Search results for: wolof word classification

Authors: Mohammad Jahangeer Warsi

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This is, perhaps, the first linguistic study of Maithili Urdu, a dialect of Urdu language of Indo-Aryan family, spoken by around four million speakers in Darbhanga, Samastipur, Begusarai, Madhubani, and Muzafarpur districts of Bihar. It has the subject–verb–object (SOV) word order and it lacks script and literature. Needless to say, this work is an attempt to document this dialect so that it should contribute to the field of descriptive linguistics. Besides, it is also spoken by majority of Maithili diaspora community. Maithili Urdu does not have its own script or literature, yet it has maintained an oral history of over many centuries. It has contributed to enriching the Maithili, Hindi and Urdu languages and literature very profoundly. Dialects are the contact languages of particular regions, and they have a deep impact on their cultural heritage. Slowly with time, these dialects begin to take shape of languages. The convergence of a dialect into a language is a symbol and pride of the people who speak it. Although, confined to the five districts of northern Bihar, yet highly popular among the natives, it is the primary mode of communication of the local Muslims. The paper will focus on the structure of expressions about Maithili Urdu that include the structure of words, phrases, clauses, and sentences. There are clear differences in linguistic features of Maithili Urdu vis-à-vis Urdu, Maithili and Hindi. Though being a dialect of Urdu, interestingly, there is only one second person pronoun tu and lack of agentive marker –ne. Although being spoken in the vicinity of Hindi, Urdu and Maithili, it undoubtedly has its own linguistic features, of them, verb conjugation is remarkably unique. Because of the oral tradition of this link language, intonation has become significantly prominent. This paper will discuss the morpho-syntactic pattern of Maithili Urdu and will go through a sample text to authenticate the findings.

Keywords: cultural heritage, morpho-syntactic pattern, Maithili Urdu, verb conjugation

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Authors: Matteo Calabrese, Martin Cimmino, Dimos Kapetis, Martina Manfrin, Donato Concilio, Giuseppe Toscano, Giovanni Ciandrini, Giancarlo Paccapeli, Gianluca Giarratana, Marco Siciliano, Andrea Forlani, Alberto Carrotta

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In this paper we describe a machine learning methodology for Predictive Maintenance (PdM) applied on woodworking industrial machines. PdM is a prominent strategy consisting of all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the challenges with PdM approach is to design and develop of an embedded smart system to enable the health status of the machine. The proposed approach allows screening simultaneously multiple connected machines, thus providing real-time monitoring that can be adopted with maintenance management. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime of woodworking machines. The effectiveness of the methodology is demonstrated by testing an independent sample of additional woodworking machines without presenting machine down event.

Keywords: predictive maintenance, machine learning, connected machines, artificial intelligence

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Authors: Thomas Soro, Tim Stott, Brendan O'Rourke

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The construction of artistic reputation has been examined within sociology, philosophy, and economics but, baring a few noteworthy exceptions its discursive aspect has been largely ignored. This is particularly surprising given that contemporary artworks primarily rely on discourse to construct their ontological status. This paper contributes a discourse analytical perspective to the broad body of literature on artistic reputation by providing an understanding of how it is discursively constructed within the institutional context of online contemporary art magazines. This paper uses corpora compiled from the websites of e-flux and ARTnews, two leading online contemporary art magazines, to examine how these organisations discursively construct the reputation of artists. By constructing word-sketches of the term 'Artist', the paper identified the most significant modifiers attributed to artists and the most significant verbs which have 'artist' as an object or subject. The most significant results were analysed through concordances and demonstrated a somewhat surprising lack of evaluative representation. To examine this feature more closely, the paper then analysed three announcement texts from e-flux’s site and three review texts from ARTnews' site, comparing the use of modifiers and verbs in the representation of artists, artworks, and institutions. The results of this analysis support the corpus findings, suggesting that artists are rarely represented in evaluative terms. Based on the relatively high frequency of evaluation in the representation of artworks and institutions, these results suggest that there may be discursive norms at work in the field of online contemporary art magazines which regulate the use of verbs and modifiers in the evaluation of artists.

