Search results for: casual inference

Authors: Edoardo Schinco

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Studying the Marxist intellectual tradition, it is possible to verify that there were numerous cases of philosophical regression, in which the important achievements of detailed studies have been replaced by naïve ideas and previous misunderstandings: one of most important example of this tendency is related to the question of ideology. According to a common Enlightenment approach, the ideology is essentially not a reality, i.e., a factor capable of having an effect on the reality itself; in other words, the ideology is a mere error without specific historical meaning, which is only due to ignorance or inability of subjects to understand the truth. From this point of view, the consequent and immediate practice against every form of ideology are the rational dialogue, the reasoning based on common sense, in order to dispel the obscurity of ignorance through the light of pure reason. The limits of this philosophical orientation are however both theoretical and practical: on the one hand, the Enlightenment criticism of ideology is not an historicistic thought, since it cannot grasp the inner connection that ties an historical context and its peculiar ideology together; moreover, on the other hand, when the Enlightenment approach fails to release people from their illusions (e.g., when the ideology persists, despite the explanation of its illusoriness), it usually becomes a racist or elitarian thought. Unlike this first conception of ideology, Gramsci attempts to recover Marx’s original thought and to valorize its dialectical methodology with respect to the reality of ideology. As Marx suggests, the ideology – in negative meaning – is surely an error, a misleading knowledge, which aims to defense the current state of things and to conceal social, political or moral contradictions; but, that is precisely why the ideological error is not casual: every ideology mediately roots in a particular material context, from which it takes its reason being. Gramsci avoids, however, any mechanistic interpretation of Marx and, for this reason; he underlines the dialectic relation that exists between material base and ideological superstructure; in this way, a specific ideology is not only a passive product of base but also an active factor that reacts on the base itself and modifies it. Therefore, there is a considerable revaluation of ideology’s role in maintenance of status quo and the consequent thematization of both ideology as objective force, active in history, and ideology as cultural hegemony of ruling class on subordinate groups. Among the Marxists, the French philosopher Louis Althusser also gives his contribution to this crucial question; as follower of Gramsci’s thought, he develops the idea of ideology as an objective force through the notions of Repressive State Apparatus (RSA) and Ideological State Apparatuses (ISA). In addition to this, his philosophy is characterized by the presence of structuralist elements, which must be studied, since they deeply change the theoretical foundation of his Marxist thought.

Keywords: Althusser, enlightenment, Gramsci, ideology

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Authors: Sharmistha Chanda, Anindita Chaudhuri

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This exploratory study highlights the psychological aspects of women's empowerment to find the importance of the psychological dimension of empowerment, such as; meaning, competence, self-determination, impact, and assumption, especially in the weaker marginalized section of women. A large proportion of rural, suburban, and urban poor survive by working in unorganized sectors of metropolitan cities. Relative Poverty and lack of employment in rural areas and small towns drive many people to the metropolitan city for work and livelihood. Women working in that field remain unrecognized as people of low socio-economic status. They are usually willing to do domestic work as daily wage workers, single wage earners, street vendors, family businesses like agricultural activities, domestic workers, and self-employed. Usually, these women accept such jobs because they do not have such an opportunity as they lack the basic level of education that is required for better-paid jobs. The unorganized sector, on the other hand, has no such clear-cut employer-employee relationships and lacks most forms of social protection. Having no fixed employer, these workers are casual, contractual, migrant, home-based, own-account workers who attempt to earn a living from whatever meager assets and skills they possess. Women have become more empowered both financially and individually through small-scale business ownership or entrepreneurship development and in household-based work. In-depth interviews have been done with 10 participants in order to understand their living styles, habits, self-identity, and empowerment in their society in order to evaluate the key challenges that they may face following by qualitative research approach. Transcription has been done from the collected data. The three-layer coding technique guides the data analysis process, encompassing – open coding, axial coding, and selective coding. Women’s Entrepreneurship is one of the foremost concerns as the Government, and non-government institutions are readily serving this domain with the primary objectives of promoting self-employment opportunities in general and empowering women in specific. Thus, despite hardship and unrecognition unorganized sector provides a huge array of opportunities for rural and sub-urban poor to earn. Also, the upper section of society tends to depend on this working force. This study gave an idea about the well-being, and meaning in life, life satisfaction on the basis of their lived experience.

Keywords: marginalized women, psychological empowerment, relative poverty, and unorganized sector.

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Authors: Sammy Kibor, Filip Huyghe, Marc Kochzius, James Kairo

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Goldstripe Sardinella, Sardinella gibbosa, (Bleeker, 1849) is a commercially and ecologically important small pelagic fish common in the Western Indian Ocean region. The present study aimed to assess genetic diversity and population structure of the species in the Kenya-Tanzania transboundary area using mtDNA and msDNA markers. Some 630 bp sequence in the mitochondrial DNA (mtDNA) Cytochrome C Oxidase I (COI) and five polymorphic microsatellite DNA loci were analyzed. Fin clips of 309 individuals from eight locations within the transboundary area were collected between July and December 2018. The S. gibbosa individuals from the different locations were distinguishable from one another based on the mtDNA variation, as demonstrated with a neighbor-joining tree and minimum spanning network analysis. None of the identified 22 haplotypes were shared between Kenya and Tanzania. Gene diversity per locus was relatively high (0.271-0.751), highest Fis was 0.391. The structure analysis, discriminant analysis of Principal component (DAPC) and the pair-wise (FST = 0.136 P < 0.001) values after Bonferroni correction using five microsatellite loci provided clear inference on genetic differentiation and thus evidence of population structure of S. gibbosa along the Kenya-Tanzania coast. This study shows a high level of genetic diversity and the presence of population structure (Φst =0.078 P < 0.001) resulting to the existence of four populations giving a clear indication of minimum gene flow among the population. This information has application in the designing of marine protected areas, an important tool for marine conservation.

