regulations. To conclude, the two main questions that come up after reading the Spanish Mortgage Credit Act preliminary draft are, in the first place, what kind of consequences might arise from the Mortgage Credit Act if finally it is not a consumer law statute. And in the second place, what might be the consequences for the responsible lending principle of being developed by administrative regulations instead of by legislation.

Keywords: consumer credit, consumer protection, creditworthiness assessment, responsible lending

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Authors: Hong-Yi Lin, Feng-Tyan Lin

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In a Bike-sharing system (BSS), users can easily rent bikes from any station in the city for mid-range or short-range trips. BSS can also be integrated with other types of transport system, especially Green Transportation system, such as rail transport, bus etc. Since BSS records time and place of each pickup and return, the operational data can reflect more authentic and dynamic state of user behaviors. Furthermore, land uses around docking stations are highly associated with origins and destinations for the BSS users. As urban researchers, what concerns us more is to take BSS into consideration during the urban planning process and enhance the quality of urban life. This research focuses on the simulation of travel behavior of BSS users in Kaohsiung. First, rules of users’ behavior were derived by analyzing operational data and land use patterns nearby docking stations. Then, integrating with Monte Carlo method, these rules were embedded into a travel behavior simulation model, which was implemented by NetLogo, an agent-based modeling tool. The simulation model allows us to foresee the rent-return behaviour of BSS in order to choose potential locations of the docking stations. Also, it can provide insights and recommendations about planning and policies for the future BSS.

Keywords: agent-based model, bike-sharing system, BSS operational data, simulation

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Authors: Yeonjeong Lee, Kyoung-jae Kim, Youngtae Kim

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This study proposes a novel recommender system that uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user’s preference. The proposed model consists of two steps. In the first step, this study uses logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. Then, this study combines the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. In the second step, this study uses the market basket analysis to extract association rules for co-purchased products. Finally, the system selects customers who have high likelihood to purchase products in each product group and recommends proper products from same or different product groups to them through above two steps. We test the usability of the proposed system by using prototype and real-world transaction and profile data. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The results also show that the proposed system may be useful in real-world online shopping store.

Keywords: product recommender system, ensemble technique, association rules, decision tree, artificial neural networks

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Authors: Meenakshi Barsaul Chauhan, Aastha Chauhan, Shilpa Hurmade, Rajeev Sen, Jyotsna Sen, Monika Dalal

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Introduction: Ovarian masses are common forms of neoplasm in women and represent 2/3rd of gynaecological malignancies. A pre-operative suggestion of malignancy can guide the gynecologist to refer women with suspected pelvic mass to a gynecological oncologist for appropriate therapy and optimized treatment, which can improve survival. In the younger age group preoperative differentiation into benign or malignant pathology can decide for conservative or radical surgery. Imaging modalities have a definite role in establishing the diagnosis. By using International Ovarian Tumor Analysis (IOTA) classification with sonography, costly radiological methods like Magnetic Resonance Imaging (MRI) / computed tomography (CT) scan can be reduced, especially in developing countries like India. Thus, this study is being undertaken to evaluate the role of clinical methods and sonography for diagnosis of the nature of the ovarian tumor. Material And Methods: This prospective observational study was conducted on 40 patients presenting with ovarian masses, in the Department of Obstetrics and Gynaecology, at a tertiary care center in northern India. Functional cysts were excluded. Ultrasonography and color Doppler were performed on all the cases.IOTA rules were applied, which take into account locularity, size, presence of solid components, acoustic shadow, dopper flow etc . Magnetic Resonance Imaging (MRI) / computed tomography (CT) scans abdomen and pelvis were done in cases where sonography was inconclusive. In inoperable cases, Fine needle aspiration cytology (FNAC) was done. The histopathology report after surgery and cytology report after FNAC was correlated statistically with the pre-operative diagnosis made clinically and sonographically using IOTA rules. Statistical Analysis: Descriptive measures were analyzed by using mean and standard deviation and the Student t-test was applied and the proportion was analyzed by applying the chi-square test. Inferential measures were analyzed by sensitivity, specificity, negative predictive value, and positive predictive value. Results: Provisional diagnosis of the benign tumor was made in 16(42.5%) and of the malignant tumor was made in 24(57.5%) patients on the basis of clinical findings. With IOTA simple rules on sonography, 15(37.5%) were found to be benign, while 23 (57.5%) were found to be malignant and findings were inconclusive in 2 patients (5%). FNAC/Histopathology reported that benign ovarian tumors were 14 (35%) and 26(65%) were malignant, which was taken as the gold standard. The clinical finding alone was found to have a sensitivity of 66.6% and a specificity of 90.9%. USG alone had a sensitivity of 86% and a specificity of 80%. When clinical findings and IOTA simple rules of sonography were combined (excluding inconclusive masses), the sensitivity and specificity were 83.3% and 92.3%, respectively. While including inconclusive masses, sensitivity came out to be 91.6% and specificity was 89.2. Conclusion: IOTA's simple sonography rules are highly sensitive and specific in the prediction of ovarian malignancy and also easy to use and easily reproducible. Thus, combining clinical examination with USG will help in the better management of patients in terms of time, cost and better prognosis. This will also avoid the need for costlier modalities like CT, and MRI.

