Search results for: affective computing

Authors: S. Shamohammadi, L. Razavi

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This paper based on the principle concepts of SCS-CN model, a new mathematical model for computation of retention potential (S) presented. In the mathematical model, not only precipitation-runoff concepts in SCS-CN model are precisely represented in a mathematical form, but also new concepts, called “maximum retention” and “total retention” is introduced, and concepts of potential retention capacity, maximum retention, and total retention have been separated from each other. In the proposed model, actual retention (F), maximum actual retention (Fmax), total retention (S), maximum retention (Smax), and potential retention (Sp), for the first time clearly defined, so that Sp is not variable, but a function of morphological characteristics of the watershed. Indeed, based on the mathematical relation of the conceptual curve of SCS-CN model, the proposed model provides a new method for the computation of actual retention in watershed and it simply determined runoff based on. In the corresponding relations, in addition to Precipitation (P), Initial retention (Ia), cumulative values of actual retention capacity (F), total retention (S), runoff (Q), antecedent moisture (M), potential retention (Sp), total retention (S), we introduced Fmax and Fmin referring to maximum and minimum actual retention, respectively. As well as, ksh is a coefficient which depends on morphological characteristics of the watershed. Advantages of the modified version versus the original model include a better precision, higher performance, easier calibration and speed computing.

Keywords: model, mathematical, retention, watershed, SCS

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Authors: Sergio A. Navarro Tuch, Martin Rogelio Bustamante Bello, Leopoldo Julian Lechuga Lopez

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In recent years, Mexico’s population has seen a rise of different physiological and mental negative states. Two main consequences of this problematic are deficient work performance and high levels of stress generating and important impact on a person’s physical, mental and emotional health. Several approaches, such as the use of audiovisual stimulus to induce emotions and modify a person’s emotional state, can be applied in an effort to decreases these negative effects. With the use of different non-invasive physiological sensors such as EEG, luminosity and face recognition we gather information of the subject’s current emotional state. In a controlled environment, a subject is shown a series of selected images from the International Affective Picture System (IAPS) in order to induce a specific set of emotions and obtain information from the sensors. The raw data obtained is statistically analyzed in order to filter only the specific groups of information that relate to a subject’s emotions and current values of the physical variables in the controlled environment such as, luminosity, RGB light color, temperature, oxygen level and noise. Finally, a neural network based control algorithm is given the data obtained in order to feedback the system and automate the modification of the environment variables and audiovisual content shown in an effort that these changes can positively alter the subject’s emotional state. During the research, it was found that the light color was directly related to the type of impact generated by the audiovisual content on the subject’s emotional state. Red illumination increased the impact of violent images and green illumination along with relaxing images decreased the subject’s levels of anxiety. Specific differences between men and women were found as to which type of images generated a greater impact in either gender. The population sample was mainly constituted by college students whose data analysis showed a decreased sensibility to violence towards humans. Despite the early stage of the control algorithm, the results obtained from the population sample give us a better insight into the possibilities of emotional domotics and the applications that can be created towards the improvement of performance in people’s lives. The objective of this research is to create a positive impact with the application of technology to everyday activities; nonetheless, an ethical problem arises since this can also be applied to control a person’s emotions and shift their decision making.

Keywords: data analysis, emotional domotics, performance improvement, neural network

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Authors: Xu Han, Shanxiong Chen, Shiyu Zhu, Xiaoyu Lin, Fujia Zhao, Dingwang Wang

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Character detection is an important issue for character recognition of ancient Yi books. The accuracy of detection directly affects the recognition effect of ancient Yi books. Considering the complex layout, the lack of standard typesetting and the mixed arrangement between images and texts, we propose a character detection method for ancient Yi books based on connected components and regressive character segmentation. First, the scanned images of ancient Yi books are preprocessed with nonlocal mean filtering, and then a modified local adaptive threshold binarization algorithm is used to obtain the binary images to segment the foreground and background for the images. Second, the non-text areas are removed by the method based on connected components. Finally, the single character in the ancient Yi books is segmented by our method. The experimental results show that the method can effectively separate the text areas and non-text areas for ancient Yi books and achieve higher accuracy and recall rate in the experiment of character detection, and effectively solve the problem of character detection and segmentation in character recognition of ancient books.

Keywords: CCS concepts, computing methodologies, interest point, salient region detections, image segmentation

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Authors: Chukwuma Mgboji

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Since the advent of Artificial Intelligence, robots have become a major stay in developing societies. Robots are deployed in Education, Health, Food and in other spheres of life. Nigeria a country in West Africa has a very low profile in the advancement of Artificial Intelligence especially in the grass roots. The benefits of Artificial intelligence are not fully maximised and harnessed. Advances in artificial intelligence are perceived as impossible or observed as irrelevant. This study seeks to ascertain the needed skills for the development of artificialintelligence amongst secondary schools in Nigeria. The study focused on South East Nigeria with Five states namely Imo, Abia, Ebonyi, Anambra and Enugu. The sample size is 1000 students drawn from Five Government owned Universities offering Computer Science, Computer Education, Electronics Engineering across the Five South East states. Survey method was used to solicit responses from respondents. The findings from the study identified mathematical skills, analytical skills, problem solving skills, computing skills, programming skills, algorithm skills amongst others. The result of this study to the best of the author’s knowledge will be highly beneficial to all stakeholders involved in the advancements and development of artificial intelligence.