Keywords: marine connectivity, microsatellites, population genetics, transboundary

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Authors: Dhanuja S. Patil, Sanjay B. Waykar

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Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

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Authors: Alexandros Lioulemes, Michail Theofanidis, Varun Kanal, Konstantinos Tsiakas, Maher Abujelala, Chris Collander, William B. Townsend, Angie Boisselle, Fillia Makedon

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This paper presents a home-based robot-rehabilitation instrument, called ”MAGNI Dynamics”, that utilized a vision-based kinematic/dynamic module and an adaptive haptic feedback controller. The system is expected to provide personalized rehabilitation by adjusting its resistive and supportive behavior according to a fuzzy intelligence controller that acts as an inference system, which correlates the user’s performance to different stiffness factors. The vision module uses the Kinect’s skeletal tracking to monitor the user’s effort in an unobtrusive and safe way, by estimating the torque that affects the user’s arm. The system’s torque estimations are justified by capturing electromyographic data from primitive hand motions (Shoulder Abduction and Shoulder Forward Flexion). Moreover, we present and analyze how the Barrett WAM generates a force-field with a haptic controller to support or challenge the users. Experiments show that by shifting the proportional value, that corresponds to different stiffness factors of the haptic path, can potentially help the user to improve his/her motor skills. Finally, potential areas for future research are discussed, that address how a rehabilitation robotic framework may include multisensing data, to improve the user’s recovery process.

Keywords: human-robot interaction, kinect, kinematics, dynamics, haptic control, rehabilitation robotics, artificial intelligence

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Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

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Authors: E. Rama Devi Jothilingam

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Diabetes mellitus is now one of the most common non communicable diseases globally. India leads the world with largest number of diabetic subjects earning the title "diabetes capital of the world". In order to reduce the mortality rate, a fuzzy expert system is designed to predict the severity of cardiac and renal problems of diabetic patients using fuzzy logic. Since uncertainty is inherent in medicine, fuzzy logic is used in this research work to remove the inherent fuzziness of linguistic concepts and uncertain status in diabetes mellitus which is the prime cause for the cardiac arrest and renal failure. In this work, the controllable risk factors "blood sugar, insulin, ketones, lipids, obesity, blood pressure and protein/creatinine ratio" are considered as input parameters and the "the stages of cardiac" (SOC)" and the stages of renal" (SORD) are considered as the output parameters. The triangular membership functions are used to model the input and output parameters. The rule base is constructed for the proposed expert system based on the knowledge from the medical experts. Mamdani inference engine is used to infer the information based on the rule base to take major decision in diagnosis. Mean of maximum is used to get a non fuzzy control action that best represent possibility distribution of an inferred fuzzy control action. The proposed system also classifies the patients with high risk and low risk using fuzzy c means clustering techniques so that the patients with high risk are treated immediately. The system is validated with Matlab and is used as a tracking system with accuracy and robustness.

Keywords: Diabetes mellitus, fuzzy expert system, Mamdani, MATLAB

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Authors: Mohsen Masoomi, Fazel Asadi Amjad, Monireh Arvin

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According to Naturalistic principles, human destiny in the form of blind chance and determinism, entraps the individual, so man is a defenceless creature unable to escape from the ruthless paws of a stoical universe. In Naturalism; nonetheless, melodrama mirrors a conscious alternative with a peculiar function. A typical American Naturalistic character thus cannot be a subject for social criticism of American society since they are not victims of the ongoing virtual slavery, capitalist system, nor of a ruined milieu, but of their own volition, and more importantly, their character frailty. Through a Postmodern viewpoint, each Naturalistic work can encompass some entropic trends and changes culminating in an entire failure and devastation. Frank Norris in McTeague displays the futile struggles of ordinary men and how they end up brutes. McTeague encompasses intoxication, abuse, violation, and ruthless homicides. Norris’ depictions of the falling individual as a demon represent the entropic dimension of Naturalistic novels. McTeague’s defeat is somewhat his own fault, the result of his own blunders and resolution, not the result of sheer accident. Throughout the novel, each character is a kind of insane quester indicating McTeague’s decadence and, by inference, the decadence of Western civilisation. McTeague seems to designate Norris’ solicitude for a community fabricated by the elements of human negative demeanours and conducts hauling acute symptoms of infectious dehumanisation. The aim of this article is to illustrate how one specific negative human disposition gradually, like a running fire, can spread everywhere and burn everything in itself. The author applies the concept of entropy metaphorically to describe the individual devolutions that necessarily comprise community entropy in McTeague, a dying universe.

Keywords: animal imagery, entropy, Gypsy, melodrama

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Authors: Norsuhana Omar, Amilia Aminuddina Zaiton Zakaria, Raifana Rosa Mohamad Sattar, Kalaivani Chellappan, Mohd Alauddin Mohd Ali, Norizam Salamt, Zanariyah Asmawi, Norliza Saari, Aini Farzana Zulkefli, Nor Anita Megat Mohd. Nordin

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Inflammation plays an important role in the pathogenesis of vascular dysfunction leading to arterial stiffness. Pulse wave velocity (PWV) and augmentation index (AS), as tools for the assessment of vascular damages are widely used and have been shown to predict cardiovascular disease (CVD). C-reactive protein (CRP) is a marker of inflammation. Several studies noted that regular exercise is associated with reduced arterial stiffness. The lack of exercise among Malaysians and the increasing CVD morbidity and mortality among young men are of concern. In Malaysia data on the workplace exercise intervention is scarce. A programme was designed to enable subjects to increase their level of walking as part of their daily work routine and self-monitored by using pedometers. The aim of this study to evaluate the reducing of inflammation by measuring CRP and improvement arterial stiffness measured by carotid femoral PWV (PWVCF) and AI. A total of 70 young men (20 - 40 years) who were sedentary, achieving less than 5,000 steps/day in casual walking with 2 or more cardiovascular risk factors were recruited in Institute of Vocational Skills for Youth (IKBN Hulu Langat). Subjects were randomly assigned to a control (CG) (n=34; no change in walking) and pedometer group (PG) (n=36; minimum target: 8,000 steps/day). The CRP was measured by using immunological method while PWVCF and AI were measured using Vicorder. All parameters were measured at baseline and after 12 weeks. Data for analysis was conducted using Statistical Package of Social Sciences Version 22 (SPSS Inc., Chicago, IL, USA). At post intervention, the CG step counts were similar (4983 ± 366vs 5697 ± 407steps/day). The PG increased step count from 4996 ± 805 to 10,128 ±511 steps/day (P<0.001). The PG showed significant improvement in anthropometric variables and lipid (time and group effect p<0.001). For vascular assessment, the PG showed significantly decreased for time and effect (p<0.001) for PWV (7.21± 0.83 to 6.42 ± 0.89) m/s; AI (11.88± 6.25 to 8.83 ± 3.7) % and CRP (pre= 2.28 ± 3.09, post=1.08± 1.37mg/L). However, no changes were seen in CG. As a conclusion, a pedometer-based walking programme may be an effective strategy for promoting increased daily physical activity which reduces cardiovascular risk markers and thus improve cardiovascular health in terms of inflammation and arterial stiffness. The community intervention for health maintenance has potential to adopt walking as an exercise and adopting vascular fitness index as the performance measuring tools.

