Search results for: affective computing

Authors: Victor Onomza Waziri, John K. Alhassan, Idris Ismaila, Noel Dogonyara

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This paper describes the problem of building secure computational services for encrypted information in the Cloud. Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy or confidentiality, availability and integrity of the data and user’s security. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute a theoretical presentations in a high-level computational processes that are based on number theory that is derivable from abstract algebra which can easily be integrated and leveraged in the Cloud computing interface with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based on cryptographic security algorithm.

Keywords: big data analytics, security, privacy, bootstrapping, Fully Homomorphic Encryption Scheme

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Authors: S. H. J. Liu

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This paper aims to explore the role of peer Corrective Feedback (CF) in improving written productions by English-as-a- foreign-language (EFL) learners who work together via Wikispaces. It attempted to determine the effect of peer CF on form accuracy in English, such as grammar and lexis. Thirty-four EFL learners at the tertiary level were randomly assigned into the experimental (with peer feedback) or the control (without peer feedback) group; each group was subdivided into small groups of two or three. This resulted in six and seven small groups in the experimental and control groups, respectively. In the experimental group, each learner played a role as an assessor (providing feedback to others), as well as an assessee (receiving feedback from others). Each participant was asked to compose his/her written work and revise it based on the feedback. In the control group, on the other hand, learners neither provided nor received feedback but composed and revised their written work on their own. Data collected from learners’ compositions and post-task interviews were analyzed and reported in this study. Following the completeness of three writing tasks, 10 participants were selected and interviewed individually regarding their perception of collaborative learning in the Computer-Mediated Communication (CMC) environment. Language aspects to be analyzed included lexis (e.g., appropriate use of words), verb tenses (e.g., present and past simple), prepositions (e.g., in, on, and between), nouns, and articles (e.g., a/an). Feedback types consisted of CF, affective, suggestive, and didactic. Frequencies of feedback types and the accuracy of the language aspects were calculated. The results first suggested that accurate items were found more in the experimental group than in the control group. Such results entail that those who worked collaboratively outperformed those who worked non-collaboratively on the accuracy of linguistic aspects. Furthermore, the first type of CF (e.g., corrections directly related to linguistic errors) was found to be the most frequently employed type, whereas affective and didactic were the least used by the experimental group. The results further indicated that most participants perceived that peer CF was helpful in improving the language accuracy, and they demonstrated a favorable attitude toward working with others in the CMC environment. Moreover, some participants stated that when they provided feedback to their peers, they tended to pay attention to linguistic errors in their peers’ work but overlook their own errors (e.g., past simple tense) when writing. Finally, L2 or FL teachers or practitioners are encouraged to employ CMC technologies to train their students to give each other feedback in writing to improve the accuracy of the language and to motivate them to attend to the language system.

Keywords: peer corrective feedback, computer-mediated communication (CMC), second or foreign language (L2 or FL) learning, Wikispaces

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Authors: Shao-Ying Wang, Shin-I Shih, Chi-Cheng Wu

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Background: By following to the maturity theory about age, the manifestation of depression in different age groups under occupational stressors still remains unclear. Therefore, the aim of this study was to examine the depression within four main symptoms clusters: cognition, affect, physical complaints and interpersonal difficulty among the different age groups. Additionally, this study also used the stress appraisal theory, through the examination of challenge and hindrance appraisals, the effects of cognitive factors were expected to give therapeutic indication for the future treatment of depression under abusive leadership. Methods (Participants and Procedure): The data were collected in two waves from employees of local companies in Taiwan. The participants (58 males and 167 females) were native Chinese speakers, ranging in age from 20 to 59 years (M= 36.51). Up to 80% educational level of participants were above senior high. The married population was approximately at 43%. Measures; 1. Abusive Leadership: To measure abusive leadership, we used 15-item scale of abusive supervision which anchored on a 7-point Likert-type scale. (α= .96) 2. Depression: We used Taiwanese Depression Scale to measure the 4 clusters (cognition, affect, physical complaints and interpersonal difficulty) of symptoms. Participants responded for depression anchored on a 7-point Likert-type scale (α= .96). 3. Stress Appraisal Scale: To measure challenge and hindrance types of appraisal, participants responded to 33-item measure anchored on a 7-point Likert-type scale. (Challenge appraisal; α= .90; hindrance appraisal α= .87). Results: The results of correlation showed that there was a significant and negative correlation between abusive leadership and age (r = - .21, p < .01). Abusive leadership was positive correlated significantly with hindrance appraisal (r = .52, p < .01) and depression (r = .20, p < .01). The results also showed that hindrance appraisal was correlated to depression positively (r = .36, p < .01). A one-way ANOVA was conducted to compare the effect of lower/middle/order age groups on each cluster of depressive symptoms. The results showed that the effect of age groups on cognition was significant F (2, 157) =3.66, P < .05. Older age group (M=13.43 SD=6.84) reported less cognitive symptoms of depression than the middle (M=16.77 SD=7.49) and lower age (M=16.91 SD=6.97) groups. Besides, the effect of age groups on affect was also significant F (2,157)= 4.09 P < .05. Older age group (M=18.68 SD=8.98) reported less affective symptoms of depression than the middle (M=22.01 SD=7.96) and lower age (M=23.56 SD=7.67) groups. Moreover, the main effect of hindrance appraisal was found F (2, 157) =3.81, P < .05. Older age group (M=9.44 SD=2.89) reported fewer score on hindrance appraisals than the middle (M=11.06 SD=4.02) and lower age (M=9.62 SD=3.17) groups. To conclude, the severity of depression symptoms varies across different age groups. Maturity seems to be the protective factor to depression, accompanying with lower hindrance appraisals.

