Search results for: training specificity

Authors: Faisal Ali, Mansoor Shuakat, Cui Lirong, Rabia Riasat

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HR is a department that enhances the power of employee performance in regard with their services, and to make the organization strategic objectives. The main concern of HR department is to organize people, focus on policies and their system. The empirical study shows the relationship between HRM (Human Resource Management practices) and their Job Satisfaction. The Hypothesis is testing on a sample of overall 320 employees of 5 different Pharmaceutical departments of different organizations in Pakistan. The important thing as Relationship of Job satisfaction with HR Practices, Impact on Job Satisfaction with HR Practices, Participation of Staff of Different Departments, HR Practices effects the Job satisfaction, Recruitment or Hiring and Selection effects the Job satisfaction, Training and Development, Performance and Appraisals, Compensation affects the Job satisfaction , and Industrial Relationships affects the Job satisfaction. After finishing all data analysis, the conclusion is that lots of Job related activities raise the confidence of Job satisfaction of employees with their salary and other benefits. Implications of HR practices discussed, Limitations, and future research study also offered write the main conclusion for your paper.

Keywords: HRM, HR practices, job satisfaction, TQM

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Authors: Martyna Chotomska, Aleksandra Studzinska, Marta Lisowska, Justyna Szubert, Aleksandra Tabis, Jacek Bania, Arkadiusz Miazek

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Objectives: Assessing antigen-specific T cell responses is of utmost importance for the pre-clinical testing of prototype vaccines against intracellular pathogens and tumor antigens. Mainly two types of in vitro assays are used for this purpose 1) enzyme-linked immunospot (ELISpot) and 2) intracellular cytokine staining (ICS). Both are time-consuming, relatively expensive, and require manual dexterity. Here, we assess if a straightforward detection of luciferase activity in blood samples of transgenic reporter mice expressing a secreted Lucia luciferase under the transcriptional control of IFN-γ promoter parallels the sensitivity of IFNγ ELISpot assay. Methods: IFN-γ-LUCIA mouse strain carrying multiple copies of Lucia luciferase transgene under the transcriptional control of IFNγ minimal promoter were generated by pronuclear injection of linear DNA. The specificity of transgene expression and mobilization was assessed in vitro using transgenic splenocytes exposed to various mitogens. The IFN-γ-LUCIA mice were immunized with 50mg of ovalbumin (OVA) emulsified in incomplete Freund’s adjuvant three times every two weeks by subcutaneous injections. Blood samples were collected before and five days after each immunization. Luciferase activity was assessed in blood serum. Peripheral blood mononuclear cells were separated and assessed for frequencies of OVA-specific IFNγ-secreting T cells. Results: We show that in vitro cultured splenocytes of IFN-γ-LUCIA mice respond by 2 and 3 fold increase in secreted luciferase activity to T cell mitogens concanavalin A and phorbol myristate acetate, respectively but fail to respond to B cell-stimulating E.coli lipopolysaccharide. Immunization of IFN-γ-LUCIA mice with OVA leads to over 4 fold increase in luciferase activity in blood serum five days post-immunization with a barely detectable increase in OVA-specific, IFNγ-secreting T cells by ELISpot. Second and third immunizations, further increase the luciferase activity and coincidently also increase the frequencies of OVA-specific T cells by ELISpot. Conclusions: We conclude that minimally invasive monitoring of luciferase secretions in blood serum of IFN-γ-LUCIA mice constitutes a sensitive method for evaluating primary and memory Th1 responses to protein antigens. As such, this method may complement existing methods for rapid immunogenicity assessment of prototype vaccines.

Keywords: ELISpot, immunogenicity, interferon-gamma, reporter mice, vaccines

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Authors: Salma Akter, Md. Kamal Uddin

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This study aims to demonstrate how top-down shelter policy and its resultant dwelling environment leads to ‘everyday compromise’ by the grassroots according to subjective (satisfaction) and objective (physical design elements and physical environmental elements) indicators, which are measured across three levels of the settlement; macro (Community), meso (Neighborhood or shelter/built environment) and micro (family). Ashrayan Prakalpa is a resettlement /housing project of Government of Bangladesh for providing shelters and human resources development activities like education, microcredit, and training programme to landless, homeless and rootless people. Despite the integrated nature of the shelter policies (comprises poverty alleviation, employment opportunity, secured tenure, and livelihood training), the ‘quality of life’ issue at the different levels of settlements becomes questionable. As dwellers of shelter units (although formally termed as ‘barracks’ rather shelter or housing) remain on the receiving end of government’s resettlement policies, they often involve with spatial-physical and socio-economic negotiation and assume curious forms of spatial practice, which often upholds contradiction with policy planning. Thus, policy based shelter force dwellers to persistently compromise with their provided built environments both in overtly and covertly. Compromising with prescribed designed space and facilities across living places articulated their negotiation with the quality of allocated space, built form and infrastructures, which in turn exert as less quality of life. The top-down shelter project, Dakshin Chandani Mahal Ashrayan Prakalpa at Dighalia Upazila, the study area located at the Eastern fringe area of Khulna, Bangladesh, is still in progress to resettle internally displaced and homeless people. In terms of methodology, this research is primarily exploratory and adopts a case study method, and an analytical framework is developed through the deductive approach for evaluating the quality of life. Secondary data have been obtained from housing policy analysis and relevant literature review, while key informant interview, focus group discussion, necessary drawings and photographs and participant observation across dwelling, neighborhood, and community level have also been administered as primary data collection methodology. Findings have revealed that various shortages, inadequacies, and negligence of policymakers force to compromise with allocated designed space, physical infrastructure and economic opportunities across dwelling, neighborhood and mostly community level. Thus, the outcome of this study can be beneficial for a global-level understating of the compromising the ‘quality of life’ under top-down shelter policy. Locally, for instance, in the context of Bangladesh, it can help policymakers and concerned authorities to formulate the shelter policies and take initiatives to improve the well-being of marginalized.