Keywords: arterial stiffness, exercise, inflammation, pedometer

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Authors: Ponghyung Lee

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This study seeks to investigate the variations occurring to Korean consonantal variations center around laryngeal features of the concerned sounds, to the exclusion of others. Our fundamental premise is that the weak contrast associated with concerned segments might be held accountable for the oscillation of the status quo of the concerned consonants. What is more, we assume that an array of notions as a measure of communicative efficiency of linguistic units would be significantly influential on triggering those variations. To this end, we have tried to compute the surprisal, entropic contribution, and relative contrastiveness associated with Korean obstruent consonants. What we found therein is that the Information-theoretic perspective is compelling enough to lend support our approach to a considerable extent. That is, the variant realizations, chronologically and stylistically, prove to be profoundly affected by a set of Information-theoretic factors enumerated above. When it comes to the biblical proper names, we use Georgetown University CQP Web-Bible corpora. From the 8 texts (4 from Old Testament and 4 from New Testament) among the total 64 texts, we extracted 199 samples. We address the issue of laryngeal feature variations associated with Korean obstruent consonants under the presumption that the variations stem from the weak contrast among the triad manifestations of laryngeal features. The variants emerge from diverse sources in chronological and stylistic senses: Christianity biblical texts, ordinary casual speech, the shift of loanword adaptation over time, and ideophones. For the purpose of discussing what they are really like from the perspective of Information Theory, it is necessary to closely look at the data. Among them, the massive changes occurring to loanword adaptation of proper nouns during the centennial history of Korean Christianity draw our special attention. We searched 199 types of initially capitalized words among 45,528-word tokens, which account for around 5% of total 901,701-word tokens (12,786-word types) from Georgetown University CQP Web-Bible corpora. We focus on the shift of the laryngeal features incorporated into word-initial consonants, which are available through the two distinct versions of Korean Bible: one came out in the 1960s for the Protestants, and the other was published in the 1990s for the Catholic Church. Of these proper names, we have closely traced the adaptation of plain obstruents, e. g. /b, d, g, s, ʤ/ in the sources. The results show that as much as 41% of the extracted proper names show variations; 37% in terms of aspiration, and 4% in terms of tensing. This study set out in an effort to shed light on the question: to what extent can we attribute the variations occurring to the laryngeal features associated with Korean obstruent consonants to the communicative aspects of linguistic activities? In this vein, the concerted effects of the triad, of surprisal, entropic contribution, and relative contrastiveness can be credited with the ups and downs in the feature specification, despite being contentiousness on the role of surprisal to some extent.

Keywords: entropic contribution, laryngeal feature variation, relative contrastiveness, surprisal

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Authors: Stuart Noel

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In a streetcar Named Desire, Tennessee Williams presents Blanche DuBois, a most complex and intriguing character who often uses prestige language to project the image of an upper-class speaker and to disguise her darker and complicated self. She embodies various fascinating and contrasting characteristics. Like New Orleans (the locale of the play), Blanche represents two opposing images. One image projects that of genteel, Southern charm and beauty, speaking formally and using prestige language and what some linguists refer to as “hypercorrection,” and the other image reveals that of a soiled, deteriorating façade, full of decadence and illusion. Williams said on more than one occasion that Blanche’s use of such language was a direct reflection of her personality and character (as a high school English teacher). Prestige language is an exaggeratedly elevated, pretentious, and oftentimes melodramatic form of one’s language incorporating superstandard or more standard speech than usual in order to project a highly authoritative individual identity. Speech styles carry personal identification meaning not only because they are closely associated with certain social classes but because they tend to be associated with certain conversational contexts. Features which may be considered to be “elaborated” in form (for example, full forms vs. contractions) tend to cluster together in speech registers/styles which are typically considered to be more formal and/or of higher social prestige, such as academic lectures and news broadcasts. Members of higher social classes have access to the elaborated registers which characterize formal writings and pre-planned speech events, such as lectures, while members of lower classes are relegated to using the more economical registers associated with casual, face-to-face conversational interaction, since they do not participate in as many planned speech events as upper-class speakers. Tennessee Williams’s work is characteristically concerned with the conflict between the illusions of an individual and the reality of his/her situation equated with a conflict between truth and beauty. An examination of Blanche DuBois reveals a recurring theme of art and decay and the use of prestige language to reveal artistry in language and to hide a deteriorating self. His graceful and poetic writing personifies her downfall and deterioration. Her loneliness and disappointment are the things so often strongly feared by the sensitive artists and heroes in the world. Hers is also a special and delicate human spirit that is often misunderstood and repressed by society. Blanche is afflicted with a psychic illness growing out of her inability to face the harshness of human existence. She is a sensitive, artistic, and beauty-haunted creature who is avoiding her own humanity while hiding behind her use of prestige language. And she embodies a partial projection of Williams himself.

Keywords: American drama, prestige language, Southern American literature, Tennessee Williams

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Authors: L. Melzerová, T. Janda, M. Šejnoha, J. Šejnoha

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Two finite element (FEM) models are presented in this paper to address the random nature of the response of glued timber structures made of wood segments with variable elastic moduli evaluated from 3600 indentation measurements. This total database served to create the same number of ensembles as was the number of segments in the tested beam. Statistics of these ensembles were then assigned to given segments of beams and the Latin Hypercube Sampling (LHS) method was called to perform 100 simulations resulting into the ensemble of 100 deflections subjected to statistical evaluation. Here, a detailed geometrical arrangement of individual segments in the laminated beam was considered in the construction of two-dimensional FEM model subjected to in four-point bending to comply with the laboratory tests. Since laboratory measurements of local elastic moduli may in general suffer from a significant experimental error, it appears advantageous to exploit the full scale measurements of timber beams, i.e. deflections, to improve their prior distributions with the help of the Bayesian statistical method. This, however, requires an efficient computational model when simulating the laboratory tests numerically. To this end, a simplified model based on Mindlin’s beam theory was established. The improved posterior distributions show that the most significant change of the Young’s modulus distribution takes place in laminae in the most strained zones, i.e. in the top and bottom layers within the beam center region. Posterior distributions of moduli of elasticity were subsequently utilized in the 2D FEM model and compared with the original simulations.