Keywords: abusive leadership, affective commitment, depression symptoms, psychological well-being

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Authors: Ahmed Tarek, Ahmed Alveed

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In the theory of computing, there are a wide variety of direct and indirect proof techniques. However, mathematical induction (MI) stands out to be one of the most powerful proof techniques for proving hypotheses, theorems, and new results. There are variations of mathematical induction-based proof techniques, which are broadly classified into three categories, such as structural induction (SI), weak induction (WI), and strong induction (SI). In this expository paper, several different variants of the mathematical induction techniques are explored, and the specific scenarios are discussed where a specific induction technique stands out to be more advantageous as compared to other induction strategies. Also, the essential difference among the variants of mathematical induction are explored. The points of separation among mathematical induction, recursion, and logical deduction are precisely analyzed, and the relationship among variations of recurrence relations, and mathematical induction are being explored. In this context, the application of recurrence relations, and mathematical inductions are considered together in a single framework for codewords over a given alphabet.

Keywords: alphabet, codeword, deduction, mathematical, induction, recurrence relation, strong induction, structural induction, weak induction

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Authors: Julio Vega

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Expression recognition is a field of Artificial Intelligence whose main objectives are to recognize basic forms of affective expression that appear on people’s faces and contributing to behavioral studies. In this work, a ROS node has been developed that, based on Deep Learning techniques, is capable of detecting the facial expressions of the people that appear in the image. These algorithms were optimized so that they can be executed in real time on an embedded platform. The experiments were carried out in a PC with a USB camera and in a Raspberry Pi 4 with a PiCamera. The final results shows a plausible system, which is capable to work in real time even in an embedded platform.

Keywords: python, low-cost, raspberry pi, emotion detection, human-robot interaction, ROS node

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Authors: Nan Hu, Chao Wang, Xi Li, Xuehai Zhou

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The field-programmable gate array (FPGA) has been widely adopted in the high-performance computing domain. In recent years, the embedded system-on-a-chip (SoC) contains coarse granularity multi-core CPU (central processing unit) and mobile GPU (graphics processing unit) that can be used as general-purpose accelerators. The motivation is that algorithms of various parallel characteristics can be efficiently mapped to the heterogeneous architecture coupled with these three processors. The CPU and GPU offload partial computationally intensive tasks from the FPGA to reduce the resource consumption and lower the overall cost of the system. However, in present common scenarios, the applications always utilize only one type of accelerator because the development approach supporting the collaboration of the heterogeneous processors faces challenges. Therefore, a systematic approach takes advantage of write-once-run-anywhere portability, high execution performance of the modules mapped to various architectures and facilitates the exploration of design space. In this paper, A servant-execution-flow model is proposed for the abstraction of the cooperation of the heterogeneous processors, which supports task partition, communication and synchronization. At its first run, the intermediate language represented by the data flow diagram can generate the executable code of the target processor or can be converted into high-level programming languages. The instantiation parameters efficiently control the relationship between the modules and computational units, including two hierarchical processing units mapping and adjustment of data-level parallelism. An embedded system of a three-dimensional waveform oscilloscope is selected as a case study. The performance of algorithms such as contrast stretching, etc., are analyzed with implementations on various combinations of these processors. The experimental results show that the heterogeneous computing system with less than 35% resources achieves similar performance to the pure FPGA and approximate energy efficiency.