Keywords: benign, international ovarian tumor analysis classification, malignant, ovarian tumours, sonography

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Authors: Adewale O. Ogunde, Olusegun Folorunso, Adesina S. Sodiya

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Most existing Distributed Association Rule Mining (DARM) systems are still facing several challenges. One of such challenges that have not received the attention of many researchers is the inability of existing systems to adapt to constantly changing databases and mining environments. In this work, an Adaptive Incremental Mining Algorithm (AIMA) is therefore proposed to address these problems. AIMA employed multiple mobile agents for the entire mining process. AIMA was designed to adapt to changes in the distributed databases by mining only the incremental database updates and using this to update the existing rules in order to improve the overall response time of the DARM system. In AIMA, global association rules were integrated incrementally from one data site to another through Results Integration Coordinating Agents. The mining agents in AIMA were made adaptive by defining mining goals with reasoning and behavioral capabilities and protocols that enabled them to either maintain or change their goals. AIMA employed Java Agent Development Environment Extension for designing the internal agents’ architecture. Results from experiments conducted on real datasets showed that the adaptive system, AIMA performed better than the non-adaptive systems with lower communication costs and higher task completion rates.

Keywords: adaptivity, data mining, distributed association rule mining, incremental mining, mobile agents

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Authors: Moshe Wasserblat, Jonathan Mamou, Oren Pereg

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Natural Language Processing (NLP) has made a major leap in the last few years, in practical integration into medical solutions; for example, extracting clinical concepts from medical texts such as medical condition, medication, treatment, and symptoms. However, training and deploying those models in real environments still demands a large amount of annotated data and NLP/Machine Learning (ML) expertise, which makes this process costly and time-consuming. We present a practical and efficient method for clinical concept extraction that does not require costly labeled data nor ML expertise. The method includes three steps: Step 1- the user injects a large in-domain text corpus (e.g., PubMed). Then, the system builds a contextual model containing vector representations of concepts in the corpus, in an unsupervised manner (e.g., Phrase2Vec). Step 2- the user provides a seed set of terms representing a specific medical concept (e.g., for the concept of the symptoms, the user may provide: ‘dry mouth,’ ‘itchy skin,’ and ‘blurred vision’). Then, the system matches the seed set against the contextual model and extracts the most semantically similar terms (e.g., additional symptoms). The result is a complete set of terms related to the medical concept. Step 3 –in production, there is a need to extract medical concepts from the unseen medical text. The system extracts key-phrases from the new text, then matches them against the complete set of terms from step 2, and the most semantically similar will be annotated with the same medical concept category. As an example, the seed symptom concepts would result in the following annotation: “The patient complaints on fatigue [symptom], dry skin [symptom], and Weight loss [symptom], which can be an early sign for Diabetes.” Our evaluations show promising results for extracting concepts from medical corpora. The method allows medical analysts to easily and efficiently build taxonomies (in step 2) representing their domain-specific concepts, and automatically annotate a large number of texts (in step 3) for classification/summarization of medical reports.