Keywords: Bayesian inference, FEM, four point bending test, laminated timber, parameter estimation, prior and posterior distribution, Young’s modulus

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Authors: Mariam Ismail, Kazeem Rufai, Jeremiah Balogun

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A study was conducted to apply fuzzy logic to the development of a monitoring model for child pornography based on associated risk factors, which can be used by forensic experts or integrated into forensic systems for the early detection of child pornographic activities. A number of methods were adopted in the study, which includes an extensive review of related works was done in order to identify the factors that are associated with child pornography following which they were validated by an expert sex psychologist and guidance counselor, and relevant data was collected. Fuzzy membership functions were used to fuzzify the associated variables identified alongside the risk of the occurrence of child pornography based on the inference rules that were provided by the experts consulted, and the fuzzy logic expert system was simulated using the Fuzzy Logic Toolbox available in the MATLAB Software Release 2016. The results of the study showed that there were 4 categories of risk factors required for assessing the risk of a suspect committing child pornography offenses. The results of the study showed that 2 and 3 triangular membership functions were used to formulate the risk factors based on the 2 and 3 number of labels assigned, respectively. The results of the study showed that 5 fuzzy logic models were formulated such that the first 4 was used to assess the impact of each category on child pornography while the last one takes the 4 outputs from the 4 fuzzy logic models as inputs required for assessing the risk of child pornography. The following conclusion was made; there were factors that were related to personal traits, social traits, history of child pornography crimes, and self-regulatory deficiency traits by the suspects required for the assessment of the risk of child pornography crimes committed by a suspect. Using the values of the identified risk factors selected for this study, the risk of child pornography can be easily assessed from their values in order to determine the likelihood of a suspect perpetuating the crime.

Keywords: fuzzy, membership functions, pornography, risk factors

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Authors: Ayodele James Akinola

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This study investigated the use of English in doctor-patient interaction in a university teaching hospital from a southwestern state in Nigeria with the aim of identifying the role of communication in an L2, patterns of communication, discourse strategies, pragmatic acts, and contexts that shape the interaction. Jacob Mey’s Pragmatic Acts notion complemented with Emanuel and Emanuel’s model of doctor-patient relationship provided the theoretical standpoint. Data comprising 7 audio-recorded doctors-patient interactions were collected from a University Hospital in Oyo state, Nigeria. Interactions involving the use of English language were purposefully selected. These were supplemented with patients’ case notes and interviews conducted with doctors. Transcription was patterned alongside modified Arminen’s notations of conversation analysis. In the study, interaction in English between doctor and patients has the preponderance of direct-translation, code-mixing and switching, Nigerianism and use of cultural worldviews to express medical experience. Irrespective of these, three patterns communication, namely the paternalistic, interpretive, and deliberative were identified. These were exhibited through varying discourse strategies. The paternalistic model reflected slightly casual conversational conventions and registers. These were achieved through the pragmemic activities of situated speech acts, psychological and physical acts, via patients’ quarrel-induced acts, controlled and managed through doctors’ shared situation knowledge. All these produced empathising, pacifying, promising and instructing practs. The patients’ practs were explaining, provoking, associating and greeting in the paternalistic model. The informative model reveals the use of adjacency pairs, formal turn-taking, precise detailing, institutional talks and dialogic strategies. Through the activities of the speech, prosody and physical acts, the practs of declaring, alerting and informing were utilised by doctors, while the patients exploited adapting, requesting and selecting practs. The negotiating conversational strategy of the deliberative model featured in the speech, prosody and physical acts. In this model, practs of suggesting, teaching, persuading and convincing were utilised by the doctors. The patients deployed the practs of questioning, demanding, considering and deciding. The contextual variables revealed that other patterns (such as phatic and informative) are also used and they coalesced in the hospital within the situational and psychological contexts. However, the paternalistic model was predominantly employed by doctors with over six years in practice, while the interpretive, informative and deliberative models were found among registrar and others below six years of medical practice. Doctors’ experience, patients’ peculiarities and shared cultural knowledge influenced doctor-patient communication in the study.

Keywords: pragmatics, communication pattern, doctor-patient interaction, Nigerian hospital situation

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Authors: Nataša Šimić, Ljiljana Gregov, Matilda Nikolić, Andrea Tokić, Ana Proroković

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Moral development takes place in six phases which can be divided in a pre-conventional, conventional and post-conventional level. Moral reasoning, as a key concept of moral development theories, involves a process of discernment/inference in doubtful situations. In research to date, education has proved to be a significant predictor of moral reasoning. The aim of this study was to investigate differences in moral reasoning and Kohlberg's phases of moral development between Croatian adolescents with different levels of education. In Study 1 comparisons between the group of secondary school students aged 17-18 (N=192) and the group of university students aged 21-25 (N=383) were made. Study 2 included comparison between university students group (N=69) and non-students group (N=43) aged from 21 to 24 (these two groups did not differ in age). In both studies, the Croatian Test of Moral Reasoning by Proroković was applied. As a measure of moral reasoning, the Index of Moral Reasoning (IMR) was calculated. This measure has some advantages compared to other measures of moral reasoning, and includes individual assessments of deviations from the ‘optimal profile’. Results of the Study 1 did not show differences in the IMR between secondary school students and university students. Both groups gave higher assessments to the arguments that correspond to higher phases of moral development. However, group differences were found for pre-conventional and conventional phases. As expected, secondary school students gave significantly higher assessments to the arguments that correspond to lower phases of moral development. Results of the Study 2 showed that university students, in relation to non-students, have higher IMR. Respecting to phases of moral development, both groups of participants gave higher assessments to the arguments that correspond to the post-conventional phase. Consistent with expectations and previous findings, results of both studies did not confirm gender differences in moral reasoning.