Keywords: artificial intelligence, secondary school, robotics, skills

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Authors: Mojtaba Valinataj

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Reversible logic as a new favorable design domain can be used for various fields especially creating quantum computers because of its speed and intangible power consumption. However, its susceptibility to a variety of environmental effects may lead to yield the incorrect results. In this paper, because of the importance of multiplication operation in various computing systems, some novel reversible logic array multipliers are proposed with error detection capability by incorporating the parity-preserving gates. The new designs are presented for two main parts of array multipliers, partial product generation and multi-operand addition, by exploiting the new arrangements of existing gates, which results in two signed parity-preserving array multipliers. The experimental results reveal that the best proposed 4×4 multiplier in this paper reaches 12%, 24%, and 26% enhancements in the number of constant inputs, number of required gates, and quantum cost, respectively, compared to previous design. Moreover, the best proposed design is generalized for n×n multipliers with general formulations to estimate the main reversible logic criteria as the functions of the multiplier size.

Keywords: array multipliers, Baugh-Wooley method, error detection, parity-preserving gates, quantum computers, reversible logic

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Authors: Zahira Anane, Abdelhafid Bayadi

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Corona in the HV overhead transmission lines is an important source of attenuation and distortion of overvoltage surges. This phenomenon of distortion, which is superimposed on the distortion by skin effect, is due to the dissipation of energy by injection of space charges around the conductor, this process with place as soon as the instantaneous voltage exceeds the threshold voltage of the corona effect conductors. This paper presents a mathematical model to determine the corona inception voltage, the critical electric field and the corona radius, to predict the capacitive changes at conductor of transmission line due to corona. This model has been incorporated into the Alternative Transients Program version of the Electromagnetic Transients Program (ATP/EMTP) as a user defined component, using the MODELS interface with NORTON TYPE94 of this program and using the foreign subroutine. For obtained the displacement of corona charge hell, dichotomy mathematical method is used for this computation. The present corona model can be used for computing of distortion and attenuation of transient overvoltage waves being propagated in a transmission line of the very high voltage electric power.

Keywords: high voltage, corona, Type94 NORTON, dichotomy, ATP/EMTP, MODELS, distortion, foreign model

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Authors: Aidan J. Bowes, Reaz Hasan

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The automotive industry is continually aiming to develop the aerodynamics of car body design. This may be for a variety of beneficial reasons such as to increase speed or fuel efficiency by reducing drag. However recently there has been a greater amount of focus on wind noise produced while driving. Designers in this industry seek a combination of both simplicity of approach and overall effectiveness. This combined with the growing availability of commercial CFD (Computational Fluid Dynamics) packages is likely to lead to an increase in the use of RANS (Reynolds Averaged Navier-Stokes) based CFD methods. This is due to these methods often being simpler than other CFD methods, having a lower demand on time and computing power. In this investigation the effectiveness of turbulent flow and acoustic noise prediction using RANS based methods has been assessed for different wing mirror geometries. Three different RANS based models were used, standard k-ε, realizable k-ε and k-ω SST. The merits and limitations of these methods are then discussed, by comparing with both experimental and numerical results found in literature. In general, flow prediction is fairly comparable to more complex LES (Large Eddy Simulation) based methods; in particular for the k-ω SST model. However acoustic noise prediction still leaves opportunities for more improvement using RANS based methods.

Keywords: acoustics, aerodynamics, RANS models, turbulent flow

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Authors: Yusef Hedjazi, Saeedeh Nazari Nooghabi

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New information and communication technologies (ICT) as one of the main needs of Faculty members in the process of teaching and learning has used in Irans higher education system since 2000.The main purpose of this study is to investigate the role of information and communication technologies (ICT) in teaching performance of Agricultural and Natural Resources Faculties at University of Tehran. The statistical population of the study consisted of all 250 faculties in Agriculture and Natural Resources Colleges and a questionnaire was used to collect data. The reliability of the questionnaire was confirmed by computing of Cronbachs Alpha coefficient at greater than .72. The study showed a significant relationship between agricultural Faculty members teaching performance and competency in using ICT. The results of the regression analysis also explained 51.7% of the variance, teaching performance. The six independent variables that accounted for the explained variance were experience in using educational websites or software, use of educational multimedia (e.g. film and CD, etc), making a presentation using PowerPoint, familiarity with online education websites, using News group to discuss on educational subjects with colleagues and students, and using Electronic communication (messengers) to solve studentsproblems.

Keywords: information and communication technologies, agricultural and natural resources, faculties, teaching performance

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Authors: Cheng Zeng, Xia Luo

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Passenger organization has always been an essential part of China's metro operation and management. Facing the massive passenger flow, stations need to improve their intelligence and automation degree by an appropriate integrated system. Based on the existing integrated supervisory control system (ISCS) and simulation software (Anylogic), this paper designs an intelligent passenger organization system (IPOS) for metro stations. Its primary function includes passenger information acquisition, data processing and computing, visualization management, decision recommendations, and decision response based on interlocking equipment. For this purpose, the logical structure and intelligent algorithms employed are particularly devised. Besides, the structure diagram of information acquisition and application module, the application of Anylogic, the case library's function process are all given by this research. Based on the secondary development of Anylogic and existing technologies like video recognition, the IPOS is supposed to improve the response speed and address capacity in the face of emergent passenger flow of metro stations.

