Search results for: multi variable decision making

Authors: Sima Radmanesh, Nahid Radmanesh, Mohsen Yaghmoor

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The presence of large number of active rival gas companies on Persian Gulf border necessitates the adaptation and implementation of effective employee retention strategies as well as implementation of promoting loyalty and belonging strategies of specialized staffs in the South Pars gas company. Hence, this study aims at assessing the amount of organizational loyalty and explaining the effect of institutional justice on organizational justice with regard to the role of mediator variables of spirituality in the work place and organizational trust. Therefore, through reviewing the related literature, the researchers achieve a conceptual model for the effect of these factors on organizational loyalty. To this end, this model was assessed and tested through questionnaires in South Pars gas company. The research method was descriptive and correlation-structural equation modeling. The findings of the study indicated a significant relationship between the concepts addressed in the research and conceptual models were confirmed. Finally, according to the results to improve effectiveness factors affecting organizational loyalty, recommendations are provided.

Keywords: organizational loyalty, organizational trust, organizational justice, organizational spirit, oil and gas company

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Authors: Kamaludeen Samaila, Khashyaullah Abdulfattah, Fahimi Ahmad Bin Amir

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The study was conducted to examine the relationship between selected factors (performance expectancy, effort expectancy, social influence and facilitating condition) and students’ intention to use the learning management system (LMS), as well as investigating the factors predicting students’ intention to use the LMS. The study was specifically conducted at the Faculty of Educational Study of University Putra Malaysia. Questionnaires were distributed to 277 respondents using a random sampling technique. SPSS Version 22 was employed in analyzing the data; the findings of this study indicated that performance expectancy (r = .69, p < .01), effort expectancy (r=.60, p < .01), social influence (r = .61, p < .01), and facilitating condition (r=.42, p < .01), were significantly related to students’ intention to use the LMS. In addition, the result also revealed that performance expectancy (β = .436, p < .05), social influence (β=.232, p < .05), and effort expectancy (β = .193, p < .05) were strong predictors of students’ intention to use the LMS. The analysis further indicated that (R2) is 0.054 which means that 54% of variation in the dependent variable is explained by the entire predictor variables entered into the regression model. Understanding the factors that affect students’ intention to use the LMS could help the lecturers, LMS managers and university management to develop the policies that may attract students to use the LMS.

Keywords: LMS, postgraduate students, PutraBlas, students’ intention, UPM, UTAUT model

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Authors: N. A. Badrul

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People are concerned that they are vulnerable as a result of what is exposed about them on the internet. Users are increasingly aware of their privacy and are making various efforts to protect their personal information. However, besides individuals themselves, organisations are also exposing personal information of their staff to the general public by publishing it on their official website. This practice may put individuals at risk and particularly vulnerable to threats. This preliminary study explores explicitly the amount and types of personal information disclosure from organisational websites. Threats and risks related to the disclosures are discussed. In general, all the examined organisational websites discloses personal information with varies identifiable degree of data.

Keywords: personal information, privacy, e-government, information disclosure

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Authors: Nayera E. Hassan, Sahar A. El-Masry, Rokia El-Banna, Mohamed S. El Hussieny

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There are several different modalities for treatment of obesity. Common intervention methods for obesity include low-calorie diet, exercise. Also acupuncture has shown good therapeutic results in the treatment of obesity. A recent clinical observation showed that laser acupuncture could reduce body weight and body mass index in obese persons. So, the aim of this research is focused on body composition changes as related to type of intervention, before and after intentional weight loss in overweight and obesity. 76 subjects were included in the study analysis. The present study recommended that every obese female must do lipid profile and fasting blood sugar analysis before weight-loss intervention to take the decision of which method should be used.