Keywords: Ashrayan Prakalpa, compromise, displaced people, quality of life

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Authors: Daniela Tapusi, Adrian Andronic, Naomi Tufan, Ruxandra Erbașu, Ioana Teodorescu

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The proposed theme of this article falls within the policy of reducing carbon emissions imposed by the ‘Green New Deal’ by replacing structural elements made of energy-intensive materials with ecological materials. In this sense, wood has many qualities (high strength/mass and stiffness/mass ratio, low specific gravity, recovery/recycling) that make it competitive with classic building materials. The topological optimization of the linear glulam elements, resulting from different types of analysis (Finite Element Method, simple regression on metamodels), tests on models or by Monte-Carlo simulation, leads to a material reduction of more than 10%. This article proposes a method of obtaining topologically optimized shapes for different types of glued laminated timber beams. The results obtained will constitute the database for AI training.

Keywords: timber, glued laminated timber, artificial-intelligence, environment, carbon emissions

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Authors: Abdulkadir Abu Lawal

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For the dearth of reliable cardinal numerical data, the linked phenomena in productivity indices such as operational costs and company turnovers, etc. could not be investigated. This would not give us insight to the root of productivity problems at unique sites. So, ordinal ranking by professionals who were most directly involved with construction sites was applied for Kendall’s concordance. Responses gathered from independent architects, builders/engineers, and quantity surveyors were herein analyzed. They were responses based on factors that affect sites productivity, and these factors were categorized as head office factors, resource management effectiveness factors, motivational factors, and training/skill development factors. It was found that productivity is low and has to be improved in order to facilitate Nigerian efforts in bridging its infrastructure deficit. The significance of this work is underlined with the Kendall’s coefficient of concordance of 0.78, while remedial measures must be emphasized to stimulate better productivity. Further detailed study can be undertaken by using Fuzzy logic analysis on wider Delphi survey.

Keywords: factors, Kendall's coefficient of concordance, magnitude of agreement, percentage magnitude of dichotomy, ranking variables

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Authors: Maharjan Shree Kumar

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Climate change impacts are observed in all livelihood sectors primarily in agriculture and forestry. Multiple factors have influenced the climate vulnerabilities and adaptations in agricultural at the household level. This study focused on the factors affecting adaptation in agriculture in Madi and Deukhuri valleys of Central and Western Nepal. The systematic random sampling technique was applied to select 154 households in Madi and 150 households in Deukhuri. The main purpose of the study was to analyze the socio-economic factors that either influence or restrain the farmers’ adaptation to climate change at the household level by applying the linear probability model. Based on the analysis, it is revealed that crop diversity, education, training and total land holding (acre) were positively significant for adaptation choices the study sites. Rest of the variables were not significant though indicated positive as expected except age, occupation, ethnicity, family size, and access to credit.

Keywords: adaptation, agriculture, climate, factors, Nepal

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Authors: Manar Aslan, Ayfer Karaaslan, Serap Selçuk

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The research was conducted in order to determine the organizational socialization levels of nurses working in hospitals in the form of a descriptive study. The research population was composed of nurses employed in public and private sector hospitals in the province of Konya with 0-3 years of professional experience in the hospitals (N=1200); and the sample was composed of 495 nurses that accepted to take part in the study voluntarily. Organizational Socialization Scale which was developed by Haueter, Macan and Winter (2003) and whose validity-reliability in Turkish was analyzed by Ataman (2012) was used. Statistical evaluation of data was conducted in SPSS.16 software. The results of the study revealed that the total score taken by nurses at the organizational socialization scale was 262.95; and this was close to the maximum score. Particularly the departmental socialization sub-dimension proved to be higher in comparison to the other two dimensions (organization socialization and task socialization). Statistically meaningful differences were found in the levels of organization socialization in relation to the status of organizational orientation training, level of education and age group.

Keywords: nurses, newcomers, organizational socialization, total score

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Authors: Li Zhang, Yuehong Su

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Lightpipe as a mature solar light tube technique has been employed worldwide. Accurately assessing the performance of lightpipe and evaluate daylighting available has been a challenging topic. Previous research had used regression model and computational simulation methods to estimate the performance of lightpipe. However, due to the nonlinear nature of solar light transferring in lightpipe, the methods mentioned above express inaccurate and time-costing issues. In the present study, a neural network model as an alternative method is investigated to predict the transmittance of lightpipe. Four types of commercial lightpipe with bended angle 0°, 30°, 45° and 60° are discussed under clear, intermediate and overcast sky conditions respectively. The neural network is generated in MATLAB by using the outcomes of an optical software Photopia simulations as targets for networks training and testing. The coefficient of determination (R²) for each model is higher than 0.98, and the mean square error (MSE) is less than 0.0019, which indicate the neural network strong predictive ability and the use of the neural network method could be an efficient technique for determining the performance of lightpipe.