Keywords: contemporary art, corpus linguistics, critical discourse analysis, symbolic capital

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Authors: Jacqueline Żammit

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Recent research indicates that the utilization of right-brain strategies holds significant implications for the acquisition of language skills. Nevertheless, the utilization of visual culture as a means to stimulate these strategies and amplify language retention among adults engaging in second language (L2) learning remains a relatively unexplored area. This investigation delves into the impact of visual culture on activating right-brain processes during the initial stages of language acquisition, particularly in the context of teaching Maltese as a second language (ML2) to adult learners. By employing a qualitative research approach, this study convenes a focus group comprising twenty-seven educators to delve into a range of visual culture techniques integrated within language instruction. The collected data is subjected to thematic analysis using NVivo software. The findings underscore a variety of impactful visual culture techniques, encompassing activities such as drawing, sketching, interactive matching games, orthographic mapping, memory palace strategies, wordless picture books, picture-centered learning methodologies, infographics, Face Memory Game, Spot the Difference, Word Search Puzzles, the Hidden Object Game, educational videos, the Shadow Matching technique, Find the Differences exercises, and color-coded methodologies. These identified techniques hold potential for application within ML2 classes for adult learners. Consequently, this study not only provides insights into optimizing language learning through specific visual culture strategies but also furnishes practical recommendations for enhancing language competencies and skills.

Keywords: visual culture, right-brain strategies, second language acquisition, maltese as a second language, visual aids, language-based activities

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Authors: Ahmed Abdulla Ashlam, Atta Badii, Frederic Stahl

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In recent years, SQL injection attacks have been identified as being prevalent against web applications. They affect network security and user data, which leads to a considerable loss of money and data every year. This paper presents the use of classification algorithms in machine learning using a method to classify the login data filtering inputs into "SQLi" or "Non-SQLi,” thus increasing the reliability and accuracy of results in terms of deciding whether an operation is an attack or a valid operation. A method Web-App auto-generated twin data structure replication. Shielding against SQLi attacks (WebAppShield) that verifies all users and prevents attackers (SQLi attacks) from entering and or accessing the database, which the machine learning module predicts as "Non-SQLi" has been developed. A special login form has been developed with a special instance of data validation; this verification process secures the web application from its early stages. The system has been tested and validated, up to 99% of SQLi attacks have been prevented.

Keywords: SQL injection, attacks, web application, accuracy, database

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Authors: K. Tejasri, K. Suvarna Vani, S. Prathyusha, S. Ramya

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Proteins are chained sequences of amino acids which are brought together by the peptide bonds. Many varying formations of the chains are possible due to multiple combinations of amino acids and rotation in numerous positions along the chain. Protein structure prediction is one of the crucial goals worked towards by the members of bioinformatics and theoretical chemistry backgrounds. Among the four different structure levels in proteins, we emphasize mainly the secondary level structure. Generally, the secondary protein basically comprises alpha-helix and beta-sheets. Multi-class classification problem of data with disparity is truly a challenge to overcome and has to be addressed for the beta strands. Imbalanced data distribution constitutes a couple of the classes of data having very limited training samples collated with other classes. The secondary structure data is extracted from the protein primary sequence, and the beta-strands are predicted using suitable machine learning algorithms.

Keywords: proteins, secondary structure elements, beta-sheets, beta-strands, alpha-helices, machine learning algorithms

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Authors: Vishnu Goyal, Basant Agarwal

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Sentiment analysis research provides methods for identifying the people’s opinion written in blogs, reviews, social networking websites etc. Sentiment analysis is to understand what opinion people have about any given entity, object or thing. Sentiment analysis research can be broadly categorised into three types of approaches i.e. semantic orientation, machine learning and lexicon based approaches. Feature selection methods improve the performance of the machine learning algorithms by eliminating the irrelevant features. Information gain feature selection method has been considered best method for sentiment analysis; however, it has the drawback of selection of threshold. Therefore, in this paper, we propose a hybrid feature selection methods comprising of information gain and proposed feature selection method. Initially, features are selected using Information Gain (IG) and further more noisy features are eliminated using the proposed feature selection method. Experimental results show the efficiency of the proposed feature selection methods.