Keywords: FPGA-CPU-GPU collaboration, design space exploration, heterogeneous computing, intermediate language, parameterized instantiation

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Authors: Izza Hidaya, Korichi Mourad

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Solvent extraction is an affective method for reduction of aromatic content of lube oil. Frequently with phenol, furfural, NMP(N-methyl pyrrolidone). The solvent power and selectivity can be further increased by using surfactant as additive which facilitate phase separation and to increase raffinate yield. The aromatics in lube oil were extracted at different temperatures (ranging from 333.15 to 343.15K) and different concentration of surfactant (ranging from 0.01 to 0.1% wt).The extraction temperature and the amount of sulfate lauryl éther de sodium In phenoll were investigated systematically in order to determine their optimum values. The amounts of aromatic, paraffinic and naphthenic compounds were determined using ASTM standards by measuring refractive index (RI), viscosity, molecular weight and sulfur content. It was found that using 0,01%wt. surfactant at 343.15K yields the optimum extraction conditions.

Keywords: extraction, lubricating oil, aromatics, hydrocarbons

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Authors: Silke Bustamante, Andrea Pelzeter, Andreas Deckmann, Rudi Ehlscheidt, Franziska Freudenberger

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Many companies increasingly seek to enhance their attractiveness as an employer to bind their employees. At the same time, corporate responsibility for social and ecological issues seems to become a more important part of an attractive employer brand. It enables the company to match the values and expectations of its members, to signal fairness towards them and to increase its brand potential for positive psychological identification on the employees’ side. In the last decade, several empirical studies have focused this relationship, confirming a positive effect of employees’ CSR perception and their affective organizational commitment. The current paper aims to take a slightly different view by analyzing the impact of another factor on commitment: the weighted employee’s satisfaction with the employer CSR. For that purpose, it is assumed that commitment levels are rather a result of the fulfillment or disappointment of expectations. Hence, instead of merely asking how CSR perception affects commitment, a more complex independent variable is taken into account: a weighted satisfaction construct that summarizes two different factors. Therefore, the individual level of commitment contingent on CSR is conceptualized as a function of two psychological processes: (1) the individual significance that an employee ascribes to specific employer attributes and (2) the individual satisfaction based on the fulfillment of expectation that rely on preceding perceptions of employer attributes. The results presented are based on a quantitative survey that was undertaken among employees of the German service sector. Conceptually a five-dimensional CSR construct (ecology, employees, marketplace, society and corporate governance) and a two-dimensional non-CSR construct (company and workplace) were applied to differentiate employer characteristics. (1) Respondents were asked to indicate the importance of different facets of CSR-related and non-CSR-related employer attributes. By means of a conjoint analysis, the relative importance of each employer attribute was calculated from the data. (2) In addition to this, participants stated their level of satisfaction with specific employer attributes. Both indications were merged to individually weighted satisfaction indexes on the seven-dimensional levels of employer characteristics. The affective organizational commitment of employees (dependent variable) was gathered by applying the established 15-items Organizational Commitment Questionnaire (OCQ). The findings related to the relationship between satisfaction and commitment will be presented. Furthermore, the question will be addressed, how important satisfaction with CSR is in relation to the satisfaction with other attributes of the company in the creation of commitment. Practical as well as scientific implications will be discussed especially with reference to previous results that focused on CSR perception as a commitment driver.

Keywords: corporate social responsibility, organizational commitment, employee attitudes/satisfaction, employee expectations, employer brand

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Authors: Eric Huang, Coleman DeLude, Justin Romberg, Saibal Mukhopadhyay, Madhavan Swaminathan

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High performance computing (HPC) based emulators can be used to model the scattering from multiple stationary and moving targets for RADAR applications. These emulators rely on the RADAR Cross Section (RCS) of the targets being available in complex scenarios. Representing the RCS using tables generated from electromagnetic (EM) simulations is often times cumbersome leading to large storage requirement. This paper proposed a spherical harmonic based anisotropic scatterer model to represent the RCS of complex targets. The problem of finding the locations and reflection profiles of all scatterers can be formulated as a linear least square problem with a special sparsity constraint. This paper solves this problem using a modified Orthogonal Matching Pursuit algorithm. The results show that the spherical harmonic based scatterer model can effectively represent the RCS data of complex targets.