Keywords: neural network, bended lightpipe, transmittance, Photopia

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Authors: N. Demertzis, J. L. Bowen

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Sepsis is a complex and rapidly evolving condition, resulting from uncontrolled prolonged activation of host immune system due to pathogenic insult. The aim of this study is the development of a multiplex electrochemical sensing platform, capable of detecting both pathogen associated and host immune markers to enable the rapid and definitive diagnosis of sepsis. A combination of aptamers and molecular imprinting approaches have been employed to generate sensing systems for lipopolysaccharide (LPS), c-reactive protein (CRP) and procalcitonin (PCT). Gold working electrodes were mechanically polished and electrochemically cleaned with 0.1 M sulphuric acid using cyclic voltammetry (CV). Following activation, a self-assembled monolayer (SAM) was generated, by incubating the electrodes with a thiolated anti-LPS aptamer / dithiodibutiric acid (DTBA) mixture (1:20). 3-aminophenylboronic acid (3-APBA) in combination with the anti-LPS aptamer was used for the development of the hybrid molecularly imprinted sensor (apta-MIP). Aptasensors, targeting PCT and CRP were also fabricated, following the same approach as in the case of LPS, with mercaptohexanol (MCH) replacing DTBA. In the case of the CRP aptasensor, the SAM was formed following incubation of a 1:1 aptamer: MCH mixture. However, in the case of PCT, the SAM was formed with the aptamer itself, with subsequent backfilling with 1 μM MCH. The binding performance of all systems has been evaluated using electrochemical impedance spectroscopy. The apta-MIP’s polymer thickness is controlled by varying the number of electropolymerisation cycles. In the ideal number of polymerisation cycles, the polymer must cover the electrode surface and create a binding pocket around LPS and its aptamer binding site. Less polymerisation cycles will create a hybrid system which resembles an aptasensor, while more cycles will be able to cover the complex and demonstrate a bulk polymer-like behaviour. Both aptasensor and apta-MIP were challenged with LPS and compared to conventional imprinted (absence of aptamer from the binding site, polymer formed in presence of LPS) and non-imprinted polymers (NIPS, absence of LPS whilst hybrid polymer is formed). A stable LPS aptasensor, capable of detecting down to 5 pg/ml of LPS was generated. The apparent Kd of the system was estimated at 17 pM, with a Bmax of approximately 50 pM. The aptasensor demonstrated high specificity to LPS. The apta-MIP demonstrated superior recognition properties with a limit of detection of 1 fg/ml and a Bmax of 100 pg/ml. The CRP and PCT aptasensors were both able to detect down to 5 pg/ml. Whilst full binding performance is currently being evaluated, there is none of the sensors demonstrate cross-reactivity towards LPS, CRP or PCT. In conclusion, stable aptasensors capable of detecting LPS, PCT and CRP at low concentrations have been generated. The realisation of a multiplex panel such as described herein, will effectively contribute to the rapid, personalised diagnosis of sepsis.

Keywords: aptamer, electrochemical impedance spectroscopy, molecularly imprinted polymers, sepsis

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Authors: Fred Mageto

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A great number of children in mainstream schools across Kenya are currently living with emotional, behavioural difficulties. This study aims to explore teachers’ perceptions of children’s emotional and behavioural difficulties (EBD) and their attributions of the causes of EBD. The relevance of this area of study to current educational practice is illustrated in the fact that primary school teachers in Kenya find classroom behaviour problems one of the major difficulties they face. The information presented in this study was gathered from 182 teachers that responded back to the survey, of whom 27 teachers were later interviewed. In general, teachers’ perceptions of EBD reflect personal experience, training, and attitudes. Teachers appear from this study to use words such as indifferent, frightened, withdrawn, aggressive, disobedient, hyperactive, less ambitious, lacking concentration, and academically weak to describe pupils with emotional and behavioural difficulties (EBD). The implications of this study are envisaged as being extremely important to support teachers addressing children’s EBD and shed light on the contributing factors to EBD for a successful teaching-learning process in Libyan primary schools.

Keywords: teachers, children, learning, emotional and behaviour difficulties

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Authors: Nicholas Milburn, Yu Liang, Dalei Wu

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Athlete performance scoring within the climbing do-main presents interesting challenges as the sport does not have an objective way to assign skill. Assessing skill levels within any sport is valuable as it can be used to mark progress while training, and it can help an athlete choose appropriate climbs to attempt. Machine learning-based methods are popular for complex problems like this. The dataset available was composed of dynamic force data recorded during climbing; however, this dataset came with challenges such as data scarcity, imbalance, and it was temporally heterogeneous. Investigated solutions to these challenges include data augmentation, temporal normalization, conversion of time series to the spectral domain, and cross validation strategies. The investigated solutions to the classification problem included light weight machine classifiers KNN and SVM as well as the deep learning with CNN. The best performing model had an 80% accuracy. In conclusion, there seems to be enough information within climbing force data to accurately categorize climbers by skill.

Keywords: classification, climbing, data imbalance, data scarcity, machine learning, time sequence

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Authors: Rachel Nir, Tina Mckee

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In the UK, reliance has been placed on the professions to ‘heal themselves’ in improving equality and diversity. This approach has faltered, in part due to the global economic climate, and stimulus is needed to make faster equality progress. Recent empirical evidence has identified specific diversity barriers, namely: the cost of training; the use of high school grades as a primary selection criteria; the significance of prior work experience in recruitment decisions; and recruitment from elite universities. Students from majority groups and affluent backgrounds are advantaged over their counterparts. We as educators are passionate about resisting this. We believe that education can be a key agent of change. As part of this belief, the presenters have recently designed learning and teaching materials for the 2015/16 academic year. These are aimed at undergraduate law students for the purpose of 1) educating them on career barriers; 2) helping them to develop personal strategies to overcome them; and 3) encouraging them to address their own biases, both conscious and implicit, so that they, themselves, may be fairer employers and managers in the future.