Keywords: feature selection, sentiment analysis, hybrid feature selection

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Authors: Vineetha Bettaiah, Heggere S. Ranganath

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This paper presents a Hierarchical Piecewise Linear Approximation (HPLA) for the representation of time series data in which the time series is treated as a curve in the time-amplitude image space. The curve is partitioned into segments by choosing perceptually important points as break points. Each segment between adjacent break points is recursively partitioned into two segments at the best point or midpoint until the error between the approximating line and the original curve becomes less than a pre-specified threshold. The HPLA representation achieves dimensionality reduction while preserving prominent local features and general shape of time series. The representation permits course-fine processing at different levels of details, allows flexible definition of similarity based on mathematical measures or general time series shape, and supports time series data mining operations including query by content, clustering and classification based on whole or subsequence similarity.

Keywords: data mining, dimensionality reduction, piecewise linear representation, time series representation

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Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

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Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

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Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: color space, neural network, random forest, skin detection, statistical feature

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Authors: Nor-Edine Abriak, Mahfoud Benzerzour, Mouhamadou Amar, Abdeljalil Zri

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In this work, firstly we have studied the potential of raw sediments and sediments treated with lime or cement for use in a foundation layer and the base layer of a roadway. Secondly, we have examined mineral changes caused by the addition of lime or cement in order to explain the mechanical performance of stabilized sediments. After determining the amount of lime and cement required stabilizing the sediments, the compaction characteristics and Immediate Bearing Capacity (IBI) were studied using the Modified Proctor method. Then, the evolution of the three parameters, which are optimum water content, maximum dry density and IBI, were determined. Mechanical performances can be evaluated through resistance to compression, resistance under traction and the elasticity modulus. The resistances of the formulations treated with ROLAC®645 increase with the amount of ROLAC®645. Traction resistance and the elastic modulus were used to evaluate the potential of the formulations as road construction materials using the classification diagram. The results show that all the other formulations with ROLAC®645 can be used in subgrades and foundation layers for roads.

Keywords: sediment, lime, cement, roadway

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Authors: Vivek Ganesh

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Tropical cyclones are some of the most damaging events. They occur in yearly cycles and affect the coastal population with three dangerous effects: heavy rain, strong wind and storm surge. In order to estimate the area and the population affected by a cyclone, all the three types of physical impacts must be taken into account. Storm surge is an abnormal rise of water above the astronomical tides, generated by strong winds and drop in the atmospheric pressure. The main aim of the study is to identify the impact by comparing three different months data. The technique used here is NDVI classification technique for change detection and other techniques like storm surge modelling for finding the tide height. Current study emphasize on recent very severe cyclonic storm Hud Hud of category 3 hurricane which had developed on 8 October 2014 and hit the coast on 12 October 2014 which caused significant changes on land and coast of Visakhapatnam, Andhra Pradesh. In the present study, we have used Remote Sensing and GIS tools for investigating and quantifying the changes in vegetation and settlement.

Keywords: inundation map, NDVI map, storm tide map, track map

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Authors: Ovett Nwosimiri

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African tradition and what it entails are the content of African concepts of knowledge. The study of African concepts of knowledge is also known as African epistemology. In other words, African epistemology is a branch of African philosophy that deals with knowledge. This branch of African philosophy engages with the nature and concept of knowledge, the ways in which knowledge can be gained, the ways in which one can justify an epistemic claim or validate a knowledge claim and the limit of human knowledge, etc. The protagonists of African epistemology based their argument for a distinctive or unique African epistemology on the premise or proposition “that each race is endowed with a distinctive nature and embodies in its civilization a particular spirit”. All human beings share some certain basic values and perceptions irrespective of where you come from, and this idea actually fosters some forms of interaction between people from different nationality. Africans like other people share in some certain values, perceptions, and interaction with the rest of the world. These basic values, perceptions, and interaction that Africans share with the rest of the word prompted African people to attempt to “modernize” their societies or develop some forms of their tradition in harmony with the ethos of the contemporary world. Based on the above ideas, it would be interesting to investigate if such (African) epistemology is still unique. The advocates of African epistemology focus on the externalist notion of justification and neglect the idea that both the internalist and externalist notion of justification are needed in order to arrive at a coherent and well-founded account of epistemic justification. Thus, this paper will critically examine the claims that there is a unique African epistemology (a mode of knowing that is peculiar to Africans, and that African mode of knowing is social, monism and situated notion of knowledge), and the grounds for justifying beliefs and epistemic claims.