Keywords: RADAR, RCS, high performance computing, point scatterer model

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Authors: Elena F. Ruiz, Marina Vicario, Chadwick Carreto, Rubén Peredo

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One of the main obstacles in Mexico’s engineering programs is math comprehension, especially in the Derivative concept. Due to this, we present a study case that relates Mobile Computing and Classroom Learning in the “Escuela Superior de Cómputo”, based on the Educational model of the Instituto Politécnico Nacional (competence based work and problem solutions) in which we propose apps and activities to teach the concept of the Derivative. M- Learning is emphasized as one of its lines, as the objective is the use of mobile devices running an app that uses its components such as sensors, screen, camera and processing power in classroom work. In this paper, we employed Augmented Reality (ARRoC), based on the good results this technology has had in the field of learning. This proposal was developed using a qualitative research methodology supported by quantitative research. The methodological instruments used on this proposal are: observation, questionnaires, interviews and evaluations. We obtained positive results with a 40% increase using M-Learning, from the 20% increase using traditional means.

Keywords: augmented reality, classroom learning, educational research, mobile computing

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Authors: Mansouri Nabila, Ben Jemaa Yousra, Motamed Cina, Watelain Eric

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Research and development efforts in intelligent Advanced Driver Assistance Systems (ADAS) seek to save lives and reduce the number of on-road fatalities. For traffic and emergency monitoring, the essential but challenging task is vehicle detection and tracking in reasonably short time. This purpose needs first of all a powerful dynamic car detector model. In fact, this paper presents an optimized HOG process based on shape and motion parameters fusion. Our proposed approach mains to compute HOG by bloc feature from foreground blobs using configurable research window and pathway in order to overcome the shortcoming in term of computing time of HOG descriptor and improve their dynamic application performance. Indeed we prove in this paper that HOG by bloc descriptor combined with motion parameters is a very suitable car detector which reaches in record time a satisfactory recognition rate in dynamic outside area and bypasses several popular works without using sophisticated and expensive architectures such as GPU and FPGA.

Keywords: car-detector, HOG, motion, computing time

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Authors: Jamileh Ahmed, Helena Hernandez, Gabriel De Erausquin

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H1N1 virus susceptibility of iPSC-derived DA neurons from schizophrenia patients and controls will compared. C57/BL-6 fibroblasts were reprogrammed into iPSCs using a lenti-viral vector containing SOKM genes. Pluripotency verification with the AP assay and immunocytochemistry ensured iPSC presence. The experimental outcome of ISPCs from DA neuron differentiation will be discussed in the Results section. Fibroblasts from patients and controls will be reprogrammed into iPSCs using a sendai-virus vector containing SOKM. IPSCs will be characterized using the AP assay, immunocytochemistry and RT-PCR. IPSCs will then be differentiated into DA neurons. Gene methylation will be compared for both groups with custom-designed microarrays.

Keywords: schizophrenia, iPSCs, stem cells, neuroscience

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Authors: Lou Gargouri

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This paper examines how Fanny Cabon's solo performance, Gardiennes (2018) strategically crafts empathetic witnessing through the artist's vocal and physical embodiment of her female ancestors' testimonies, dramatizing the cyclical inheritance of reproductive trauma across generations. Drawing on affect theory and the concept of ethical co-presence, we argue that Cabon's raw voicing of illegal abortions, miscarriages, and abuse through her shape-shifting presence generates an intimate energy loop with the audience. This affective resonance catalyzes recognition of historical injustices, consecrating each singular experience while building collective solidarity. Central to Cabon's political efficacy is her transparent self-revelation through intimate impersonation, which fosters identification with diverse characters as interconnected subjects rather than objectified others. Her solo form transforms the isolation often associated with women's marginalization into radical inclusion, repositioning them from victims to empowered survivors. Comparative analysis with other contemporary works addressing abortion rights illuminates how Gardiennes subverts the traditional medical and clerical gazes that have long governed women's bodies. Ultimately, we contend Gardiennes models the potential of solo performance to harness empathy as a subversive political force. Cabon's theatrical alchemy circulates the effects of injustice through the ethical co-presence of performer and spectator, forging intersubjective connections that reframe marginalized groups traditionally objectified within dominant structures of patriarchal power. In dramatizing how the act of witnessing another's trauma can generate solidarity and galvanize resistance, Cabon's work demonstrates the role of embodied performance in catalyzing social change through the recuperation of women's voices and lived experiences. This paper thus aims to contribute to the emerging field of feminist solo performance criticism by illuminating how Cabon's innovative dramaturgy bridges the personal and the political. Her strategic mobilization of intimacy, identification, and co-presence offers a model for how the affective dynamics of autobiographical performance can be harnessed to confront gendered oppression and imagine more equitable futures. Gardiennes invites us to consider how the circulation of empathy through ethical spectatorship can foster the collective alliances necessary for advancing the unfinished project of women's liberation.