Keywords: anylogic software, decision-making support system, intellectualization, ISCS, passenger organization

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Authors: Mustafa Elfituri, Jonathan Cook

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Recently, graph-based computations have become more important in large-scale scientific computing as they can provide a methodology to model many types of relations between independent objects. They are being actively used in fields as varied as biology, social networks, cybersecurity, and computer networks. At the same time, graph problems have some properties such as irregularity and poor locality that make their performance different than regular applications performance. Therefore, parallelizing graph algorithms is a hard and challenging task. Initial evidence is that standard computer architectures do not perform very well on graph algorithms. Little is known exactly what causes this. The Graph500 benchmark is a representative application for parallel graph-based computations, which have highly irregular data access and are driven more by traversing connected data than by computation. In this paper, we present results from analyzing the performance of various example implementations of Graph500, including a shared memory (OpenMP) version, a distributed (MPI) version, and a hybrid version. We measured and analyzed all the factors that affect its performance in order to identify possible changes that would improve its performance. Results are discussed in relation to what factors contribute to performance degradation.

Keywords: graph computation, graph500 benchmark, parallel architectures, parallel programming, workload characterization.

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Authors: Benjamin O. Ehigie, Aderemi Alarape, Nyitor Shenge, Sylvester A. Okhakhume, Timileyin Fashola, Fiyinfunjah Dosumu

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Organisational citizenship behaviour (OCB) is a construct in industrial and organisational behaviour that explains a person's voluntary commitment within an organisation, which is outside the scope of his or her contractual tasks. To attain organisational effectiveness the human factor of production is inevitable, hence the importance of employee behaviour. While the concept of organisational citizenship behavior is mostly discussed in the context of the workplace, it is reasoned that the idea could be reflective in relation to national commitment. Many developing countries in Africa, including Nigeria, suffer economic hardship today not necessarily due to poor resources but bad management of the resources. The mangers of their economies are not committed to the tenets of economic growth but engrossed in fraud, corruption, bribery, and other economic vices. It is this backdrop that necessitated the development and validation of the Ibadan-Nigeria Citizenship Behaviour (I-NCB) Scale. The study adopted a cross-sectional survey (online) research design, using 2404 postgraduate students in the Premier University of the country, with 99.2% being Nigerians and 0.8% non-Nigerians. Gender composition was 1,439 (60%) males and 965 (40%) females, 1201 (50%) were employed while 1203 50% unemployed, 74.2% of the employed were in public paid employment, 19.5% in private sector, and 6.3% were self-employed. Through literature review, 78 items were generated. Using 10 lecturers and 21 students, content and face validity were established respectively. Data collected were subjected to reliability and factor analytic statistics at p < .05 level of significance. Results of the content and face validity at 80% level of item acceptance resulted to 60 items; this was further reduced to 50 after item-total correlation using r=.30 criterion. Divergent validity of r= -.28 and convergent validity of r= .44 were obtained by correlating the I-NCB scale with standardized Counterproductive work behaviour (CWB) scale and Organisational Citizenship Behaviour (OCB) scale among the workers. The reliability coefficients obtained were; Cronbach alpha of internal consistency (α = 0.941) and split-half reliability of r = 0.728. Factor analyses of the I-NCB scale with principal component and varimax rotation yielded five factors when Eigenvalue above 1 were extracted. The factors which accounted for larger proportions of the total variance were given factor names as; Altruistic, Attachment, Affective, Civic responsibility and Allegiance. As much as there are vast journals on citizenship behaviour in organisations, there exists no standardized tool to measure citizenship behaviour of a country. The Ibadan-Nigeria Citizenship Behaviour (I-NCB) scale was consequently developed. The scale could be used to select personnel into political positions and senior administrative positions among career workers in Nigeria, with the aim of determining national commitment to service.

Keywords: counterproductive work behaviour, CWB, Nigeria Citizenship Behaviour, organisational citizenship behaviour, OCB, Ibadan

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Authors: Pratap Sriram Sundar, Chandan Chowdhury, Sagar Kamarthi

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Nature has perfected her designs over 3.5 billion years of evolution. Research fields such as biomimicry, biomimetics, bionics, bio-inspired computing, and nature-inspired designs have explored nature-made artifacts and systems to understand nature’s mechanisms and intelligence. Learning from nature, the researchers have generated sustainable designs and innovation in a variety of fields such as energy, architecture, agriculture, transportation, communication, and medicine. Axiomatic design offers a method to judge if a design is good. This paper analyzes design aspects of one of the nature’s amazing object: chicken egg. The functional requirements (FRs) of components of the object are tabulated and mapped on to nature-chosen design parameters (DPs). The ‘independence axiom’ of the axiomatic design methodology is applied to analyze couplings and to evaluate if eggs’ design is good (i.e., uncoupled design) or bad (i.e., coupled design). The analysis revealed that eggs design is a good design, i.e., uncoupled design. This approach can be applied to any nature’s artifacts to judge whether their design is a good or a bad. This methodology is valuable for biomimicry studies. This approach can also be a very useful teaching design consideration of biology and bio-inspired innovation.