Keywords: internalist, externalist, knowledge, justification

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Authors: Akshat Kumar, Vidushi

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This paper identifies 27 KOIs, 26 of which are currently classified as candidates and one as false positives that have a high probability of being confirmed. For this purpose, 11 machine learning algorithms were implemented on the cumulative kepler dataset sourced from the NASA exoplanet archive; it was observed that the best-performing model was HistGradientBoosting and XGBoost with a test accuracy of 93.5%, and the lowest-performing model was Gaussian NB with a test accuracy of 54%, to test model performance F1, cross-validation score and RUC curve was calculated. Based on the learned models, the significant characteristics for confirm exoplanets were identified, putting emphasis on the object’s transit and stellar properties; these characteristics were namely koi_count, koi_prad, koi_period, koi_dor, koi_ror, and koi_smass, which were later considered to filter out the potential KOIs. The paper also calculates the Earth similarity index based on the planetary radius and equilibrium temperature for each KOI identified to aid in their classification.

Keywords: Kepler objects of interest, exoplanets, space exploration, machine learning, earth similarity index, transit photometry

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Authors: Snezhana G. Gocheva-Ilieva, Maya P. Stoimenova

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Ambient air pollution with fine particulate matter (PM10) is a systematic permanent problem in many countries around the world. The accumulation of a large number of measurements of both the PM10 concentrations and the accompanying atmospheric factors allow for their statistical modeling to detect dependencies and forecast future pollution. This study applies the classification and regression trees (CART) method for building and analyzing PM10 models. In the empirical study, average daily air data for the city of Pleven, Bulgaria for a period of 5 years are used. Predictors in the models are seven meteorological variables, time variables, as well as lagged PM10 variables and some lagged meteorological variables, delayed by 1 or 2 days with respect to the initial time series, respectively. The degree of influence of the predictors in the models is determined. The selected best CART models are used to forecast future PM10 concentrations for two days ahead after the last date in the modeling procedure and show very accurate results.

Keywords: cross-validation, decision tree, lagged variables, short-term forecasting

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Authors: Manal Mohammed Hisham Said Najjar

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The Arab Grammarians shed light on the redundant kana (was) and gave it a considerable attention. However, their considerations and interpretations pertaining to using this verb varied: is it used to determine tense? Or used for further emphasis or for another function? Does it have a syntactic function? Morphologically, could it be used in other forms than the past? In addition, Arab Grammarians discussed the possibility of using kana to locate itself in between the syntactic constructs of a sentence, a phrase, or a collocation. Others questioned its position whether it is in initial or final. This study found out that the redundant kana (was) is cited in Quran and was used by the Arabs in their speech and poetry. This redundant kana, whether used in initial position or in a final position, or in between the constructs of a sentence, a phrase, or a collocation, implies pragmatic meanings intended by the speaker or the poet to serve different functions, such as to indicate the past tense, to provide emphasis, and to refer to the continuity of the effect and meaning of a verb or adjective. The study concludes that this verb kana can be utilized in different contexts to achieve a specific effect as did the old Arabs who used it to add specific shades of meanings. Kana as a redundant word could be added to further highlight the meaning aimed at in a specific utterance. In addition, this verb can be used in both the past and the present morphological form; and its availability in an utterance could be functional and could not be. In other words, the study found out that the redundant kana can be used in various positions in an utterance, initial, final, or in between a syntactic structure, provided that this use is pragmatically functional. In conclusion, this paper seeks to invite the scholars of the Arabic language to coin a new term which is the “pragmatic kana” to replace the term “kana alzae’da (redundant kana)” which might mean that its use is redundant and void of significance – a fact that is illogical due to its recurrent use in the Holy Quran. NOTE: Please take this study not the other one (sent by mistake) and titled kana alnaqisa

Keywords: redundan, kana, grammarians, quran

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Authors: Sara Tusian, Zahra Salehi Motaahed, Narges Sajjadie, Nikoo Dialame

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One of the methods which have frequently been used in Quran is the “question”. In the Quran, in addition to the content, methods are also important. Using analysis-interpretation method, the present study has investigated Quranic questions, and extracted its functions from educational perspective. In so doing, it has first investigated all the questions in Quran and then taking the three-stage classification of education into account, it has offered question functions. The results obtained from this study suggest that question functions in Quran are presented in three categories: the preparation stage (including preparation of the audience, revising the insights, and internal Evolution); main body (including the granting the insight, and elimination of intellectual negligence and the question of innate and logical axioms, the introducting of the realm of thinking, creating emotional arousal and alleged in the claim) and the third stage as modification and revision (including invitation to move in the framework of tasks using the individual beliefs to reveal the contradictions and, Error detection and contribution to change the function) that each of which has a special role in the education process.