Keywords: career barriers, challenging professional bias, education, elitism, personal student strategies

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Authors: Isa Muhammad Zumo, Musa Lawan

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This study analyzes the land use/land cover changes in Damaturu metropolis from 1986 to 2005. LandSat TM Images of 1986, 1999, and 2005 were used. Built-up lands, agric lands, water body and other lands were created as themes within ILWIS 3.4 software. The images were displayed in False Colour Composite (FCC) for a better visualization and identification of the themes created. Training sample sets were collected based on the ground truth data during field the checks. Statistical data were then extracted from the classified sample set. Area in hectares for each theme was calculated for each year and the result for each land use/land cover types for each study year was compared. From the result, it was found out that built-up areas have a considerable increase from 37.71 hectares in 1986 to 1062.72 hectares in 2005. It has an annual increase rate of approximately 0.34%. The results also reveal that there is a decrease of 5829.66 hectares of other lands (vacant lands) from 1986 to 2005.

Keywords: land use, changes, analysis, environmental pollution

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Authors: Rainner Roweder

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Theme: The present paper aims to analyze the specificity of the judicial evidence linked to the subjects of dignity and personality rights, otherwise known as moral rights, in the determination of the truth and formation of the judicial reasoning in cases concerning these areas. This research is about the way courts in Brazilian domestic law search for truth and handles evidence in cases involving moral rights that are abundant and important in Brazil. The main object of the paper is to analyze the effectiveness of the evidence in the formation of judicial conviction in matters related to morally controverted rights, based on the Brazilian, and as a comparison, the Latin American legal systems. In short, the rights of dignity and personality are moral. However, the evidential legal system expects a rational demonstration of moral rights that generate judicial conviction or persuasion. Moral, in turn, tends to be difficult or impossible to demonstrate in court, generating the problem considered in this paper, that is, the study of the moral demonstration problem as proof in court. In this sense, the more linked to moral, the more difficult to be demonstrated in court that right is, expanding the field of judicial discretion, generating legal uncertainty. More specifically, the new personality rights, such as gender, and their possibility of alteration, further amplify the problem being essentially an intimate manner, which does not exist in the objective, rational evidential system, as normally occurs in other categories, such as contracts. Therefore, evidencing this legal category in court, with the level of security required by the law, is a herculean task. It becomes virtually impossible to use the same evidentiary system when judging the rights researched here; therefore, it generates the need for a new design of the evidential task regarding the rights of the personality, a central effort of the present paper. Methodology: Concerning the methodology, the Method used in the Investigation phase was Inductive, with the use of the comparative law method; in the data treatment phase, the Inductive Method was also used. Doctrine, Legislative, and jurisprudential comparison was the technique research used. Results: In addition to the peculiar characteristics of personality rights that are not found in other rights, part of them are essentially linked to morale and are not objectively verifiable by design, and it is necessary to use specific argumentative theories for their secure confirmation, such as interdisciplinary support. The traditional pragmatic theory of proof, for having an obvious objective character, when applied in the rights linked to the morale, aggravates decisionism and generates legal insecurity, being necessary its reconstruction for morally charged cases, with the possible use of the “predictive theory” ( and predictive facts) through algorithms in data collection and treatment.

Keywords: moral rights, proof, pragmatic proof theory, insufficiency, Brazil

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Authors: Khader S. Al-Aidmat, Venus W. Samawi

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Blurred vision in the misty atmosphere is essential problem which needs to be resolved. To solve this problem, we developed a technique to restore foggy degraded image from its original version using Back-propagation neural network (BP-NN). The suggested technique is based on mapping between foggy scene and its corresponding original scene. Seven different approaches are suggested based on type of features used in image restoration. Features are extracted from spatial and spatial-frequency domain (using DCT). Each of these approaches comes with its own BP-NN architecture depending on type and number of used features. The weight matrix resulted from training each BP-NN represents a fog filter. The performance of these filters are evaluated empirically (using PSNR), and perceptually. By comparing the performance of these filters, the effective features that suits BP-NN technique for restoring foggy images is recognized. This system proved its effectiveness and success in restoring moderate foggy images.

Keywords: artificial neural network, discrete cosine transform, feed forward neural network, foggy image restoration

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Authors: Rana I. Abdulghani, Amera I. Melhum

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With the abnormal growth of the usage of computers over networks and under the consideration or agreement of most of the computer security experts who said that the goal of building a secure system is never achieved effectively, all these points led to the design of the intrusion detection systems(IDS). This research adopts a comparison between two techniques for network intrusion detection, The first one used the (Particles Swarm Optimization) that fall within the field (Swarm Intelligence). In this Act, the algorithm Enhanced for the purpose of obtaining the minimum error rate by amending the cluster centers when better fitness function is found through the training stages. Results show that this modification gives more efficient exploration of the original algorithm. The second algorithm used a (Back propagation NN) algorithm. Finally a comparison between the results of two methods used were based on (NSL_KDD) data sets for the construction and evaluation of intrusion detection systems. This research is only interested in clustering the two categories (Normal and Abnormal) for the given connection records. Practices experiments result in intrude detection rate (99.183818%) for EPSO and intrude detection rate (69.446416%) for BP neural network.