Keywords: education, index of moral reasoning, Kohlberg's theory of moral development, moral reasoning

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Authors: Partha Sarathi Mondal, Srabani Sanyal

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Different geomorphic agents produce a different landforms pattern. Similarly rivers also have a distinct and diverse landforms pattern. And even, within a river course different and distinct assemblage of landforms i.e. morphological variability are seen. These morphological variability are produced by different river processes. Channel and floodplain morphology helps to interpret river processes. Consequently morphological variability can be used as an important tool for assessing river processes, hydrological connectivity and river health, which will help us to draw inference about river processes and therefore, management of river health. The present study is documented on West Rapti river, a trans-boundary river flowing through Nepal and India, from its source to confluence with Ghaghra river in India. The river shows a significant morphological variability throughout its course. The present study tries to find out factors and processes responsible for the morphological variability of the river and in which way it can be applied in river management practices. For this purpose channel and floodplain morphology of West Rapti river was mapped as accurately as possible and then on the basis of process-form interactions, inferences are drawn to understand factors of morphological variability. The study shows that the valley setting of West Rapti river, in the Himalayan region, is confined and somewhere partly confined whereas, channel of the West Rapti river is single thread in most part of Himalayan region and braided in valley region. In the foothill region valley is unconfined and channel is braided, in middle part channel is meandering and valley is unconfined, whereas, channel is anthropogenically altered in the lower part of the course. Due to this the morphology of West Rapti river is highly diverse. These morphological variability are produced by different geomorphic processes. Therefore, for any river management it is essential to sustain these morphological variability so that the river could not cross the geomorphic threshold and environmental flow of the river along with the biodiversity of riparian region is maintained.

Keywords: channel morphology, environmental flow, floodplain morphology, geomorphic threshold

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Authors: Eman W. Boghdady, A. R. Shehata, M. A. Azem

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Database (DB) security demands permitting authorized users and prohibiting non-authorized users and intruders actions on the DB and the objects inside it. Organizations that are running successfully demand the confidentiality of their DBs. They do not allow the unauthorized access to their data/information. They also demand the assurance that their data is protected against any malicious or accidental modification. DB protection and confidentiality are the security concerns. There are four types of controls to obtain the DB protection, those include: access control, information flow control, inference control, and cryptographic. The cryptographic control is considered as the backbone for DB security, it secures the DB by encryption during storage and communications. Current cryptographic techniques are classified into two types: traditional classical cryptography using standard algorithms (DES, AES, IDEA, etc.) and chaos cryptography using continuous (Chau, Rossler, Lorenz, etc.) or discreet (Logistics, Henon, etc.) algorithms. The important characteristics of chaos are its extreme sensitivity to initial conditions of the system. In this paper, DB-security systems based on chaotic algorithms are described. The Pseudo Random Numbers Generators (PRNGs) from the different chaotic algorithms are implemented using Matlab and their statistical properties are evaluated using NIST and other statistical test-suits. Then, these algorithms are used to secure conventional DB (plaintext), where the statistical properties of the ciphertext are also tested. To increase the complexity of the PRNGs and to let pass all the NIST statistical tests, we propose two hybrid PRNGs: one based on two chaotic Logistic maps and another based on two chaotic Henon maps, where each chaotic algorithm is running side-by-side and starting from random independent initial conditions and parameters (encryption keys). The resulted hybrid PRNGs passed the NIST statistical test suit.

Keywords: algorithms and data structure, DB security, encryption, chaotic algorithms, Matlab, NIST

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Authors: Ting Shen, Spyros Konstantopoulos

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During the past three decades, class size effects have been a focal debate in education. The idea of having smaller class is enormously popular among parents, teachers and policy makers. The rationale of its popularity is that small classroom could provide a better learning environment in which there would be more teacher-pupil interaction and more individualized instruction. This early stage benefits would also have a long-term positive effect. It is a common belief that reducing class size may result in increases in student achievement. However, the empirical evidence about class-size effects from experimental or quasi-experimental studies has been mixed overall. This study sheds more light on whether class size reduction impacts reading achievement in eight European countries: Bulgaria, Germany, Hungary, Italy, Lithuania, Romania, Slovakia, and Slovenia. We examine class size effects on reading achievement using national probability samples of fourth graders. All eight European countries had participated in the Progress in International Reading Literacy Study (PIRLS) in 2001, 2006 and 2011. Methodologically, the quasi-experimental method of instrumental variables (IV) has been utilized to facilitate causal inference of class size effects. Overall, the results indicate that class size effects on reading achievement are not significant across countries and years. However, class size effects are evident in Romania where reducing class size increases reading achievement. In contrast, in Germany, increasing class size seems to increase reading achievement. In future work, it would be valuable to evaluate differential class size effects for minority or economically disadvantaged student groups or low- and high-achievers. Replication studies with different samples and in various settings would also be informative. Future research should continue examining class size effects in different age groups and countries using rich international databases.

Keywords: class size, reading achievement, instrumental variables, PIRLS

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Authors: Farahnaz Karami

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Routing is an important, challenging task in mobile ad hoc networks due to node mobility, lack of central control, unstable links, and limited resources. An ant colony has been found to be an attractive technique for routing in Mobile Ad Hoc Networks (MANETs). However, existing swarm intelligence based routing protocols find an optimal path by considering only one or two route selection metrics without considering correlations among such parameters making them unsuitable lonely for routing real time applications. Fuzzy logic combines multiple route selection parameters containing uncertain information or imprecise data in nature, but does not have multipath routing property naturally in order to provide load balancing. The objective of this paper is to design a routing algorithm using fuzzy logic and ant colony that can solve some of routing problems in mobile ad hoc networks, such as nodes energy consumption optimization to increase network lifetime, link failures rate reduction to increase packet delivery reliability and providing load balancing to optimize available bandwidth. In proposed algorithm, the path information will be given to fuzzy inference system by ants. Based on the available path information and considering the parameters required for quality of service (QoS), the fuzzy cost of each path is calculated and the optimal paths will be selected. NS2.35 simulation tools are used for simulation and the results are compared and evaluated with the newest QoS based algorithms in MANETs according to packet delivery ratio, end-to-end delay and routing overhead ratio criterions. The simulation results show significant improvement in the performance of these networks in terms of decreasing end-to-end delay, and routing overhead ratio, and also increasing packet delivery ratio.