Keywords: education, question, Quranic questions, Quran

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Authors: Chika Catherine Ayogu

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Rehabilitation plays an important and integral part in the life of roadway rehabilitation management system. It is a systematic method for inspection and rating the roadway condition in a given area. The system performs a cost effective analysis of various maintenance and rehabilitation strategies. Finally the system prioritize and recommend roadway rehabilitation and maintenance to maximize results within a given budget amount. During execution of maintenance activity, the system also tracks labour, materials, equipment and cost for activities performed. The system implements physical assessment field inspection and rating of each street segment which is then entered into a database. The information is analyzed using a software, and provide recommendations and project future conditions. The roadway management system provides a deterioration curve for each segment based on input then assigns the most cost-effective maintenance strategy based on conditions, surface type and functional classification, and available budget. This paper investigates the roadway management system and its capabilities to assist in applying the right treatment to the right roadway at the right time so that expected service life of the roadway is extended as long as possible with acceptable cost.

Keywords: effectiveness, rehabilitation, roadway, software system

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Authors: Priya Arora, Ashutosh Mishra

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Gene identification, towards the pursuit of mutated genes, leading to Parkinson’s disease, puts forward a challenge towards proactive cure of the disorder itself. Computational analysis is an effective technique for exploring genes in the form of protein sequences, as the theoretical and manual analysis is infeasible. The limitations and effectiveness of a particular computational method are entirely dependent on the previous data that is available for disease identification. The article presents a sequence-based classification method for the identification of genes responsible for Parkinson’s disease. During the initiation phase, the physicochemical properties of amino acids transform protein sequences into a feature vector. The second phase of the method employs Jaccard distances to select negative genes from the candidate population. The third phase involves artificial neural networks for making final predictions. The proposed approach is compared with the state of art methods on the basis of F-measure. The results confirm and estimate the efficiency of the method.

Keywords: disease gene identification, Parkinson’s disease, physicochemical properties of amino acid, protein sequences

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Authors: Ahmad Al Aboudi

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The Department of Archaeology at King Saud University conduct a long Term excavations since 2004 at the archaeological site of (Qurh) in Al-Ula area. The history of the site goes back to the eighth century AD. The main aim of the excavations is the training of the students on the archaeological field work associated with the scientific skills of exploring, surveying, classifying, documentations and other necessary in the field archaeology. During the 12th Season of Excavations, an area of 20 × 40 m2 of the site was excavated. The depth of the excavating the site was reached to 2-3 m. Many of the architectural features of a residential area in the northern part of the site were excavated this season. Circular walls made of mud-brick and a brick column drums and tiles made of clay were revealed this season. Additionally, lots of findings such as Gemstones, jars, ceramic plates, metal, glass, and fabric, as well as some jewelers and coins were discovered. This paper will deal with the main results of this field project including the architectural features and phenomena and their interpretations, the classification of excavated material culture remains and stratigraphy.

Keywords: Islamic architecture, Islamic art, excavations, early Islamic city

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Authors: R. Oleko, A. Saraceni

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The aim of this research is to provide a rigorous evaluation of the existing academic productivity in relation to value proposition and creation in networked environments. Bibliometrics is a vigorous approach used to structure existing literature in an objective and reliable manner. To that aim, a thorough bibliometric analysis was performed in order to assess the large volume of the information encountered in a structured and reliable manner. A clear distinction between networks and service networks was considered indispensable in order to capture the effects of each network’s type properties on value creation processes. Via the use of bibliometric parameters, this review was able to capture the state-of-the-art in both value proposition and value creation consecutively. The results provide a rigorous assessment of the annual scientific production, the most influential journals, and the leading corresponding author countries. By means of citation analysis, the most frequently cited manuscripts and countries for each network type were identified. Moreover, by means of co-citation analysis, existing collaborative patterns were detected through the creation of reference co-citation networks and country collaboration networks. Co-word analysis was also performed in order to provide an overview of the conceptual structure in both networks and service networks. The acquired results provide a rigorous and systematic assessment of the existing scientific output in networked settings. As such, they positively contribute to a better understanding of the distinct impact of service networks on value proposition and value creation when compared to regular networks. The implications derived can serve as a guide for informed decision-making by practitioners during network formation and provide a structured evaluation that can stand as a basis for future research in the field.