Keywords: clinical concepts, concept expansion, medical records annotation, medical records summarization

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Authors: Bubaker F. Shareia

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The aim of this paper is to determine a general frame of the auditor's legal responsibilities in Libya which were implied in professional codes and rules, these codes and rules were concerned with the auditor's rights and duties in conducting his professional duties. This will provide a background for the Libyan accounting profession, and the challenges in tailoring Auditors to meet third party's needs. Being informed of the kinds of legal responsibilities which the external auditors could face during conducting their duties. The study is based on a literature review and archival research, reinforced by a qualitative case study comprised of interviews, questionnaire and a study of internal documents. To reach such an understanding, the researcher designed two questionnaires for collecting the data. One questionnaire was distributed among the certified public accountant firms in Libya and the second was distributed among a group of randomly selected lawyers and judges in the same country. Most auditors agreed upon the determination of their responsibilities toward the state and they emphasized that their responsibilities toward their clients were limited to the accepted standards of auditing. Moreover, all auditors who were surveyed emphasized that there has never been any juridical claims against them, and as a consequence they have never paid any legal fines. This study focuses on one country, which does limit its generalisability. However, it also suggests fruitful research areas in considering the impact and challenge of the historic factors in the accounting profession in emerging economies.

Keywords: accounting, external auditor, legal responsibilities, libyan accounting profession

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Authors: Merina Islam

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In this paper, an attempt is made to draw out the contemporary relevance of philosophy in school education of India. This paper attempt is made to inquire into the importance of philosophy for schoolchildren in the Indian cultural context. As education in philosophy for children is useful for teaching the acquisition of knowledge from the information provided, for questioning of rules in different contexts, and for the analysis of facts encountered in daily life. Ethical attitudes can neither be derived from the information provided about the moral rules, nor do they result from a practice of unquestioning obedience It includes some studies done in this field and also reports on philosophy. Many European countries emphasise on the above said theme. There are lots of work and research done by many philosophers on philosophy for children. Indian values system is different from the West and more important than others. Education has become a tool to achieve efficiency in all walks of human life whether social, political, religious or philosophical. Every nation started developing its own specific set of educational values. For India it is very necessary to increase philosophical thinking study and research. Philosophy could make significant contribution, particularly in relation to children's moral development because the Indian curriculum currently neglects this aim. A teacher can play an important role in promoting this discussion because a teacher has the capacity to influence students with their thoughts and personality and engages them in these activities. Philosophy needs to be included in the curriculum and have demonstrated cognitive and social gains in children who were explored to philosophy in their schooling.

Keywords: education, ethical attitude, moral value, philosophy

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Authors: Emmanuel Ayobami Adesiyan

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Political theorists have identified ethnicity as an obstacle to democratic stability in deeply divided societies. Nigeria belongs to the categories of problematic states labeled divided or deeply divided societies, as such post-independence politics is characterized by ethnicity with its ruinous effect on democratic governance and development. Institutional Engineering, the purposive manipulation of the electoral rule relating to party organization and the electoral formula has been established in comparative political studies as a policy measure for managing ethnicity in order to stabilize politics in divided societies. This paper examines the use of electoral engineering tools in managing ethnic politics in Nigeria’s Fourth Republic. The study is guided by rational institutional theory. Secondary data on electoral rules and disaggregated results of presidential elections were collected from archival documents. Data were subjected to content analysis. Institutional changes in electoral rules have promoted the development of inter-ethnic bargaining and compromises within the party system. Presidential Electoral Formula aided the emergence of national rather parochial parties. Electoral engineering tools moved Nigerian Politics from ethnic parochialism to inclusion and accommodation. These innovations should be strengthened to enhance democratic stability.