Keywords: mobile ad hoc networks, routing, quality of service, ant colony, fuzzy logic

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Authors: Jorge Anibal Restrepo Morales, Sonia Martín Gómez

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A model based on a logical framework was developed to quantify SMEs' internationalization capacity. To do so, linguistic variables, such as human talent, infrastructure, innovation strategies, FTAs, marketing strategies, finance, etc. were integrated. It is argued that a company’s management of international markets depends on internal factors, especially capabilities and resources available. This study considers internal factors as the biggest business challenge because they force companies to develop an adequate set of capabilities. At this stage, importance and strategic relevance have to be defined in order to build competitive advantages. A fuzzy inference system is proposed to model the resources, skills, and capabilities that determine the success of internationalization. Data: 157 linguistic variables were used. These variables were defined by international trade entrepreneurs, experts, consultants, and researchers. Using expert judgment, the variables were condensed into18 factors that explain SMEs’ export capacity. The proposed model is applied by means of a case study of the textile and clothing cluster in Medellin, Colombia. In the model implementation, a general index of 28.2 was obtained for internationalization capabilities. The result confirms that the sector’s current capabilities and resources are not sufficient for a successful integration into the international market. The model specifies the factors and variables, which need to be worked on in order to improve export capability. In the case of textile companies, the lack of a continuous recording of information stands out. Likewise, there are very few studies directed towards developing long-term plans, and., there is little consistency in exports criteria. This method emerges as an innovative management tool linked to internal organizational spheres and their different abilities.

Keywords: business strategy, exports, internationalization, fuzzy set methods

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Authors: Ipek Goktepe, Israa Elnemr, Hammad Asim, Hao Feng, Mosbah Kushad, Hee Park, Sheikha Alzeyara, Mohammad Alhajri

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Food safety management in Qatar is under the shared oversight of multiple agencies in two government ministries (Ministry of Public Health and Ministry of Municipality and Environment). Despite the increasing number and diversity of the food service establishments, no systematic food surveillance system is in place in the country, which creates a gap in terms of determining the food safety attitudes and practices applied in the food service operations. Therefore, this study seeks to partially address this gap through determination of food safety knowledge among food handlers, specifically with respect to food preparation and handling practices, and sanitation methods applied in food service providers (FSPs) and a major market in Doha, Qatar. The study covered a sample of 53 FSPs randomly selected out of 200 FSPs. Face-to-face interviews with managers at participating FSPs were conducted using a 40-questions survey. Additionally, 120 produce handlers who are in direct contact with fresh produce at the major produce market in Doha were surveyed using a questionnaire containing 21 questions. A written informed consent was obtained from each survey participant. The survey data were analyzed using the chi-square test and correlation test. The significance was evaluated at p ˂ 0.05. The results from the FSPs surveys indicated that the average age of FSPs was 11 years, with the oldest and newest being established in 1982 and 2015, respectively. Most managers (66%) had college degree and 68% of them were trained on the food safety management system known as HACCP. These surveys revealed that FSP managers’ training and education level were highly correlated with the probability of their employees receiving food safety training while managers with lower education level had no formal training on food safety for themselves nor for their employees. Casual sit-in and fine dine-in restaurants consistently kept records (100%), followed by fast food (36%), and catering establishments (14%). The produce handlers’ survey results showed that none of the workers had any training on safe produce handling practices. The majority of the workers were in the age range of 31-40 years (37%) and only 38% of them had high-school degree. Over 64% of produce handlers claimed to wash their hands 4-5 times per day but field observations pointed limited handwashing as there was soap in the settings. This observation suggests potential food safety risks since a significant correlation (p ˂ 0.01) between the educational level and the hand-washing practices was determined. This assessment on food safety culture through determination of food and produce handlers' level of knowledge and practices, the first of its kind in Qatar, demonstrated that training and education are important factors which directly impact the food safety culture in FSPs and produce markets. These findings should help in identifying the need for on-site training of food handlers for effective food safety practices in food establishments in Qatar.

Keywords: food safety, food safety culture, food service providers, food handlers

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Authors: Emmanuel Chinaguh, Kehinde Adeosun

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Nigerians die untimely, with 55.75 years of life expectancy, which is 17.45 below the world average of 73.2 (Worldometer, 2020). This is due, among other factors, to the country's limited access to high-quality healthcare. To increase access to good and affordable healthcare services, the National Health Insurance Authority (NHIA) Bill 2022 – which repealed the National Health Insurance Scheme Act 2004 – was passed into law. Applying Jacob Mey’s (2001) pragmatics act (pract) theory, this study explores how NHIA seeks to actualise these healthcare goals by characterising the general situational prototype or pragmemes and pragmatic acts in institutional communications. Data was sourced from the NHIA operational guidelines, which has 147 pages and four sections, and shared posters on NHIA Nigeria Twitter Handle with 14,200 followers. Digital humanities tools, like AntConc and Voyant, were engaged in the data analysis for text encoding and data visualisation. This study identifies these discourse tokens in the data: advertisement and programmes, standards and accreditation, records and information, and offences and penalties. Advertisement and programmes pract facilitating, propagating, prospecting, advising and informing; standards and accreditation, and records and information pract stating, informing and instructing; and offences and penalties pract stating and sanctioning. These practs combined to advance the goals of affordable care and universal accessibility to quality healthcare services. The pragmatic acts were marked by these pragmatic tools: shared situational knowledge (SSK), relevance (REL), reference (REF) and inference (INF). This paper adds to the understanding of health insurance discourse in Nigeria as a mediated social practice that promotes the health of Nigerians.

Keywords: affordable care, NHIA, Nigeria’s health insurance discourse, pragmatic acts.