Keywords: bibliometrics, co-citation analysis, networks, service networks, value creation, value proposition

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Authors: Chen Jun

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Antonia Susan Byatt’s Possession: A Romance has been misread as a postmodern pastiche novel since its publication because there are epics, epigraphs, lyrics, fairy tales, epistles, and even critical articles swollen in this work. The word ‘pastiche’ suggests messy, disorganized, and chaotic, which buries its artistic excellence while overlooking its subtitle, A Romance. The center of romance is the quest that the hero sets forth to conquer the adversity, hardship, and danger to accomplish a task to prove his identity or social worth. This paper argues that Byatt’s Possession is not a postmodern pastiche novel but rather a postmodern romance in which the characters in the academic world set forth their quest into the Victorian literary past that is nostalgically identified by Byatt as the Golden Age of English literature. In doing so, these five following issues are addressed: first, the origin of the protagonist Roland, and consequently, the nature of his quest; second, the central image of the dragon created by the fictional Victorian poet Henry Ash; third, Melusine as an image of female serpent created by the fictional Victorian poet Christabel LaMotte; fourth, the images of the two ladies; last, the image of water that links the dragon and the serpent. In Possession, the past is reinvented not as an unfortunate fall but as a Golden Age presented in the imaginative academic adventure. The dragon, a stereotypical symbol of evil, becomes the symbol of life in Byatt’s work, which parallels with the image of the mythical phoenix that can resurrect from its own ash. At the same time, the phoenix symbolizes Byatt’s efforts to revive the Victorian poetic art that is supposed to be dead in the post-capitalism society when the novel is the dominating literary genre and poetry becomes the minority. The fictional Victorian poet Ash is in fact Byatt’s own poetic mask through which she breathes life into the lost poetic artistry in the postmodern era.

Keywords: Byatt, possession, postmodern romance, literary past

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Authors: Tegan H. Emerson, Colin C. Olson, George Stantchev, Jason A. Edelberg, Michael Wilson

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Detecting small targets at range is difficult because there is not enough spatial information present in an image sub-region containing the target to use correlation-based methods to differentiate it from dynamic confusers present in the scene. Moreover, this lack of spatial information also disqualifies the use of most state-of-the-art deep learning image-based classifiers. Here, we use characteristics of target tracks extracted from video sequences as data from which to derive distinguishing topological features that help robustly differentiate targets of interest from confusers. In particular, we calculate persistent homology from time-delayed embeddings of dynamic statistics calculated from motion tracks extracted from a wide field-of-view video stream. In short, we use topological methods to extract features related to target motion dynamics that are useful for classification and disambiguation and show that small targets can be detected at range with high probability.

Keywords: motion tracks, persistence images, time-delay embedding, topological data analysis

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Authors: Ashkan Zakaryazad, Ekrem Duman

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A typical classification technique ranks the instances in a data set according to the likelihood of belonging to one (positive) class. A credit card (CC) fraud detection model ranks the transactions in terms of probability of being fraud. In fact, this approach is often criticized, because firms do not care about fraud probability but about the profitability or costliness of detecting a fraudulent transaction. The key contribution in this study is to focus on the profit maximization in the model building step. The artificial neural network proposed in this study works based on profit maximization instead of minimizing the error of prediction. Moreover, some studies have shown that the back propagation algorithm, similar to other gradient–based algorithms, usually gets trapped in local optima and swarm-based algorithms are more successful in this respect. In this study, we train our profit maximization ANN using the Migrating Birds optimization (MBO) which is introduced to literature recently.