Keywords: uncoupled design, axiomatic design, nature design, design evaluation

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Authors: Itissam Abuiziah

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In several hydraulic systems, it is necessary to calculate the head losses which depend on the resistance flow friction factor in Darcy equation. Computing the resistance friction is based on implicit Colebrook-White equation which is considered as the standard for the friction calculation, but it needs high computational cost, therefore; several explicit approximation methods are used for solving an implicit equation to overcome this issue. It follows that the relative error is used to determine the most accurate method among the approximated used ones. Steel, cast iron and polyethylene pipe materials investigated with practical diameters ranged from 0.1m to 2.5m and velocities between 0.6m/s to 3m/s. In short, the results obtained show that the suitable method for some cases may not be accurate for other cases. For example, when using steel pipe materials, Zigrang and Silvester's method has revealed as the most precise in terms of low velocities 0.6 m/s to 1.3m/s. Comparatively, Halland method showed a less relative error with the gradual increase in velocity. Accordingly, the simulation results of this study might be employed by the hydraulic engineers, so they can take advantage to decide which is the most applicable method according to their practical pipe system expectations.

Keywords: Colebrook–White, explicit equation, friction factor, hydraulic resistance, implicit equation, Reynolds numbers

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Authors: Elisa Coraggio, Dawei Han, Weiru Liu, Theo Tryfonas

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Water is one of the most important resources for human society. The world is currently undergoing a wave of urban growth, and pollution problems are of a great impact. Monitoring water quality is a key task for the future of the environment and human species. In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for environmental monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the artificial intelligence algorithm. This study derives the methodology and demonstrates its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for the environment monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a new methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the Artificial Intelligence algorithm. This study derives the methodology and demonstrate its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.

Keywords: artificial intelligence, hydroinformatics, numerical modelling, smart cities, water quality

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Authors: S. Alina Wang

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A Gibsonian approach is used to understand the existential dimensions of the human ecological niche. Then, this existential-Gibsonian framework is applied to rethinking Hacking’s historical analysis of multiple personality disorder. This research culminates in a generalized account of psychiatric illness from an enactivist lens. In conclusion, reflections on the implications of this account on approaches to psychiatric treatment are mentioned. J.J. Gibson’s theory of affordances centered on affordances of sensorimotor varieties, which guide basic behaviors relative to organisms’ vital needs and physiological capacities (1979). Later theorists, notably Neisser (1988) and Rietveld (2014), expanded on the theory of affordances to account for uniquely human activities relative to the emotional, intersubjective, cultural, and narrative aspects of the human ecological niche. This research shows that these affordances are structured by what Haugeland (1998) calls existential commitments, which draws on Heidegger’s notion of dasein (1927) and Merleau-Ponty’s account of existential freedom (1945). These commitments organize the existential affordances that fill an individual’s environment and guide their thoughts, emotions, and behaviors. This system of a priori existential commitments and a posteriori affordances is called existential enactivism. For humans, affordances do not only elicit motor responses and appear as objects with instrumental significance. Affordances also, and possibly primarily, determine so-called affective and cognitive activities and structure the wide range of kinds (e.g., instrumental, aesthetic, ethical) of significances of objects found in the world. Then existential enactivism is applied to understanding the psychiatric phenomenon of multiple personality disorder (precursor of the current diagnosis of dissociative identity disorder). A reinterpretation of Hacking’s (1998) insights into the history of this particular disorder and his generalizations on the constructed nature of most psychiatric illness is taken on. Enactivist approaches sensitive to existential phenomenology can provide a deeper understanding of these matters. Conceptualizing psychiatric illness as strictly a disorder in the head (whether parsed as a disorder of brain chemicals or meaning-making capacities encoded in psychological modules) is incomplete. Rather, psychiatric illness must also be understood as a disorder in the world, or in the interconnected networks of existential affordances that regulate one’s emotional, intersubjective, and narrative capacities. All of this suggests that an adequate account of psychiatric illness must involve (1) the affordances that are the sources of existential hindrance, (2) the existential commitments structuring these affordances, and (3) the conditions of these existential commitments. Approaches to treatment of psychiatric illness would be more effective by centering on the interruption of normalized behaviors corresponding to affordances targeted as sources of hindrance, the development of new existential commitments, and the practice of new behaviors that erect affordances relative to these reformed commitments.