Keywords: gender and sexuality studies, solo performance, trauma studies, affect theory

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Authors: Shokofeh Ebrtahimi

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Let G be the chemical graph of a molecule. The matrix D = [dij ] is called the detour matrix of G, if dij is the length of longest path between atoms i and j. The sum of all entries above the main diagonal of D is called the detour index of G.Chemical graph theory is the topology branch of mathematical chemistry which applies graph theory to mathematical modelling of chemical phenomena.[1] The pioneers of the chemical graph theory are Alexandru Balaban, Ante Graovac, Ivan Gutman, Haruo Hosoya, Milan Randić and Nenad TrinajstićLet G be the chemical graph of a molecule. The matrix D = [dij ] is called the detour matrix of G, if dij is the length of longest path between atoms i and j. The sum of all entries above the main diagonal of D is called the detour index of G. In this paper, a new program for computing the detour index of molecular graphs of nanotubes by heptagons is determineded. Some Conjectures about detour index of Molecular graphs of nanotubes is included.

Keywords: chemical graph, detour matrix, Detour index, carbon nanotube

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Authors: Almudena Konrad, Tomás Galguera

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Lack of motivation and interest is a serious obstacle to students’ learning computing skills. A need exists for a knowledge base on effective pedagogy and curricula to teach computer programming. This paper presents results from research evaluating a six-year project designed to teach complex concepts in computer programming collaboratively, while supporting students to continue developing their computer thinking and related coding skills individually. Utilizing a quasi-experimental, mixed methods design, the pedagogical approaches and methods were assessed in two contrasting groups of students with different socioeconomic status, gender, and age composition. Analyses of quantitative data from Likert-scale surveys and an evaluation rubric, combined with qualitative data from reflective writing exercises and semi-structured interviews yielded convincing evidence of the project’s success at both teaching and inspiring students.

Keywords: computational thinking, computing education, computer programming curriculum, logic, teaching methods

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Authors: Mohammad H. Almomani

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In this paper, we argue the effect of the initial sample size, and the increment in simulation samples on the performance of a sequential approach that used in selecting the top m designs when the number of alternative designs is very large. The sequential approach consists of two stages. In the first stage the ordinal optimization is used to select a subset that overlaps with the set of actual best k% designs with high probability. Then in the second stage the optimal computing budget is used to select the top m designs from the selected subset. We apply the selection approach on a generic example under some parameter settings, with a different choice of initial sample size and the increment in simulation samples, to explore the impacts on the performance of this approach. The results show that the choice of initial sample size and the increment in simulation samples does affect the performance of a selection approach.

Keywords: Large Scale Problems, Optimal Computing Budget Allocation, ordinal optimization, simulation optimization

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Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

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The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: neural network computing, continuous functions generating the input-output mapping, decreasing the training time, machines with big memories

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Authors: Barbara Gawda

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Attachment model formed in childhood has an important impact on emotional development, personality, and social relationships. Attachment is also thought to have an impact on construction of affective-cognitive schemas and cognitive functioning. The aim of the current study was to verify whether there is an association between attachment and cognitive rigidity defined as dogmatism and intolerance of ambiguity. The analysis of 180 participants (persons of a similar age and education level, number of men and women was equal) was conducted. To test the attachment styles, the Revised Experiences in Close Relationships Inventory (ECR-R) was used. To examine cognitive rigidity, the Rokeach and Budner questionnaires were used. A multiple regression model was employed to examine whether attachment styles are predictors for dogmatism. The results confirmed that fearful-ambivalent attachment is the main predictor for dogmatism but not for intolerance of ambiguity.

Keywords: attachment styles, cognitive rigidity, dogmatism, intolerance of ambiguity

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Authors: Elena Arquer Cuenca