Keywords: neural network, profit-based neural network, sum of squared errors (SSE), MBO, gradient descent

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Authors: Y. H. Wu, Ji-Yuan Lin, Yu-Ming Liou

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This study aims to set up the landslide susceptibility map of County Route 89 at Ren-Ai Township in Nantou County using the Instability Index Method and Logistic regression. Seven susceptibility factors including Slope Angle, Aspect, Elevation, Distance to fold, Distance to River, Distance to Road and Accumulated Rainfall were obtained by GIS based on the Typhoon Toraji landslide area identified by Industrial Technology Research Institute in 2001. To calculate the landslide percentage of each factor and acquire the weight and grade the grid by means of Instability Index Method. In this study, landslide susceptibility can be classified into four grades: high, medium high, medium low and low, in order to determine the advantages and disadvantages of the two models. The precision of this model is verified by classification error matrix and SRC curve. These results suggest that the logistic regression model is a preferred method than instability index in the assessment of landslide susceptibility. It is suitable for the landslide prediction and precaution in this area in the future.

Keywords: instability index method, logistic regression, landslide susceptibility, SRC curve

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Authors: Mikhail Zarechnev, Bora I. Kumova

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A syllogism is a deductive inference scheme used to derive a conclusion from a set of premises. In a categorical syllogisms, there are only two premises and every premise and conclusion is given in form of a quantified relationship between two objects. The different order of objects in premises give classification known as figures. We have shown that the ordered combinations of 3 generalized quantifiers with certain figure provide in total of 108 syllogistic moods which can be considered as different inference rules. The classical syllogistic system allows to model human thought and reasoning with syllogistic structures always attracted the attention of cognitive scientists. Since automated reasoning is considered as part of learning subsystem of AI agents, syllogistic system can be applied for this approach. Another application of syllogistic system is related to inference mechanisms on the Semantic Web applications. In this paper we proposed the mathematical model and algorithm for syllogistic reasoning. Also the model of iterative syllogistic reasoning in case of continuous flows of incoming data based on case–based reasoning and possible applications of proposed system were discussed.

Keywords: categorical syllogism, case-based reasoning, cognitive architecture, inference on the semantic web, syllogistic reasoning

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Authors: Jamal Ahmed Hama Kareem, Noraini Abu Talib

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The purpose of this paper is to explore the literature on 5S and Total Productive Maintenance (TPM) and the benefits that are to be derived from their implementation. It also seeks to highlight the main phases for implementing both the 5S and the TPM successfully, along with highlighting aspects that are needed for successful implementation of these two techniques simultaneously in the contemporary manufacturing scenario. The literature on classification of 5S and TPM has so far been very limited. The paper reviews a large number of papers in this field and presents the overview of several of implementation practices of 5S and TPM, and the benefits that can be achieved by the implementation of 5S and TPM as a one system by industrial organizations globally. The paper systematically categorizes the published literature and reveals important issues that influence the successful implementation of 5S and TPM in organizations to improve production effectiveness for competitiveness. Further, the paper also highlights various phases suggested by researchers and practitioners, which ensure smooth and effective implementation of the 5S and TPM in industrial organizations. In the end, study puts forth propositions based on the model of the study after extensive review of literature. The paper will be useful to researchers, maintenance professionals and other concerned officials with improving the performance of production processes effectiveness in industrial organizations.

Keywords: 5S, Total Productive Maintenance (TPM), phases of implementation of 5S and TPM, industrial organizations

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Authors: Sean Paulsen, Michael Casey

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In this work we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training

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

Abstract:

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: Heba Elbibas, Esra Gnijeewa, Zedan Hatush

Abstract:

This paper presents research on occupational safety in construction projects, where the importance of safety management in projects was studied, including the preparation of a safety plan and program for each project and the identification of the responsibilities of each party to the contract. The research consists of two parts: 1-Field visits: which were field visits to three construction projects, including building projects, road projects, and tower installation. The safety level of these projects was evaluated through a checklist that includes the most important safety elements in terms of the application of these items in the projects. 2-Preparation of a questionnaire: which included supervisors and engineers and aimed to determine the level of awareness and commitment of different project categories to safety standards. The results showed the following: i) There is a moderate occupational safety policy. ii) The preparation and storage of maintenance reports are not fully complied with. iii) There is a moderate level of training on occupational safety for project workers. iv) The company does not impose penalties on safety violators permanently. v) There is a moderate policy for equipment and machinery safety. vi) Self-injuries occur due to (fatigue, lack of attention, deliberate error, and emotional factors), with a rate of 82.4%.

Keywords: management, safety, occupational safety, classification

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