Keywords: IDS, SI, BP, NSL_KDD, PSO

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Authors: Bruno Biagianti, Angela Tseng, Kathy Wannaviroj, Allison Corlett, Megan DuBois, Kyu Lee, Suma Jacob

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Background: ASD is characterized by pervasive Sensory Processing Abnormalities (SPA) and social cognitive deficits that persist throughout the course of the illness and have been linked to functional abnormalities in specific neural systems that underlie the perception, processing, and representation of sensory information. SPA and social cognitive deficits are associated with difficulties in interpersonal relationships, poor development of social skills, reduced social interactions and lower academic performance. Importantly, they can hamper the effects of established evidence-based psychological treatments—including PEERS (Program for the Education and Enrichment of Relationship Skills), a parent/caregiver-assisted, 16-weeks social skills intervention—which nonetheless requires a functional brain capable of assimilating and retaining information and skills. As a matter of fact, some adolescents benefit from PEERS more than others, calling for strategies to increase treatment response rates. Objective: We will present interim data on CICADAS (Care Improving Cognition for ADolescents on the Autism Spectrum)—a clinician-assisted, closed-loop technology mobile application for adolescents with ASD. Via ten mobile assessments, CICADAS captures data on sensory processing abnormalities and associated cognitive deficits. These data populate a machine learning algorithm that tailors the delivery of ten neuroplasticity-based social cognitive training (NB-SCT) exercises targeting sensory processing abnormalities. Methods: In collaboration with the Autism Spectrum and Neurodevelopmental Disorders Clinic at the University of Minnesota, we conducted a fully remote, three-arm, randomized crossover trial with adolescents with ASD to document the acceptability of CICADAS and evaluate its potential as a stand-alone treatment or as a treatment enhancer of PEERS. Twenty-four adolescents with ASD (ages 11-18) have been initially randomized to 16 weeks of PEERS + CICADAS (Arm A) vs. 16 weeks of PEERS + computer games vs. 16 weeks of CICADAS alone (Arm C). After 16 weeks, the full battery of assessments has been remotely administered. Results: We have evaluated the acceptability of CICADAS by examining adherence rates, engagement patterns, and exit survey data. We found that: 1) CICADAS is able to serve as a treatment enhancer for PEERS, inducing greater improvements in sensory processing, cognition, symptom reduction, social skills and behaviors, as well as the quality of life compared to computer games; 2) the concurrent delivery of PEERS and CICADAS induces greater improvements in study outcomes compared to CICADAS only. Conclusion: While preliminary, our results indicate that the individualized assessment and treatment approach designed in CICADAS seems effective in inducing adaptive long-term learning about social-emotional events. CICADAS-induced enhancement of processing and cognition facilitates the application of PEERS skills in the environment of adolescents with ASD, thus improving their real-world functioning.

Keywords: ASD, social skills, cognitive training, mobile app

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Authors: Nihal Murali, Kunal Gupta, Surekha Bhanot

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Training of artificial neural networks (ANNs) using reinforcement learning (RL) techniques is being widely discussed in the robot learning literature. The high model complexity of ANNs along with the model-free nature of RL algorithms provides a desirable combination for many robotics applications. There is a huge need for algorithms that generalize using raw sensory inputs, such as vision, without any hand-engineered features or domain heuristics. In this paper, the standard control problem of line following robot was used as a test-bed, and an ANN controller for the robot was trained on images from a live video feed using Q-learning. A virtual agent was first trained in simulation environment and then deployed onto a robot’s hardware. The robot successfully learns to traverse a wide range of curves and displays excellent generalization ability. Qualitative analysis of the evolution of policies, performance and weights of the network provide insights into the nature and convergence of the learning algorithm.

Keywords: artificial neural networks, q-learning, reinforcement learning, robot learning

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Authors: Hiromi Kawai

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This study investigates the nature of EFL older children’s L2 perceptive and productive abilities using classroom data, in order to find a pedagogical solution to the teaching of L2 sounds at an early stage of learning in a formal school setting. It is still inconclusive whether older children with only EFL formal school instruction at the initial stage of L2 learning are able to attain native-like perception and production in English within the very limited amount of exposure to the target language available. Based on the notion of the lack of study of EFL Japanese children’s acquisition of English segments, the researcher uses a model of L1 speech processing which was developed for investigating L1 English children’s speech and literacy difficulties using a psycholinguistic framework. The model is composed of input channel, output channel, and lexical representation, and examines how a child receives information from spoken or written language, remembers and stores it within the lexical representations and how the child selects and produces spoken or written words. Concerning language universality and language specificity in the language acquisitional process, the aim of finding any sound errors in L1 English children seemed to conform to the author’s intention to find abilities of English sounds in older Japanese children at the novice level of English in an EFL setting. 104 students in Grade 5 (between the ages of 10 and 11 years old) of an elementary school in Tokyo participated in this study. Four tests to measure their perceptive ability and three oral repetition tests to measure their productive ability were conducted with/without reference to lexical representation. All the test items were analyzed to calculate item facility (IF) indices, and correlational analyses and Structural Equation Modeling (SEM) were conducted to examine the relationship between the receptive ability and the productive ability. IF analysis showed that (1) the participants were better at perceiving a segment than producing a segment, (2) they had difficulty in auditory discrimination of paired consonants when one of them does not exist in the Japanese inventory, (3) they had difficulty in both perceiving and producing English vowels, and (4) their L1 loan word knowledge had an influence on their ability to perceive and produce L2 sounds. The result of the Multiple Regression Modeling showed that the two production tests could predict the participants’ auditory ability of real words in English. The result of SEM showed that the hypothesis that perceptive ability affects productive ability was supported. Based on these findings, the author discusses the possible explicit method of teaching English segments to EFL older children in a formal school setting.