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The gypsy community has been a mistreated and rejected group since its arrival in the Iberian Peninsula in the 15th century. At present, despite being the largest ethnic minority group in Spain as well as in Europe, the different legal and social initiatives in favour of equality continue to suffer discrimination by the general society. This has fostered a strengthening of the endogroup accompanied by cultural conservatism as a form of self-protection. Despite the current trend of normalization of sexual diversity in modern societies, LGB people continue to suffer discrimination, especially in more traditional environments or communities. This rejection for reasons of sexual orientation within the family or community can hinder the free development of the person and compromise peaceful coexistence. The present work is intended as an approach to the attitudes of the gypsy population towards non-heterosexual sexual orientation. The objective is none other than ‘to know the appreciation that the gypsy population has about homosexual sex-affective relationships, in order to assess whether this has any impact on family and community coexistence’. The following specific objectives are derived from this general objective: ‘To find out whether there is a relationship between the dichotomous Roma gender system and the acceptance/rejection of homosexuality’; ‘to analyse whether sexual orientation has an impact on the coexistence of the Roman family and community’; ‘to analyse whether the historical discrimination suffered by the Roman population favours the maintenance of the patriarchal heterosexual reproductive family’; and lastly ‘to explore whether ICTs have promoted the process of normalisation and/or acceptance of homosexuality within the Roma community’. In order to achieve these objectives, a bibliographical and documentary review has been used, as well as the semi-structured interview technique, in which 4 gypsy people participated (2 women and 2 men of different ages). One of the main findings was the inappropriateness of the use of the homogenising category "Gypsy People" at present, given the great diversity among the Roma communities. Moreover, the difficulty in accepting homosexuality seems to be related to the fact that the heterosexual reproductive family has been the main survival mechanism of Roma communities over centuries. However, it will be concluded that attitudes towards homosexuality will vary depending on the socio-economic and cultural context and factors such as age or professed religion. Three main contributions of this research are: firstly, the inclusion of sexual orientation as a variable to be considered when analysing peaceful coexistence; secondly socio-historical dynamics and structures of inequality have been taken into account when analysing Roma attitudes towards homosexuality; and finally, the processual nature of socio-cultural changes has also been considered.

Keywords: gender, homosexuality, ICTs, peaceful coexistence, Roma community, sexual orientation

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Authors: Javed Mohammed

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Right now, bio-medical infrastructure lags well behind the curve. Our healthcare system is dispersed and disjointed; medical records are a bit of a mess; and we do not yet have the capacity to store and process the crazy amounts of data coming our way from widespread whole-genome sequencing. And then there are privacy issues. Despite these infrastructure challenges, some researchers are plunging into bio medical Big Data now, in hopes of extracting new and actionable knowledge. They are doing delving into molecular-level data to discover bio markers that help classify patients based on their response to existing treatments; and pushing their results out to physicians in novel and creative ways. Computer scientists and bio medical researchers are able to transform data into models and simulations that will enable scientists for the first time to gain a profound under-standing of the deepest biological functions. Solving biological problems may require High-Performance Computing HPC due either to the massive parallel computation required to solve a particular problem or to algorithmic complexity that may range from difficult to intractable. Many problems involve seemingly well-behaved polynomial time algorithms (such as all-to-all comparisons) but have massive computational requirements due to the large data sets that must be analyzed. High-throughput techniques for DNA sequencing and analysis of gene expression have led to exponential growth in the amount of publicly available genomic data. With the increased availability of genomic data traditional database approaches are no longer sufficient for rapidly performing life science queries involving the fusion of data types. Computing systems are now so powerful it is possible for researchers to consider modeling the folding of a protein or even the simulation of an entire human body. This research paper emphasizes the computational biology's growing need for high-performance computing and Big Data. It illustrates this article’s indispensability in meeting the scientific and engineering challenges of the twenty-first century, and how Protein Folding (the structure and function of proteins) and Phylogeny Reconstruction (evolutionary history of a group of genes) can use HPC that provides sufficient capability for evaluating or solving more limited but meaningful instances. This article also indicates solutions to optimization problems, and benefits Big Data and Computational Biology. The article illustrates the Current State-of-the-Art and Future-Generation Biology of HPC Computing with Big Data.

Keywords: high performance, big data, parallel computation, molecular data, computational biology

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Authors: Bonchan Koo, Junhee Han, Dohyung Lee

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The research attempts to evaluate the accuracy and efficiency of a design optimization procedure which combines wavelets-based solution algorithm and proper orthogonal decomposition (POD) database management technique. Aerodynamic design procedure calls for high fidelity computational fluid dynamic (CFD) simulations and the consideration of large number of flow conditions and design constraints. Even with significant computing power advancement, current level of integrated design process requires substantial computing time and resources. POD reduces the degree of freedom of full system through conducting singular value decomposition for various field simulations. For additional efficiency improvement of the procedure, adaptive wavelet technique is also being employed during POD training period. The proposed design procedure was applied to the optimization of wing aerodynamic performance. Throughout the research, it was confirmed that the POD/wavelets design procedure could significantly reduce the total design turnaround time and is also able to capture all detailed complex flow features as in full order analysis.