Keywords: affordance, enaction, phenomenology, psychiatry, psychopathology

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Authors: Bill D. Geis

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Suicide wrongful death forensic cases are the fastest rising tort in mental health law. It is estimated that suicide-related cases have accounted for 15% of U.S. malpractice claims since 2006. Most suicide-related personal injury claims fall into the legal category of “wrongful death.” Though mental health experts may be called on to address a range of forensic questions in wrongful death cases, the central consultation that most experts provide is about the negligence element—specifically, the issue of whether the clinician met the clinical standard of care in assessing, treating, and managing the deceased person’s mental health care. Standards of care, varying from U.S. state to state, are broad and address what a reasonable clinician might do in a similar circumstance. This fact leaves the issue of the suicide standard of care, in each case, up to forensic experts to put forth a reasoned estimate of what the standard of care should have been in the specific case under litigation. Because the general state guidelines for standard of care are broad, forensic experts are readily retained to provide scientific and clinical opinions about whether or not a clinician met the standard of care in their suicide assessment, treatment, and management of the case. In the past and in much of current practice, the assessment of suicide has centered on the elicitation of verbalized suicide ideation. Research in recent years, however, has indicated that the majority of persons who end their lives do not say they are suicidal at their last medical or psychiatric contact. Near-term risk assessment—that goes beyond verbalized suicide ideation—is needed. Our previous research employed structural equation modeling to predict lethal suicide risk--eight negative thought patterns (feeling like a burden on others, hopelessness, self-hatred, etc.) mediated by nine transdiagnostic clinical factors (mental torment, insomnia, substance abuse, PTSD intrusions, etc.) were combined to predict acute lethal suicide risk. This structural equation model, the Lethal Suicide Risk Pattern (LSRP), Acute model, had excellent goodness-of-fit [χ2(df) = 94.25(47)***, CFI = .98, RMSEA = .05, .90CI = .03-.06, p(RMSEA = .05) = .63. AIC = 340.25, ***p < .001.]. A further SEQ analysis was completed for this paper, adding a measure of Acute Suicide Ideation to the previous SEQ. Acceptable prediction model fit was no longer achieved [χ2(df) = 3.571, CFI > .953, RMSEA = .075, .90% CI = .065-.085, AIC = 529.550].This finding suggests that, in this additional study, immediate verbalized suicide ideation information was unhelpful in the assessment of lethal risk. The LSRP and other dynamic, near-term risk models (such as the Acute Suicide Affective Disorder Model and the Suicide Crisis Syndrome Model)—going beyond elicited suicide ideation—need to be incorporated into current clinical suicide assessment training. Without this training, the standard of care for suicide assessment is out of sync with current research—an emerging dilemma for the forensic evaluation of suicide wrongful death cases.

Keywords: forensic evaluation, standard of care, suicide, suicide assessment, wrongful death

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Authors: Mahesh Vishwakarma, Sadhana Vishwakarma

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Vocational education includes all kind of education which can help students to acquire skills related to a certain profession, art, or activity so that they are able to exercise that profession, art or activity after acquiring such qualification. However, in this global economy of the modern world, job seekers are expected to have certain soft skills over and above the technical knowledge and skills acquired in their areas of expertise. These soft skills include but not limited to interpersonal communication, understanding, personal attributes, problem-solving, working in team, quick adaptability to the workplace environment, and other. Not only the hands-on, job-related skills, and competencies are now being sought by the employers, but also a complex of attitudinal dispositions and affective traits are being looked by them in their prospective employees. This study was performed to identify the employability skills of technical students from an Industrial Training Centre (ITC) in central India. It also aimed to convey a message to the students currently on the role, that for them to remain relevant in the job market, they would need to constantly adapt to changes and evolving requirements in the work environment, including the use of updated technologies. Five hypotheses were formulated and tested on the employability skills of students as a function of gender, trade, work experience, personal attributes, and IT skills. Data were gathered with the help of center’s training officers who approached 200 recently graduated students from the center and administered the instrument to students. All 200 respondents returned the completed instrument. The instrument used for the study consisted of 2 sections; demographic details and employability skills. To measure the employability skills of the trainees, the instrument was developed by referring to the several instruments developed by the past researchers for similar studies. The 1st section of the instrument of demographic details recorded age, gender, trade, year of passing, interviews faced, and employment status of the respondents. The 2nd section of the instrument on employability skills was categorized into seven specific skills: basic vocational skills; personal attributes; imagination skills; optimal management of resources; information-technology skills; interpersonal skills; adapting to new technologies. The reliability and validity of the instrument were checked. The findings revealed valuable information on the relationship and interdependence of vocational education and employability skills of students in the central Indian scenario. The findings revealed a valuable information on supplementing the existing vocational education programs with few soft skills and competencies so as to develop a superior workforce much better equipped to face the job market. The findings of the study can be used as an example by the management of government and private industrial training centers operating in the other parts of the Asian region. Future research can be undertaken on a greater population base from different geographical regions and backgrounds for an enhanced outcome.

Keywords: employability skills, vocational education, industrial training centers, students

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Authors: Chryssa Thermolia, Ekaterini S. Bei, Stelios Sotiriadis, Kostas Stravoskoufos, Euripides G. M. Petrakis

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Moving into a new era of healthcare, new tools and devices are developed to extend and improve health services, such as remote patient monitoring and risk prevention. In this concept, Internet of Things (IoT) and Cloud Computing present great advantages by providing remote and efficient services, as well as cooperation between patients, clinicians, researchers and other health professionals. This paper focuses on patients suffering from bipolar disorder, a brain disorder that belongs to a group of conditions called effective disorders, which is characterized by great mood swings.We exploit the advantages of Semantic Web and Cloud Technologies to develop a patient monitoring system to support clinicians. Based on intelligently filtering of evidence-knowledge and individual-specific information we aim to provide treatment notifications and recommended function tests at appropriate times or concluding into alerts for serious mood changes and patient’s non-response to treatment. We propose an architecture, as the back-end part of a cloud platform for IoT, intertwining intelligence devices with patients’ daily routine and clinicians’ support.