Keywords: EFL older children, english segments, perception, production, speech processing system

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Authors: Sandra Mendes

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Social Work has encountered over time with multivariate requests in the field of its action, provisioning frameworks of knowledge and praxis. Over the years, we have observed a transformation of society and, consequently, of the public who deals with the social work practitioners. Both, training and profession have had need to adapt and readapt the ways of doing, bailing up theories to action, while action unfolds emancipation of new theories. The theoretical questioning of this subject lies on classical authors from social sciences, and contemporary authors of Social Work. In fact, both enhance, in the design of social work, an integration and social cohesion function, creating a culture of action and theory, attributing to its method a relevant function, which shall be promoter of social changes in various dimensions of both individual and collective life, as well as scientific knowledge. On the other hand, it is assumed that Social Work, through its professionalism and through the academy, is now closer to distinguish itself from other Social Sciences as an autonomous scientific field, being, however, in the center of power struggles. This paper seeks to fill the gap in social work literature about the study of the scientific field of this area of knowledge.

Keywords: field theory, knowledge, science, social work

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Authors: Omran Alharbi, Victor Lally

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The advantages of the adoption of new technology such as learning management systems (LMSs) in education and teaching methods have been widely recognised. This has led a large number of universities to integrate this type of technology into their daily learning and teaching activities in order to facilitate the education process for both learners and teachers. On the other hand, in some developing countries such as Saudi Arabia, educators have seldom used this technology. As a result, this study was conducted in order to investigate the factors that impede teachers’ use of technology (LMSs) in their teaching in Saudi Arabian institutions. This study used a qualitative approach. Eight participants were invited to take part in this study, and they were asked to give their opinions about the most significant factors that prevented them from integrating technology into their daily activities. The results revealed that a lack of LMS skills, interest in and knowledge about the LMS among teachers were the most significant factors impeding them from using technology in their lessons. The participants suggested that incentive training should be provided to reduce these challenges.

Keywords: LMS, factors, KSA, teachers

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Authors: Merve Begum Terzi, Orhan Arikan, Adnan Abaci, Mustafa Candemir

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Acute myocardial infarction is a major cause of death in the world. Therefore, its fast and reliable diagnosis is a major clinical need. ECG is the most important diagnostic methodology which is used to make decisions about the management of the cardiovascular diseases. In patients with acute myocardial ischemia, temporary chest pains together with changes in ST segment and T wave of ECG occur shortly before the start of myocardial infarction. In this study, a technique which detects changes in ST/T sections of ECG is developed for the early diagnosis of acute myocardial ischemia. For this purpose, a database of real ECG recordings that contains a set of records from 75 patients presenting symptoms of chest pain who underwent elective percutaneous coronary intervention (PCI) is constituted. 12-lead ECG’s of the patients were recorded before and during the PCI procedure. Two ECG epochs, which are the pre-inflation ECG which is acquired before any catheter insertion and the occlusion ECG which is acquired during balloon inflation, are analyzed for each patient. By using pre-inflation and occlusion recordings, ECG features that are critical in the detection of acute myocardial ischemia are identified and the most discriminative features for the detection of acute myocardial ischemia are extracted. A classification technique based on support vector machine (SVM) approach operating with linear and radial basis function (RBF) kernels to detect ischemic events by using ST-T derived joint features from non-ischemic and ischemic states of the patients is developed. The dataset is randomly divided into training and testing sets and the training set is used to optimize SVM hyperparameters by using grid-search method and 10fold cross-validation. SVMs are designed specifically for each patient by tuning the kernel parameters in order to obtain the optimal classification performance results. As a result of implementing the developed classification technique to real ECG recordings, it is shown that the proposed technique provides highly reliable detections of the anomalies in ECG signals. Furthermore, to develop a detection technique that can be used in the absence of ECG recording obtained during healthy stage, the detection of acute myocardial ischemia based on ECG recordings of the patients obtained during ischemia is also investigated. For this purpose, a Gaussian mixture model (GMM) is used to represent the joint pdf of the most discriminating ECG features of myocardial ischemia. Then, a Neyman-Pearson type of approach is developed to provide detection of outliers that would correspond to acute myocardial ischemia. Neyman – Pearson decision strategy is used by computing the average log likelihood values of ECG segments and comparing them with a range of different threshold values. For different discrimination threshold values and number of ECG segments, probability of detection and probability of false alarm values are computed, and the corresponding ROC curves are obtained. The results indicate that increasing number of ECG segments provide higher performance for GMM based classification. Moreover, the comparison between the performances of SVM and GMM based classification showed that SVM provides higher classification performance results over ECG recordings of considerable number of patients.