Keywords: POD (Proper Orthogonal Decomposition), wavelets, CFD, design optimization, ROM (Reduced Order Model)

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Authors: Sunghae Jun

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Technology management (TM) is important issue in a company improving the competitiveness. Among many activities of TM, technology analysis (TA) is important factor, because most decisions for management of technology are decided by the results of TA. TA is to analyze the developed results of target technology using statistics or Delphi. TA based on Delphi is depended on the experts’ domain knowledge, in comparison, TA by statistics and machine learning algorithms use objective data such as patent or paper instead of the experts’ knowledge. Many quantitative TA methods based on statistics and machine learning have been studied, and these have been used for technology forecasting, technological innovation, and management of technology. They applied diverse computing tools and many analytical methods case by case. It is not easy to select the suitable software and statistical method for given TA work. So, in this paper, we propose a methodology for quantitative TA using statistical computing software called R and data science to construct a general framework of TA. From the result of case study, we also show how our methodology is applied to real field. This research contributes to R&D planning and technology valuation in TM areas.

Keywords: technology management, R system, R data science, statistics, machine learning

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Authors: Maha Shamseddine, Amjad Nusayr, Wassim Itani

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In this paper, we present a Platform-as-a-Service (PaaS) model for controlling the privacy enforcement mechanisms applied on user data when stored and processed in Cloud data centers. The proposed architecture consists of establishing user configurable ‘sticky’ policies on the Graphical User Interface (GUI) data-bound components during the application development phase to specify the details of privacy enforcement on the contents of these components. Various privacy classification classes on the data components are formally defined to give the user full control on the degree and scope of privacy enforcement including the type of execution containers to process the data in the Cloud. This not only enhances the privacy-awareness of the developed Cloud services, but also results in major savings in performance and energy efficiency due to the fact that the privacy mechanisms are solely applied on sensitive data units and not on all the user content. The proposed design is implemented in a real PaaS cloud computing environment on the Microsoft Azure platform.

Keywords: privacy enforcement, platform-as-a-service privacy awareness, cloud computing privacy

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Authors: Gani Pllana

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In the conditions of the rapid development of technics and technology in recent years, the cooperation of the scientific-technical language with the standard Albanian language is continuing with a higher intensity than before. We notice a vigor of enrichment in the vocabulary of technical terminology, due to the birth and formation of new fields and subfields of technics, technology, as computing, mechatronics, telemetry, a multitude of concepts many of which, on the one hand, are marked with names of the languages they come from, mainly from English, but on the other hand, they meet their needs with the lexical mother tongue composition (by common words being raised to terms) and with the activation of other layers, such as compound word terms. Thus, for example, in the field of computing, we notice in it the inclusion of the ordinary vocabulary for reproductive reasons, like mi, dritare, flamur, adresë, skedar (Engl: mouse, window, flag, address, file), and along with them, the compound word terms, serving to differentiate relevant concepts, like, adresë e hiperlidhjes, adresë e uebit, adresë relative, adresë virtuale (Engl. address hyperlink, web address, relative address, virtual address) etc.

Keywords: common words, Albanian language, technical terminology, standardization

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Authors: K. C. Wong

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This paper demonstrates a number of examples in the hope to shed some light on the possibility of designing future operating systems in a more adaptation-based manner. A modern operating system, we conceive, should possess the capability of 'learning' in such a way that it can dynamically adjust its services and behavior according to the current status of the environment in which it operates. In other words, a modern operating system should play a more proactive role during the session of providing system services to users. As such, a modern operating system is expected to create a computing environment, in which its users are provided with system services more matching their dynamically changing needs. The examples demonstrated in this paper show that user's resource access patterns 'learned' and determined during a session can be utilized to improve system performance and hence to provide users with a better and more effective computing environment. The paper also discusses how to use the frequency, the continuity, and the duration of resource accesses in a session to quantitatively measure and determine user's resource access patterns for the examples shown in the paper.

Keywords: adaptation-based systems, operating systems, resource access patterns, system performance

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Authors: Chunye Gong, Ming Tie, Jie Liu, Weimin Bao, Xinbiao Gan, Shengguo Li, Bo Yang, Xuguang Chen, Tiaojie Xiao, Yang Sun

Abstract:

Large-scale CFD simulation relies on high-performance parallel computing, and the load balance is the key role which affects the parallel efficiency. This paper focuses on the load-balancing problem of parallel CFD simulation with structured mesh. A mathematical model for this load-balancing problem is presented. The genetic algorithm, fitness computing, two-level code are designed. Optimal selector, robust operator, and local optimization operator are designed. The properties of the presented genetic algorithm are discussed in-depth. The effects of optimal selector, robust operator, and local optimization operator are proved by experiments. The experimental results of different test sets, DLR-F4, and aircraft design applications show the presented load-balancing algorithm is robust, quickly converged, and is useful in real engineering problems.