Keywords: bipolar disorder, intelligent systems patient monitoring, semantic web technologies, healthcare

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Authors: A. Grilec, S. Petrak, M. Mahnic Naglic

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Technological development and the globalization in production and sales of clothing in the last decade have significantly influenced the changes in consumer relationship with the industrial-fashioned apparel and in the way of clothing purchasing. The Internet sale of clothing is in a constant and significant increase in the global market, but the possibilities offered by modern computing technologies in the customization segment are not yet fully involved, especially according to the individual customer requirements and body sizes. Considering the growing trend of online shopping, the main goal of this paper is to investigate the differences in customer perceptions towards online apparel shopping and particularly to discover the main differences in perceptions between customers regarding three different body sizes. In order to complete the research goal, the quantitative study on the sample of 85 Croatian consumers was conducted in 2017 in Zagreb, Croatia. Respondents were asked to indicate their level of agreement according to a five-point Likert scale ranging from strongly disagree (1) to strongly agree (5). To analyze attitudes of respondents, simple and descriptive statistics were used. The main findings highlight the differences in respondent perception of 3D body scanning, using 3D body scanning in Internet shopping, online apparel shopping habits regarding their body sizes.

Keywords: consumer behavior, Internet, 3D body scanning, body types

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Authors: Mário Ernesto Sitoe, Orlando Zacarias

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University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: evasion and retention, cross-validation, bagging, stacking

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Authors: A. Bayaga

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This research provides a technical account of estimating Transition Probability using Time-homogeneous Markov Jump Process applying by South African HIV/AIDS data from the Statistics South Africa. It employs Maximum Likelihood Estimator (MLE) model to explore the possible influence of Transition Probability of mortality cases in which case the data was based on actual Statistics South Africa. This was conducted via an integrated demographic and epidemiological model of South African HIV/AIDS epidemic. The model was fitted to age-specific HIV prevalence data and recorded death data using MLE model. Though the previous model results suggest HIV in South Africa has declined and AIDS mortality rates have declined since 2002 – 2013, in contrast, our results differ evidently with the generally accepted HIV models (Spectrum/EPP and ASSA2008) in South Africa. However, there is the need for supplementary research to be conducted to enhance the demographic parameters in the model and as well apply it to each of the nine (9) provinces of South Africa.

Keywords: AIDS mortality rates, epidemiological model, time-homogeneous markov jump process, transition probability, statistics South Africa

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Authors: Yoji Yamato

Abstract:

In this paper, we propose an automatic verification technology of software patches for user virtual environments on IaaS Cloud to decrease verification costs of patches. In these days, IaaS services have been spread and many users can customize virtual machines on IaaS Cloud like their own private servers. Regarding to software patches of OS or middleware installed on virtual machines, users need to adopt and verify these patches by themselves. This task increases operation costs of users. Our proposed method replicates user virtual environments, extracts verification test cases for user virtual environments from test case DB, distributes patches to virtual machines on replicated environments and conducts those test cases automatically on replicated environments. We have implemented the proposed method on OpenStack using Jenkins and confirmed the feasibility. Using the implementation, we confirmed the effectiveness of test case creation efforts by our proposed idea of 2-tier abstraction of software functions and test cases. We also evaluated the automatic verification performance of environment replications, test cases extractions and test cases conductions.

Keywords: OpenStack, cloud computing, automatic verification, jenkins

Procedia PDF Downloads 471

Authors: T. S. Terence Ma, Irene T. Ho

Abstract:

Conducting adequate assessment of the challenges students with ASD (Autism Spectrum Disorder) face and the support they need is imperative for promoting their school adjustment. Students with ASD often show deficits in communication, social interaction, emotional regulation, and self-management in learning. While targeting these areas in intervention is often helpful, we argue that not enough attention has been paid to weak self-regulation being a key factor underlying their manifest difficulty in all these areas. Self-regulation refers to one’s ability to moderate their behavioral or affective responses without assistance from others. Especially for students with high functioning autism, who often show problems not so much in acquiring the needed skills but rather in applying those skills appropriately in everyday problem-solving, self-regulation becomes a key to successful adjustment in daily life. Therefore, a greater understanding of the construct of self-regulation, its relationship with other daily skills, and its role in school functioning for students with ASD would generate insights on how students’ school adjustment could be promoted more effectively. There were two focuses in this study. Firstly, we examined the extent to which self-regulation is a distinct construct that is differentiable from other daily skills and the most salient indicators of this construct. Then we tested a model of relationships between self-regulation and other daily school skills as well as their relative and combined effects on school adjustment. A total of 1,345 Grade1 to Grade 6 students with ASD attending mainstream schools in Hong Kong participated in the research. In the first stage of the study, teachers filled out a questionnaire consisting of 136 items assessing a wide range of student skills in social, emotional and learning areas. Results from exploratory factor analysis (EFA) with 673 participants and subsequent confirmatory factor analysis (CFA) with another group of 672 participants showed that there were five distinct factors of school skills, namely (1) communication skills, (2) pro-social behavior, (3) emotional skills, (4) learning management, and (5) self-regulation. Five scales representing these skill dimensions were generated. In the second stage of the study, a model postulating the mediating role of self-regulation for the effects of the other four types of skills on school adjustment was tested with structural equation modeling (SEM). School adjustment was defined in terms of the extent to which the student is accepted well in school, with high engagement in school life and self-esteem as well as good interpersonal relationships. A 5-item scale was used to assess these aspects of school adjustment. Results showed that communication skills, pro-social behavior, emotional skills and learning management had significant effects on school adjustment only indirectly through self-regulation, and their total effects were found to be not high. The results indicate that support rendered to students with ASD focusing only on the training of well-defined skills is not adequate for promoting their inclusion in school. More attention should be paid to the training of self-management with an emphasis on the application of skills backed by self-regulation. Also, other non-skill factors are important in promoting inclusive education.