Keywords: ECG classification, Gaussian mixture model, Neyman–Pearson approach, support vector machine

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Authors: David Oluigbo, Erik Hemberg, Nathan Shwatal, Wenqi Ding, Yin Yuan, Susanna Mierau

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Introduction: Calcium imaging is an established technique in neuroscience research for detecting activity in neural networks. Bursts of action potentials in neurons lead to transient increases in intracellular calcium visualized with fluorescent indicators. Manual identification of cell bodies and their contours by experts typically takes 10-20 minutes per calcium imaging recording. Our aim, therefore, was to design an automated pipeline to facilitate and optimize calcium imaging data analysis. Our pipeline aims to accelerate cell body and contour identification and production of graphical representations reflecting changes in neuronal calcium-based fluorescence. Methods: We created a Python-based pipeline that uses OpenCV (a computer vision Python package) to accurately (1) detect neuron contours, (2) extract the mean fluorescence within the contour, and (3) identify transient changes in the fluorescence due to neuronal activity. The pipeline consisted of 3 Python scripts that could both be easily accessed through a Python Jupyter notebook. In total, we tested this pipeline on ten separate calcium imaging datasets from murine dissociate cortical cultures. We next compared our automated pipeline outputs with the outputs of manually labeled data for neuronal cell location and corresponding fluorescent times series generated by an expert neuroscientist. Results: Our results show that our automated pipeline efficiently pinpoints neuronal cell body location and neuronal contours and provides a graphical representation of neural network metrics accurately reflecting changes in neuronal calcium-based fluorescence. The pipeline detected the shape, area, and location of most neuronal cell body contours by using binary thresholding and grayscale image conversion to allow computer vision to better distinguish between cells and non-cells. Its results were also comparable to manually analyzed results but with significantly reduced result acquisition times of 2-5 minutes per recording versus 10-20 minutes per recording. Based on these findings, our next step is to precisely measure the specificity and sensitivity of the automated pipeline’s cell body and contour detection to extract more robust neural network metrics and dynamics. Conclusion: Our Python-based pipeline performed automated computer vision-based analysis of calcium image recordings from neuronal cell bodies in neuronal cell cultures. Our new goal is to improve cell body and contour detection to produce more robust, accurate neural network metrics and dynamic graphs.

Keywords: calcium imaging, computer vision, neural activity, neural networks

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Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

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Authors: Dominika Collett

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AI applications, such as machine learning, require access to a vast amount of data in the training phase, which can often be the subject of copyright protection. During later usage, the various content with which the application works can be recorded or made available on the basis of which it produces the resulting output. The EU has recently adopted new legislation to secure machine access to protected works under the DSM Directive; but, the issue of machine use of copyright works is not clearly addressed. However, such clarity is needed regarding the increasing importance of AI and its development. Therefore, this paper provides a basic background of the technology used in the development of applications in the field of computer creativity. The second part of the paper then will focus on a legal analysis of machine use of the authors' works from the perspective of existing European and Czech legislation. The main results of the paper discuss the potential collision of existing legislation in regards to machine use of works with special focus on exceptions and limitations. The legal regulation of machine use of copyright work will impact the development of AI technology.

Keywords: copyright, artificial intelligence, legal use, infringement, Czech law, EU law, text and data mining

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Authors: Abdelbasit Gadour

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A great number of children in mainstream schools across Libya are currently living with emotional, behavioral difficulties. This study aims to explore teachers’ perceptions of children’s emotional and behavioral difficulties (EBD) and their attributions of the causes of EBD. The relevance of this area of study to current educational practice is illustrated in the fact that primary school teachers in Libya find classroom behavior problems one of the major difficulties they face. The information presented in this study was gathered from 182 teachers that responded back to the survey, of whom 27 teachers were later interviewed. In general, teachers’ perceptions of EBD reflect personal experience, training, and attitudes. Teachers appear from this study to use words such as indifferent, frightened, withdrawn, aggressive, disobedient, hyperactive, less ambitious, lacking concentration, and academically weak to describe pupils with emotional and behavioral difficulties (EBD). The implications of this study are envisaged as being extremely important to support teachers addressing children’s EBD and shed light on the contributing factors to EBD for a successful teaching-learning process in Libyan primary schools.

Keywords: children, emotional and behavior difficulties, learning, teachers'

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Authors: Radesh Palakurthi

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The purpose of this study was to determine the impact of experiential learning on learning outcomes in hospitality education. This paper presents the results of an online survey of students from the U.S. studying abroad and their self-reported change in learning outcomes as assessed using the Core Competencies Model for the Hospitality Industry developed by Employment and Training Development Office of the U.S. Department of Labor. The impact of student learning styles on learning outcomes is also evaluated in this study. Kolb’s Learning Styles Inventory Model was used to assess students’ learning style. The results show that students reported significant improvements in their learning outcomes because of engaging in study abroad experiential learning programs. The learning styles of the students had significant effect on one of core learning outcomes- personal effectiveness.

Keywords: hospitality competencies, hospitality education, Kolb’s learning style inventory, learning outcomes, study abroad

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Authors: Pieter van den Berg, Retief Broodryk, Bert Moolman

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Firstly, this study aimed to identify which performance indicators (PIs) discriminate between winning and losing university-level Rugby Union (RU) teams and, secondly, to compare the significant PIs in RU and Rugby Union Sevens (RS) at university level. Understanding the importance of PIs and their effect on match outcomes could assist coaching staff to prioritise specific game aspects during training to increase performance. Twenty randomly selected round-robin matches of the 2018 Varsity Cup (n=20), and Varsity Sports sevens (n=20) tournaments were analysed. A linear mixed model was used to determine statistical significant differences set at p≤0.05 while effect size was reported according to Cohen's d value. Results revealed that various PIs discriminated between winning and losing RU teams and that specific PIs could be observed as significant in both RU and RS. Therefore, specific identified tactical aspects of RU and RS should be prioritised to optimise performance

Keywords: match success, notational analysis, performance analysis, rugby, video analysis

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Authors: Suman Som, Abhijit Maity, Sunil B. Daschakraborty, Sujit Chaudhuri, Manik Pradhan