Keywords: genetic algorithm, load-balancing algorithm, optimal variation, local optimization

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Authors: Abdellahi Cheikh

Abstract:

With the emergence of quantum computers with very powerful capabilities, the security of the exchange of shared keys between two interlocutors poses a big problem in terms of the rapid development of technologies such as computing power and computing speed. Therefore, the Diffie-Hellmann (DH) algorithm is more vulnerable than ever. No mechanism guarantees the security of the key exchange, so if an intermediary manages to intercept it, it is easy to intercept. In this regard, several studies have been conducted to improve the security of key exchange between two interlocutors, which has led to interesting results. The modification made on our model Diffie-Hellman-RSA-AES (DRA), which encrypts the information exchanged between two users using the three-encryption algorithms DH, RSA and AES, by using stenographic photos to hide the contents of the p, g and ClesAES values that are sent in an unencrypted state at the level of DRA model to calculate each user's public key. This work includes a comparative study between the DRA model and all existing solutions, as well as the modification made to this model, with an emphasis on the aspect of reliability in terms of security. This study presents a simulation to demonstrate the effectiveness of the modification made to the DRA model. The obtained results show that our model has a security advantage over the existing solution, so we made these changes to reinforce the security of the DRA model.

Keywords: Diffie-Hellmann, DRA, RSA, advanced encryption standard

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Authors: Ali Muhammad

Abstract:

The purpose of this study is to develop a theoretical framework which demonstrates the effect of four personal factors on employees rule following behavior in Kuwaiti business organizations. The model suggested in this study includes organizational citizenship behavior, affective organizational commitment, organizational trust, and procedural justice as possible predictors of rule following behavior. The study also attempts to compare the effects of the suggested factors on employees rule following behavior. The new model will, hopefully, extend previous research by adding new variables to the models used to explain employees rule following behavior. A discussion of issues related to rule-following behavior is presented, as well as recommendations for future research.

Keywords: employee adherence to rules, organizational justice, organizational commitment, organizational citizenship behavior

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Authors: Marina Fuertes

Abstract:

Introduction: In everyday life experiences, children are solicited to cooperate with others. Often they perform cooperative tasks with their parents (e.g., setting the table for dinner) or in school. These tasks are very significant since children may learn to turn taking in interactions, to participate as well to accept others participation, to trust, to respect, to negotiate, to self-regulate their emotions, etc. Indeed, cooperative tasks contribute to children social, motor, cognitive and linguistic development. Therefore, it is important to study what learning, social and affective experiences are provided to children during these tasks. In this study, we included parents and preschool educators. Parents and educators are both significant: educative, interactive and affective figures. Rarely parents and educators behavior have been compared in studies about cooperative tasks. Parents and educators have different but complementary styles of interaction and communication. Aims: Therefore, this study aims to compare parents and educators' (of both genders) interactive behavior (cooperativity, empathy, ability to challenge the child, reciprocity, elaboration) during a play/individualized situation involving a cooperative task. Moreover, to compare parents and educators' behavior with girls and boys. Method: A quasi-experimental study with 45 dyads educators-children and 45 dyads with parents and their children. In this study, participated children between 3 and 5 years old and with age appropriate development. Adults and children were videotaped using a variety of materials (e.g., pencils, wood, wool) and tools (e.g., scissors, hammer) to produce together something of their choice during 20-minutes. Each dyad (one adult and one child) was observed and videotaped independently. Adults and children agreed and consented to participate. Experimental conditions were suitable, pleasant and age appropriated. Results: Findings indicate that parents and teachers offer different learning experiences. Teachers were more likely to challenged children to explore new concepts and to accept children ideas. In turn, parents gave more support to children actions and were more likely to use their own example to teach children. Multiple regression analysis indicates that parent versus educator status predicts their behavior. Gender of both children and adults affected the results. Adults acted differently with girls and boys (e.g., adults worked more cooperatively with girls than boys). Male participants supported more girls participation rather than boys while female adults allowed boys to make more decisions than girls. Discussion: Taking our results and past studies, we learn that different qualitative interactions and learning experiences are offered by parents, educators according to parents and children gender. Thus, the same child needs to learn different cooperative strategies according to their interactive patterns and specific context. Yet, cooperative play and individualized activities with children generate learning opportunities and benefits children participation and involvement.

Keywords: early childhood education, parenting, gender, cooperative tasks, adult-child interaction

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Authors: Mohammad H. Taheri, David J. Brown, Nasser Sherkat

Abstract:

Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Keywords: affective computing in education, affect detection, continuous performance test, engagement, flow, HCI, interaction, learning disabilities, machine learning, multimodal, multisensor, physiological sensors, student engagement

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