Keywords: Nigeria, presidential-elections, ethnic politics, institutional engineering

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: Abdu Bedru Hussien

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The purpose of this study was to examine the determinants of Takaful insurance in Addis Ababa. In this study, descriptive and explanatory research design was used. We have taken marketing and business development from 17 insurance company and manager and officer from 5 insurance company those are active currently in takaful and all of them were taken as a sample. Questionnaire was used as instrument for data collection. The questionnaire contained 79 items with 5-point Likert scale, 1 being strongly disagree and 5 being strongly agree. The questionnaire was developed based on past literature and a pilot test was conducted to check normality, reliability and validity of the scale. The dependent variable used in this research was Takaful Insurance and the independent variables were Awareness, human resource, sharia rules, Regulation and interest free banking service. The collected data was analyzed using descriptive Statistics, correlation, and multiple leaner regressions through SPSS 25. The result of this research indicates that Awareness and interest free banking service have a positive and significant impact on Takaful Insurance. However, this research did not find any significant impact of human resource, sharia rules and regulation on Takaful. And also, the research indicates that, any positive improvement on these variables will result in improvement Takaful insurance. Therefore, this research recommends that the Ethiopian insurance companies to formulate strategies that boost Takaful insurance awareness as well as train manpower for the service.

Keywords: Takaful, insurance, human resource, IFB

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Authors: Kam Wen Hang, Tan Kee Teng, Huang Poh Ching, Chia Kai Xiang, H. V. Annegowda, H. S. Naveen Kumar

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Gynura procumbens (G. procumbens) leaves, commonly known as ‘sambung nyawa’ in Malaysia is a well-known medicinal plant commonly used as folk medicines in controlling blood glucose, cholesterol level as well as treating cancer. These medicinal properties were believed to be related to the polyphenolic content present in G. procumbens extract, therefore optimization of its extraction process is vital to obtain highest possible antioxidant activities. The current study was conducted to investigate the effect of different concentrations of extracting solvent (ethanol) on the amount of polyphenolic content and antioxidant activities of G. procumbens leaf extract. The concentrations of ethanol used were 30-70%, with the temperature and time kept constant at 50°C and 30 minutes, respectively using ultrasound-assisted extraction. The polyphenolic content of these extracts were quantified by Folin-Ciocalteu colorimetric method and results were expressed as milligram gallic acid equivalent (mg GAE)/g. Phosphomolybdenum method and 1, 1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging assays were used to investigate the antioxidant properties of the extract and the results were expressed as milligram ascorbic acid equivalent (mg AAE)/g and effective concentration (EC50) respectively. Among the three different (30%, 50% and 70%) concentrations of ethanol studied, the 50% ethanolic extract showed total phenolic content of 31.565 ± 0.344 mg GAE/g and total antioxidant activity of 78.839 ± 0.199 mg AAE/g while 30% ethanolic extract showed 29.214 ± 0.645 mg GAE/g and 70.701 ± 1.394 mg AAE/g, respectively. With respect to DPPH radical scavenging assay, 50% ethanolic extract had exhibited slightly lower EC50 (314.3 ± 4.0 μg/ml) values compared to 30% ethanol extract (340.4 ± 5.3 μg/ml). Out of all the tested extracts, 70% ethanolic extract exhibited significantly (p< 0.05) highest total phenolic content (38.000 ± 1.009 mg GAE/g), total antioxidant capacity (95.874 ± 2.422 mg AAE/g) and demonstrated the lowest EC50 in DPPH assay (244.2 ± 5.9 μg/ml). An excellent correlations were drawn between total phenolic content, total antioxidant capacity and DPPH radical scavenging activity (R2 = 0.949 and R2 = 0.978, respectively). It was concluded from this study that, 70% ethanol should be used as the optimal polarity solvent to obtain G. procumbens leaf extract with maximum polyphenolic content with antioxidant properties.