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Background: Helicobacter pylori is a common and important human pathogen and the primary cause of peptic ulcer disease and gastric cancer. Currently H. pylori infection is detected by both invasive and non-invasive way but the diagnostic accuracy is not up to the mark. Aim: To set up an optimal diagnostic cut-off value of 13C-Urea Breath Test to detect H. pylori infection and evaluate a novel c-PDR methodology to overcome of inconclusive grey zone. Materials and Methods: All 83 subjects first underwent upper-gastrointestinal endoscopy followed by rapid urease test and histopathology and depending on these results; we classified 49 subjects as H. pylori positive and 34 negative. After an overnight, fast patients are taken 4 gm of citric acid in 200 ml water solution and 10 minute after ingestion of the test meal, a baseline exhaled breath sample was collected. Thereafter an oral dose of 75 mg 13C-Urea dissolved in 50 ml water was given and breath samples were collected upto 90 minute for 15 minute intervals and analysed by laser based high precisional cavity enhanced spectroscopy. Results: We studied the excretion kinetics of 13C isotope enrichment (expressed as δDOB13C ‰) of exhaled breath samples and found maximum enrichment around 30 minute of H. pylori positive patients, it is due to the acid mediated stimulated urease enzyme activity and maximum acidification happened within 30 minute but no such significant isotopic enrichment observed for H. pylori negative individuals. Using Receiver Operating Characteristic (ROC) curve an optimal diagnostic cut-off value, δDOB13C ‰ = 3.14 was determined at 30 minute exhibiting 89.16% accuracy. Now to overcome grey zone problem we explore percentage dose of 13C recovered per hour, i.e. 13C-PDR (%/hr) and cumulative percentage dose of 13C recovered, i.e. c-PDR (%) in exhaled breath samples for the present 13C-UBT. We further explored the diagnostic accuracy of 13C-UBT by constructing ROC curve using c-PDR (%) values and an optimal cut-off value was estimated to be c-PDR = 1.47 (%) at 60 minute, exhibiting 100 % diagnostic sensitivity , 100 % specificity and 100 % accuracy of 13C-UBT for detection of H. pylori infection. We also elucidate the gastric emptying process of present 13C-UBT for H. pylori positive patients. The maximal emptying rate found at 36 minute and half empting time of present 13C-UBT was found at 45 minute. Conclusions: The present study exhibiting the importance of c-PDR methodology to overcome of grey zone problem in 13C-UBT for accurate determination of infection without any risk of diagnostic errors and making it sufficiently robust and novel method for an accurate and fast non-invasive diagnosis of H. pylori infection for large scale screening purposes.

Keywords: 13C-Urea breath test, c-PDR methodology, grey zone, Helicobacter pylori

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Authors: Yijie Wang, Tianyue Wang

Abstract:

In the past two decades, there has been a great ‘piano lesson frenzy’ among Chinese middle-class families, with a large number of parents adding piano training to children’s extra-curriculum lists. Superficially, the frenzy reflects a rather ‘leisurely’ attitude: parents typically claim that pianos lessons are ‘just for fun’ and will hopefully render children’s life more exciting. However, a closer scrutiny reveals that there is great social-status anxiety hidden beneath this ‘leisurely’ surface. Based on pre-interviews of six Chinese middle-class parents who have enthusiastically signed their children up for piano lessons, several tentative analysis are made: 1. Owing to a series of historical and social factors, the Chinese middle-class have yet to establish their cultural norms in the past few decades, resulting in great confusion concerning how to cultivate cultural tastes in their offspring. And partly due to the fact that the middle-class status of the past Chinese generation is mostly self-acquired rather than inherited, parents are much less confident about their cultural resources—which require long-time accumulation—than material ones. Both factors combine to lead to a sort of blind, overcompensating enthusiasm in culture-related education, and the piano frenzy is but a demonstration. 2. The piano has been chosen to be the object of the frenzy partly because of its inherent characteristics as well as socially-constructed ones. Costly, large in size, imported from another culture and so forth, the piano has acquired the meaning of being exclusive, high-end and exotic, which renders it a token of top-tier status among Chinese people, and piano lessons for offspring have therefore become parents’ paths towards a kind of ‘symbolic elevation’. A child playing piano is an exhibition as well as psychological assurance of the families’ middle-class status. 3. A closer look at children’s piano training process reveals that there is much more anxiety than leisurely elements involved. Despite parents’ claim that ‘piano is mainly for kids to have fun,’ the whole process is evidently of a rather ‘ascetic’ nature, with the demands of diligence and senses of time urgency throughout, and techniques rather than flair or styles are emphasized. This either means that the apparent ‘piano-for-fun’ stance is unauthentic and is only other motives in disguise, or that the Chinese middle-class parents are not yet capable of shaking off the sense of anxiety even if they sincerely intend to. 4. When viewed in relation to Chinese formal school system as well as the job market at large, it can be said that by signing children up for piano lessons, parents are consciously or unconsciously seeking to prepare for, or reduce the risks of, their children’s future social mobility. In face of possible failures in the highly-crucial, highly-competitive formal school system, piano-playing as an extra-curriculum activity may be conveniently transferred into an alternative career path. Besides, in contemporary China, as the occupational structure goes through change, and the school-related certificates decline in value, aspects such as a person’s overall deportment, which can be gained or proved by piano-learning, have been gaining in significance.

Keywords: extra-curriculum activities, middle class, piano lesson frenzy, status anxiety

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