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Authors: Yong Chen

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To understand the detailed molecular mechanisms of memory formation in engram cells is one of the most fundamental questions in neuroscience. Recent single-cell RNA-seq (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq) techniques have allowed us to explore the sparsely activated engram ensembles, enabling access to the molecular mechanisms that underlie experience-dependent memory formation and consolidation. However, the absence of specific and powerful computational methods to detect memory-related genes (modules) and their regulatory relationships in the sc/snRNA-seq datasets has strictly limited the analysis of underlying mechanisms and memory coding principles in mammalian brains. Here, we present a deep-learning method named SCENTBOX, to detect memory-related gene modules and causal regulatory relationships among themfromsc/snRNA-seq datasets. SCENTBOX first constructs codifferential expression gene network (CEGN) from case versus control sc/snRNA-seq datasets. It then detects the highly correlated modules of differential expression genes (DEGs) in CEGN. The deep network embedding and attention-based convolutional neural network strategies are employed to precisely detect regulatory relationships among DEG genes in a module. We applied them on scRNA-seq datasets of TRAP; Ai14 mouse neurons with fear memory and detected not only known memory-related genes, but also the modules and potential causal regulations. Our results provided novel regulations within an interesting module, including Arc, Bdnf, Creb, Dusp1, Rgs4, and Btg2. Overall, our methods provide a general computational tool for processing sc/snRNA-seq data from case versus control studie and a systematic investigation of fear-memory-related gene modules.

Keywords: sc/snRNA-seq, memory formation, deep learning, gene module, causal inference

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Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

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Authors: Andrea Miconi

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The research will focus on the results of the Tempus European Project eMEDia dedicated to Cross-Media Journalism. The project is founded by the European Commission as it involves four European partners - IULM University, Tampere University, University of Barcelona, and the Mediterranean network Unimed - and three Tunisian Universities – IPSI La Manouba, Sfax and Sousse – along with the Tunisian Ministry for Higher Education and the National Syndicate of Journalists. The focus on Tunisian condition is basically due to the role played by digital activists in its recent history. The research is dedicated to the relationship between political participation, news-making practices and the spread of social media, as it is affecting Tunisian society. As we know, Tunisia during the Arab Spring had been widely considered as a laboratory for the analysis the use of new technologies for political participation. Nonetheless, the literature about the Arab Spring actually fell short in explaining the genesis of the phenomenon, on the one hand by isolating technologies as a casual factor in the spread of demonstrations, and on the other by analyzing North-African condition through a biased perspective. Nowadays, it is interesting to focus on the consolidation of the information environment three years after the uprisings. And what is relevant, only a close, in-depth analysis of Tunisian society is able to provide an explanation of its history, and namely of the part of digital media in the overall evolution of political system. That is why the research is based on different methodologies: desk stage, interviews, and in-depth analysis of communication practices. Networked journalism is the condition determined by the technological innovation on news-making activities: a condition upon which professional journalist can no longer be considered the only player in the information arena, and a new skill must be developed. Along with democratization, nonetheless, the so-called citizen journalism is also likely to produce some ambiguous effects, such as the lack of professional standards and the spread of information cascades, which may prove to be particularly dangerous in an evolving media market as the Tunisian one. This is why, according to the project, a new profile must be defined, which is able to manage this new condition, and which can be hardly reduced to the parameters of traditional journalistic work. Rather than simply using new devices for news visualization, communication professionals must also be able to dialogue with all new players and to accept the decentralized nature of digital environments. This networked nature of news-making seemed to emerge during the Tunisian revolution, when bloggers, journalists, and activists used to retweet each other. Nonetheless, this intensification of communication exchange was inspired by the political climax of the uprising, while all media, by definition, are also supposed to bring some effects on people’s state of mind, culture and daily life routines. That is why it is worth analyzing the consolidation of these practices in a normal, post-revolutionary situation.

Keywords: cross-media, education, Mediterranean, networked journalism, social media, Tunisia

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Authors: Vahid Ebrahimipour

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Word representation and context meaning of text-based documents play an essential role in knowledge modeling. Business procedures written in natural language are meant to store technical and engineering information, management decision and operation experience during the production system life cycle. Context meaning representation is highly dependent upon word sense, lexical relativity, and sematic features of the argument. This paper proposes a method for lexical semantic analysis and context meaning representation of maintenance activity in a mass production system. Our approach constructs a straightforward lexical semantic approach to analyze facilitates semantic and syntactic features of context structure of maintenance report to facilitate translation, interpretation, and conversion of human-readable interpretation into computer-readable representation and understandable with less heterogeneity and ambiguity. The methodology will enable users to obtain a representation format that maximizes shareability and accessibility for multi-purpose usage. It provides a contextualized structure to obtain a generic context model that can be utilized during the system life cycle. At first, it employs a co-occurrence-based clustering framework to recognize a group of highly frequent contextual features that correspond to a maintenance report text. Then the keywords are identified for syntactic and semantic extraction analysis. The analysis exercises causality-driven logic of keywords’ senses to divulge the structural and meaning dependency relationships between the words in a context. The output is a word contextualized representation of maintenance activity accommodating computer-based representation and inference using OWL/RDF.

Keywords: lexical semantic analysis, metadata modeling, contextual meaning extraction, ontology modeling, knowledge representation

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Authors: G. Medkour Ishak-Boushaki, A. Taibi, M. Allab

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Quantitative environmental radioactivity measurements are needed to determine the level of exposure of a population to ionizing radiations and for the assessment of the associated risks. Gamma spectrometry remains a very powerful tool for the analysis of radionuclides present in an environmental sample but the basic problem in such measurements is the low rate of detected events. Using large environmental samples could help to get around this difficulty but, unfortunately, new issues are raised by gamma rays attenuation and self-absorption. Recently, a new method has been suggested, to detect and identify without quantification, in a short time, a gamma ray of a low count source. This method does not require, as usually adopted in gamma spectrometry measurements, a pulse height spectrum acquisition. It is based on a chronological record of each detected photon by simultaneous measurements of its energy ε and its arrival time τ on the detector, the pair parameters [ε,τ] defining an event mode sequence (EMS). The EMS serials are analyzed sequentially by a Bayesian approach to detect the presence of a given radioactive source. The main object of the present work is to test the applicability of this sequential approach in radioactive environmental materials detection. Moreover, for an appropriate health oversight of the public and of the concerned workers, the analysis has been extended to get a reliable quantification of the radionuclides present in environmental samples. For illustration, we consider as an example, the problem of detection and quantification of 238U. Monte Carlo simulated experience is carried out consisting in the detection, by a Ge(Hp) semiconductor junction, of gamma rays of 63 keV emitted by 234Th (progeny of 238U). The generated EMS serials are analyzed by a Bayesian inference. The application of the sequential Bayesian approach, in environmental radioactivity analysis, offers the possibility of reducing the measurements time without requiring large environmental samples and consequently avoids the attached inconvenient. The work is still in progress.