Keywords: antioxidant activity, DPPH assay, Gynura procumbens, phenolic compounds

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Authors: Satinder Bhatia

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Limited Liability Partnerships (LLPs) was a concept introduced in India in 2009. Ever since then, there has been a fierce growth in the number of organizations registered as LLPs outpacing the number of registrations as private companies. Among other benefits extended to LLPs, the audit being mandated only for LLPs having a turnover of at least Rs 40 lakhs or capital contribution of Rs 25 lakhs, has been a major attraction. This has resulted in only about 10 per cent of LLPs coming under mandatory audit. Even for such companies, the accounting standards to be followed in the preparation of financial statements have not been specified. The Revised Indian Accounting Standards (Revised IndAS) which are aligned with IFRS to a great extent, may apply to LLPs only under limited conditions. Thus, the veracity of even the audited financial statements of LLPs can be questioned. If in future, these LLPs would like to list on a stock exchange to raise capital, there can be serious hurdles if investors do not find the financial statements to be reliable and consistent. LLPs are generally governed by country-specific rules in the area of accounts and audit. Thus, such rules vary across UK, EU and the USA. Some countries have adopted the IFRS for SMEs and since LLPs can be referred to as SMEs; they would come under the ambit of these IFRS provisions. Besides, as the scope of audit widens to cover qualitative information in addition to quantitative data, audit of LLPs has now acquired a new meaning and a new urgency as demands for at least limited purpose audits are arising from different stakeholders including lenders, suppliers, customers and joint venture partners.

Keywords: audit disclosures, audit quality, guidance for SMEs, non-audit services

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Authors: Chukwudi Chidume

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This paper considers the symbolism of kola nut according to Igbo worldview. How kola nut helps to shape the people’s philosophical ideology, especially in relation to religion. The roles of kola nut within the Igbo socio-cultural context and the values attached to these roles will be examined. The roles of kola nut as a means of socialization, education and transmission of cultural values from the preceding to succeeding generations will come under consideration. Equally, this paper looks at the traditional rules regarding not only the uses but more essentially the mode of kola nut presentation, blessing, breaking and sharing of kola nut. How these rules and kola nut have persisted in the face of social and cultural changes which have affected the Igbo people shall be reviewed. The roles played by kola nut in Igbo religion will come under study, which is to correct some of the misconceptions by writers who are motivated by eurocentric idealism but quite oblivious of the Igbo cultural setting and the place of kola nut in it. The onslaught of Western civilization causing the change of attitude among the young generation towards kola nut as a vital aspect of our culture tends to pose a threat to the future and survival of kola nut. Again, the study of Igbo culture as many have done rarely gives an in depth knowledge on the concept, roles and symbolism of kola nut as one of the sacred objects like Ofo and Shrines in Igboland. Mostly it is forgotten that without kola nut, shrines cannot be attended to. Many people think that the spiritual significance and sacramental symbolism are not worth exploring. They, therefore, refuse to try and discover the ritual ramifications, claiming that to probe into the mystery demystifies the matter. Kola nut symbolism is not mysteriously inexplicable. It is a revered symbol of social intercourse with deep social relevance.

Keywords: communion, consecration, Igbo, kola nut, religion

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Authors: Veronica S. Moertini, Vinsensius Kevin, Gede Karya

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Customer reviews have been collected by many kinds of e-commerce websites selling products, services, hotel rooms, tickets and so on. Each website collects its own customer reviews. The reviews can be crawled, collected from those websites and stored as big data. Text analysis techniques can be used to analyze that data to produce summarized information, such as customer opinions. Then, these opinions can be published by independent service provider websites and used to help customers in choosing the most suitable products or services. As the opinions are analyzed from big data of reviews originated from many websites, it is expected that the results are more trusted and accurate. Indonesian customers write reviews in Indonesian language, which comes with its own structures and uniqueness. We found that most of the reviews are expressed with “daily language”, which is informal, do not follow the correct grammar, have many abbreviations and slangs or non-formal words. Hadoop is an emerging platform aimed for storing and analyzing big data in distributed systems. A Hadoop cluster consists of master and slave nodes/computers operated in a network. Hadoop comes with distributed file system (HDFS) and MapReduce framework for supporting parallel computation. However, MapReduce has weakness (i.e. inefficient) for iterative computations, specifically, the cost of reading/writing data (I/O cost) is high. Given this fact, we conclude that MapReduce function is best adapted for “one-pass” computation. In this research, we develop an efficient technique for extracting or mining opinions from big data of Indonesian reviews, which is based on MapReduce with one-pass computation. In designing the algorithm, we avoid iterative computation and instead adopt a “look up table” technique. The stages of the proposed technique are: (1) Crawling the data reviews from websites; (2) cleaning and finding root words from the raw reviews; (3) computing the frequency of the meaningful opinion words; (4) analyzing customers sentiments towards defined objects. The experiments for evaluating the performance of the technique were conducted on a Hadoop cluster with 14 slave nodes. The results show that the proposed technique (stage 2 to 4) discovers useful opinions, is capable of processing big data efficiently and scalable.