Keywords: autism, assessment, factor analysis, self-regulation, school adjustment

Procedia PDF Downloads 98

Authors: Shu Yin, Zhiyang Ding, Jianzhong Huang, Xiaojun Ruan, Xiaomin Zhu, Xiao Qin

Abstract:

Since large-scale and data-intensive applications have been widely deployed, there is a growing demand for high-performance storage systems to support data-intensive applications. Compared with traditional storage systems, next-generation systems will embrace dedicated processor to reduce computational load of host machines and will have hybrid combinations of different storage devices. The advent of flash- memory-based solid state disk has become a critical role in revolutionizing the storage world. However, instead of simply replacing the traditional magnetic hard disk with the solid state disk, it is believed that finding a complementary approach to corporate both of them is more challenging and attractive. This paper explores an idea of active storage, an emerging new storage configuration, in terms of the architecture and design, the parallel processing capability, the cooperation of other machines in cluster computing environment, and a disk configuration, the hybrid combination of different types of disk drives. Experimental results indicate that the proposed HcDD achieves better I/O performance and longer storage system lifespan.

Keywords: arallel storage system, hybrid storage system, data inten- sive, solid state disks, reliability

Procedia PDF Downloads 431

Authors: Manuel I. Capel, Antonio Tomeu, Alberto Salguero

Abstract:

Tumor growth from a transformed cancer-cell up to a clinically apparent mass spans through a range of spatial and temporal magnitudes. Through computer simulations, Cellular Automata (CA) can accurately describe the complexity of the development of tumors. Tumor development prognosis can now be made -without making patients undergo through annoying medical examinations or painful invasive procedures- if we develop appropriate CA-based software tools. In silico testing mainly refers to Computational Biology research studies of application to clinical actions in Medicine. To establish sound computer-based models of cellular behavior, certainly reduces costs and saves precious time with respect to carrying out experiments in vitro at labs or in vivo with living cells and organisms. These aim to produce scientifically relevant results compared to traditional in vitro testing, which is slow, expensive, and does not generally have acceptable reproducibility under the same conditions. For speeding up computer simulations of cellular models, specific literature shows recent proposals based on the CA approach that include advanced techniques, such the clever use of supporting efficient data structures when modeling with deterministic stochastic cellular automata. Multiparadigm and multiscale simulation of tumor dynamics is just beginning to be developed by the concerned research community. The use of stochastic cellular automata (SCA), whose parallel programming implementations are open to yield a high computational performance, are of much interest to be explored up to their computational limits. There have been some approaches based on optimizations to advance in multiparadigm models of tumor growth, which mainly pursuit to improve performance of these models through efficient memory accesses guarantee, or considering the dynamic evolution of the memory space (grids, trees,…) that holds crucial data in simulations. In our opinion, the different optimizations mentioned above are not decisive enough to achieve the high performance computing power that cell-behavior simulation programs actually need. The possibility of using multicore and GPU parallelism as a promising multiplatform and framework to develop new programming techniques to speed-up the computation time of simulations is just starting to be explored in the few last years. This paper presents a model that incorporates parallel processing, identifying the synchronization necessary for speeding up tumor growth simulations implemented in Java and C++ programming environments. The speed up improvement that specific parallel syntactic constructs, such as executors (thread pools) in Java, are studied. The new tumor growth parallel model is proved using implementations with Java and C++ languages on two different platforms: chipset Intel core i-X and a HPC cluster of processors at our university. The parallelization of Polesczuk and Enderling model (normally used by researchers in mathematical oncology) proposed here is analyzed with respect to performance gain. We intend to apply the model and overall parallelization technique presented here to solid tumors of specific affiliation such as prostate, breast, or colon. Our final objective is to set up a multiparadigm model capable of modelling angiogenesis, or the growth inhibition induced by chemotaxis, as well as the effect of therapies based on the presence of cytotoxic/cytostatic drugs.

Keywords: cellular automaton, tumor growth model, simulation, multicore and manycore programming, parallel programming, high performance computing, speed up

Procedia PDF Downloads 230

Authors: Zaia Derrar Kaddour

Abstract:

The study of a beam throughout an optical path is generally achieved by means of diffraction integral. Unfortunately, in some problems, this tool turns out to be not very friendly and hard to implement. Instead, the beam expansion method for computing field profiles appears to be an interesting alternative. The beam expansion method consists of expanding the field pattern as a series expansion in a set of orthogonal functions. Propagating each individual component through a circuit and adding up the derived elements leads easily to the result. The problem is then reduced to finding how the expansion coefficients change in a circuit. The beam expansion method requires a systematic study of each type of optical element that can be met in the considered optical path. In this work, we analyze the following fundamental elements: first order optical systems, hard apertures and waveguides. We show that the former element type is completely defined thanks to the Gouy phase shift expression we provide and the latters require a suitable mode conversion. For endorsing the usefulness and relevance of the beam expansion approach, we show here some of its applications such as the treatment of the thermal lens effect and the study of unstable resonators.