Keywords: Bayesian approach, event mode sequence, gamma spectrometry, Monte Carlo method

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Authors: Ambrish Tiwari, Sudhasini Panda, Archana Singh, Kalpana Luthra, S. K. Sharma

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Introduction: On the basis of available literature we know that various host factors play a role in outcome of Tuberculosis (TB) infection by modulating innate immunity. One such factor is Inducible Nitric Oxide Synthase enzyme (iNOS) which help in the production of Nitric Oxide (NO), an antimicrobial agent. Expression of iNOS is in control of various host factors in which Vitamin D along with its nuclear receptor Vitamin D receptor (VDR) is one of them. Vitamin D along with its receptor also produces cathelicidin (antimicrobicidal agent). With this background, we attempted to investigate the levels of Vitamin D and NO along with their associated molecules in tuberculosis patients and household contacts as compared to healthy controls and assess the implication of these findings in susceptibility to tuberculosis (TB). Study subjects and methods: 100 active TB patients, 75 household contacts, and 70 healthy controls were taken. VDR and iNOS mRNA levels were studied using real-time PCR. Serum VDR, cathelicidin, iNOS levels were measured using ELISA. Serum Vitamin D levels were measured in serum samples using chemiluminescence based immunoassay. NO was measured using colorimetry based kit. Results: VDR and iNOS mRNA levels were found to be lower in active TB group compared to household contacts and healthy controls (P=0.0001 and 0.005 respectively). The serum levels of Vitamin D were also found to be lower in active TB group as compared to healthy controls (P =0.001). Levels of cathelicidin and NO was higher in patient group as compared to other groups (p=0.01 and 0.5 respectively). However, the expression of VDR and iNOS and levels of vitamin D was significantly (P < 0.05) higher in household contacts compared to both active TB and healthy control groups. Inference: Higher levels of Vitamin D along with VDR and iNOS expression in household contacts as compared to patients suggest that vitamin D might have a protective role against TB which prevents activation of the disease. From our data, we can conclude that decreased vitamin D levels could be implicated in disease progression and we can use cathelicidin and NO as a biomarker for early diagnosis of pulmonary tuberculosis.

Keywords: vitamin D, VDR, iNOS, tuberculosis

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Authors: Erika Takidah, Salina Kassim

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Digital transformation has accelerated in the new millennium. It is reshaping the financial services industry from a traditional system to financial technology. Moreover, the number of financial inclusion rates in Indonesia is less than 60%. An innovative model needed to elucidate this national problem. On the other hand, the Islamic financial service industry and financial technology grow fast as a new aspire in economic development. An Islamic bank, takaful, Islamic microfinance, Islamic financial technology and Islamic social finance institution could collaborate to intensify the financial inclusion number in Indonesia. The primary motive of this paper is to examine the strategy of collaboration-based Islamic financial services to enhance financial inclusion in Indonesia, particularly facing the digital era. The fundamental findings for the main problems are the foundations and key ecosystems aspect involved in the development of collaboration-based Islamic financial services. By using the Interpretive Structural Model (ISM) approach, the core problems faced in the development of the models have lacked policy instruments guarding the collaboration-based Islamic financial services with fintech work process and availability of human resources for fintech. The core strategies or foundations that are needed in the framework of collaboration-based Islamic financial services are the ability to manage and analyze data in the big data era. For the aspects of the Ecosystem or actors involved in the development of this model, the important actor is government or regulator, educational institutions, and also existing industries (Islamic financial services). The outcome of the study designates that strategy collaboration of Islamic financial services institution supported by robust technology, a legal and regulatory commitment of the regulators and policymakers of the Islamic financial institutions, extensive public awareness of financial inclusion in Indonesia. The study limited itself to realize financial inclusion, particularly in Islamic finance development in Indonesia. The study will have an inference for the concerned professional bodies, regulators, policymakers, stakeholders, and practitioners of Islamic financial service institutions.

Keywords: collaboration, financial inclusion, Islamic financial services, Islamic fintech

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Authors: Hung-Sheng Lin, Cheng-Hsuan Li

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Over the past few years, kernel-based algorithms have been widely used to extend some linear feature extraction methods such as principal component analysis (PCA), linear discriminate analysis (LDA), and nonparametric weighted feature extraction (NWFE) to their nonlinear versions, kernel principal component analysis (KPCA), generalized discriminate analysis (GDA), and kernel nonparametric weighted feature extraction (KNWFE), respectively. These nonlinear feature extraction methods can detect nonlinear directions with the largest nonlinear variance or the largest class separability based on the given kernel function. Moreover, they have been applied to improve the target detection or the image classification of hyperspectral images. The double nearest proportion feature extraction (DNP) can effectively reduce the overlap effect and have good performance in hyperspectral image classification. The DNP structure is an extension of the k-nearest neighbor technique. For each sample, there are two corresponding nearest proportions of samples, the self-class nearest proportion and the other-class nearest proportion. The term “nearest proportion” used here consider both the local information and other more global information. With these settings, the effect of the overlap between the sample distributions can be reduced. Usually, the maximum likelihood estimator and the related unbiased estimator are not ideal estimators in high dimensional inference problems, particularly in small data-size situation. Hence, an improved estimator by shrinkage estimation (regularization) is proposed. Based on the DNP structure, LDA is included as a special case. In this paper, the kernel method is applied to extend DNP to kernel-based DNP (KDNP). In addition to the advantages of DNP, KDNP surpasses DNP in the experimental results. According to the experiments on the real hyperspectral image data sets, the classification performance of KDNP is better than that of PCA, LDA, NWFE, and their kernel versions, KPCA, GDA, and KNWFE.

Keywords: feature extraction, kernel method, double nearest proportion feature extraction, kernel double nearest feature extraction

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