Keywords: big data analysis, Hadoop MapReduce, analyzing text data, mining Indonesian reviews

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Authors: Mojtaba Eshraghi Arani

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Concluding the contract for carriage of cargo with the shipper (through bill of lading or charterparty), the carrier must transport the cargo from loading port to the port of discharge and deliver it to the consignee. Unless otherwise agreed in the contract, the carrier must avoid from any deviation, transfer of cargo to another vessel or unreasonable stoppage of carriage in-transit. However, the vessel might break down in-transit for any reason and becomes unable to continue its voyage to the port of discharge. This is a frequent incident in the carriage of goods by sea which leads to important dispute between the carrier/owner and the shipper/charterer (hereinafter called “cargo interests”). It is a generally accepted rule that in such event, the carrier/owner must repair the vessel after which it will continue its voyage to the destination port. The dispute will arise in the case that temporary repair of the vessel cannot be done in the short or reasonable term. There are two options for the contract parties in such a case: First, the carrier/owner is entitled to repair the vessel while having the cargo onboard or discharged in the port of refugee, and the cargo interests must wait till the breakdown is rectified at any time, whenever. Second, the carrier/owner will be responsible to charter another vessel and transfer the entirety of cargo to the substitute vessel. In fact, the main question revolves around the duty of carrier/owner to perform transfer of cargo to another vessel. Such operation which is called “trans-shipment” or “transhipment” (in terms of the oil industry it is usually called “ship-to-ship” or “STS”) needs to be done carefully and with due diligence. In fact, the transshipment operation for various cargoes might be different as each cargo requires its own suitable equipment for transfer to another vessel, so this operation is often costly. Moreover, there is a considerable risk of collision between two vessels in particular in bulk carriers. Bulk cargo is also exposed to the shortage and partial loss in the process of transshipment especially during bad weather. Concerning tankers which carry oil and petrochemical products, transshipment, is most probably followed by sea pollution. On the grounds of the above consequences, the owners are afraid of being held responsible for such operation and are reluctant to perform in the relevant disputes. The main argument raised by them is that no regulation has recognized such duty upon their shoulders so any such operation must be done under the auspices of the cargo interests and all costs must be reimbursed by themselves. Unfortunately, not only the international conventions including Hague rules, Hague-Visby Rules, Hamburg rules and Rotterdam rules but also most domestic laws are silent in this regard. The doctrine has yet to analyse the issue and no legal researches was found out in this regard. A qualitative method with the concept of interpretation of data collection has been used in this paper. The source of the data is the analysis of regulations and cases. It is argued in this article that the paramount rule in the maritime law is “the accomplishment of the voyage” by the carrier/owner in view of which, if the voyage can only be finished by transshipment, then the carrier/owner will be responsible to carry out this operation. The duty of carrier/owner to apply “due diligence” will strengthen this reasoning. Any and all costs and expenses will also be on the account pf the owner/carrier, unless the incident is attributable to any cause arising from the cargo interests’ negligence.

Keywords: cargo, STS, transshipment, vessel, voyage

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Authors: Mohammad Zavid Parvez, Manoranjan Paul

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A seizure prediction method is proposed by extracting global features using phase correlation between adjacent epochs for detecting relative changes and local features using fluctuation/deviation within an epoch for determining fine changes of different EEG signals. A classifier and a regularization technique are applied for the reduction of false alarms and improvement of the overall prediction accuracy. The experiments show that the proposed method outperforms the state-of-the-art methods and provides high prediction accuracy (i.e., 97.70%) with low false alarm using EEG signals in different brain locations from a benchmark data set.

Keywords: Epilepsy, seizure, phase correlation, fluctuation, deviation.

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