Keywords: gouy phase shift, modes, optical resonators, unstable resonators

Procedia PDF Downloads 49

Authors: Mohammed Habchi, Sidi Mohammed Mesli, Rafik Benallal, Mohammed Kotbi

Abstract:

On the basis of four partial correlation functions and some geometric constraints obtained from neutron scattering experiments, a Reverse Monte Carlo (RMC) simulation has been performed in the study of the aqueous electrolyte LiCl6H2O at the glassy state. The obtained 3-dimensional model allows computing pair radial and orientational distribution functions in order to explore the structural features of the system. Unrealistic features appeared in some coordination peaks. To remedy to this, we use the Hybrid Reverse Monte Carlo (HRMC), incorporating an additional energy constraint in addition to the usual constraints derived from experiments. The energy of the system is calculated using an Environment Dependence Interaction Potential (EDIP). Ions effects is studied by comparing correlations between water molecules in the solution and in pure water at room temperature Our results show a good agreement between experimental and computed partial distribution functions (PDFs) as well as a significant improvement in orientational distribution curves.

Keywords: LiCl6H2O, glassy state, RMC, HRMC

Procedia PDF Downloads 453

Authors: Der-Feng Guo

Abstract:

Optoelectronic switches have attracted a considerable attention in the semiconductor research field due to their potential applications in optical computing systems and optoelectronic integrated circuits (OEICs). With high gains and high-speed operations, npn heterostructures can be used to produce promising optoelectronic switches. It is known that the bulk barrier and heterostructure-induced potential spike act important roles in the characteristics of the npn heterostructures. To investigate the effects of bulk barrier and potential spike heights on the optoelectronic switching of the npn heterostructures, GaAs/InGaP and AlGaAs/GaAs/InAlGaP npn heterostructural optoelectronic switches (HSOSs) have been fabricated in this work. It is seen that the illumination decreases the switching voltage Vs and increases the switching current Is, and thus the OFF state is under dark and ON state under illumination in the optical switching of the GaAs/InGaP HSOS characteristics. But in the AlGaAs/GaAs/InAlGaP HSOS characteristics, the Vs and Is present contrary trends, and the OFF state is under illumination and ON state under dark. The studied HSOSs show quite different switching variations with incident light, which are mainly attributed to the bulk barrier and potential spike heights affected by photogenerated carriers.

Keywords: bulk barrier, heterostructure, optoelectronic switch, potential spike

Procedia PDF Downloads 229

Authors: Faith-Michael E. Uzoka, Boluwaji A. Akinnuwesi, Taiwo Amoo, Flora Aladi, Stephen Fashoto, Moses Olaniyan, Joseph Osuji

Abstract:

The overarching aim of this study is to develop a soft-computing system for the differential diagnosis of tropical diseases. These conditions are of concern to health bodies, physicians, and the community at large because of their mortality rates, and difficulties in early diagnosis due to the fact that they present with symptoms that overlap, and thus become ‘confusable’. We report on the first phase of our study, which focuses on the development of a fuzzy cognitive map model for early differential diagnosis of tropical diseases. We used malaria as a case disease to show the effectiveness of the FCM technology as an aid to the medical practitioner in the diagnosis of tropical diseases. Our model takes cognizance of manifested symptoms and other non-clinical factors that could contribute to symptoms manifestations. Our model showed 85% accuracy in diagnosis, as against the physicians’ initial hypothesis, which stood at 55% accuracy. It is expected that the next stage of our study will provide a multi-disease, multi-symptom model that also improves efficiency by utilizing a decision support filter that works on an algorithm, which mimics the physician’s diagnosis process.

Keywords: medical diagnosis, tropical diseases, fuzzy cognitive map, decision support filters, malaria differential diagnosis

Procedia PDF Downloads 305

Authors: Phuoc Si Nguyen

Abstract:

Infinite impulse response (IIR) filters can be designed from an analogue low pass prototype by using frequency transformation in the s-domain and bilinear z-transformation with pre-warping frequency; this method is known as frequency transformation from the s-domain to the z-domain. This paper will introduce a new method to transform an IIR digital filter to another type of IIR digital filter (low pass, high pass, band pass, band stop or narrow band) using a technique based on inverse bilinear z-transformation and inverse matrices. First, a matrix equation is derived from inverse bilinear z-transformation and Pascal’s triangle. This Low Pass Digital to Digital Filter Pascal Matrix Equation is used to transform a low pass digital filter to other digital filter types. From this equation and the inverse matrix, a Digital to Digital Filter Pascal Matrix Equation can be derived that is able to transform any IIR digital filter. This paper will also introduce some specific matrices to replace the inverse matrix, which is difficult to determine due to the larger size of the matrix in the current method. This will make computing and hand calculation easier when transforming from one IIR digital filter to another in the digital domain.

Keywords: bilinear z-transformation, frequency transformation, inverse bilinear z-transformation, IIR digital filters

Procedia PDF Downloads 407