Keywords: obesity, weight-loss, body composition, modalities

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Authors: Alexander Vandesompele, Joni Dambre

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The diversity in dendritic arborization, as first illustrated by Santiago Ramon y Cajal, has always suggested a role for dendrites in the functionality of neurons. In the past decades, thanks to new recording techniques and optical stimulation methods, it has become clear that dendrites are not merely passive electrical components. They are observed to integrate inputs in a non-linear fashion and actively participate in computations. Regardless, in simulations of neural networks dendritic structure and functionality are often overlooked. Especially in a machine learning context, when designing artificial neural networks, point neuron models such as the leaky-integrate-and-fire (LIF) model are dominant. These models mimic the integration of inputs at the neuron soma, and ignore the existence of dendrites. In this work, the LIF point neuron model is extended with a simple form of dendritic computation. This gives the LIF neuron increased capacity to discriminate spatiotemporal input sequences, a dendritic functionality as observed in another study. Simulations of the spiking neurons are performed using the Bindsnet framework. In the common LIF model, incoming synapses are independent. Here, we introduce a dependency between incoming synapses such that the post-synaptic impact of a spike is not only determined by the weight of the synapse, but also by the activity of other synapses. This is a form of short term plasticity where synapses are potentiated or depressed by the preceding activity of neighbouring synapses. This is a straightforward way to prevent inputs from simply summing linearly at the soma. To implement this, each pair of synapses on a neuron is assigned a variable,representing the synaptic relation. This variable determines the magnitude ofthe short term plasticity. These variables can be chosen randomly or, more interestingly, can be learned using a form of Hebbian learning. We use Spike-Time-Dependent-Plasticity (STDP), commonly used to learn synaptic strength magnitudes. If all neurons in a layer receive the same input, they tend to learn the same through STDP. Adding inhibitory connections between the neurons creates a winner-take-all (WTA) network. This causes the different neurons to learn different input sequences. To illustrate the impact of the proposed dendritic mechanism, even without learning, we attach five input neurons to two output neurons. One output neuron isa regular LIF neuron, the other output neuron is a LIF neuron with dendritic relationships. Then, the five input neurons are allowed to fire in a particular order. The membrane potentials are reset and subsequently the five input neurons are fired in the reversed order. As the regular LIF neuron linearly integrates its inputs at the soma, the membrane potential response to both sequences is similar in magnitude. In the other output neuron, due to the dendritic mechanism, the membrane potential response is different for both sequences. Hence, the dendritic mechanism improves the neuron’s capacity for discriminating spa-tiotemporal sequences. Dendritic computations improve LIF neurons even if the relationships between synapses are established randomly. Ideally however, a learning rule is used to improve the dendritic relationships based on input data. It is possible to learn synaptic strength with STDP, to make a neuron more sensitive to its input. Similarly, it is possible to learn dendritic relationships with STDP, to make the neuron more sensitive to spatiotemporal input sequences. Feeding structured data to a WTA network with dendritic computation leads to a significantly higher number of discriminated input patterns. Without the dendritic computation, output neurons are less specific and may, for instance, be activated by a sequence in reverse order.

Keywords: dendritic computation, spiking neural networks, point neuron model

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Authors: Ali Ashraf Hamedi Oghul Beyk

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This research is aimed in order to demonstrate the factors affecting on effectiveness of animal artificial insemination training courses in Zanjan province. The research method is descriptive and correlation. Research tools a questionnaire and research sample are 104 persons who participated in animal artificial insemination training courses. The data resulted from this procedure was analysed by using SPSS software under windows system.independent variables include :individual, sociological, technical, and organizational, dependent variable is: affecting factors on effectiveness of animal artificial insemination training courses the finding of this study indicates that there is a significant correlation(99/0) between individual variables such as motivation and interest and experiment and effectiveness of animal artificial insemination training courses. There is significant correlation (95/0) between sociological variables such as job and education and effectiveness of animal artificial insemination training course. There is significant correlation (99/0) between techn ical variables such as training quality media and instructional materials. Moreover, effectiveness of animal artificial insemination training course there is significant correlation(0/95) between organizational variables such as trainers combination,place conditions.

Keywords: animal artificial insemination, effect, effectiveness, training courses, Zanjan

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Authors: Zine Souhila Rached, Mazari Benyounes Bouzid, Mohamed Amine, Allaoui Tayeb

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Wind energy has many advantages, it does not pollute and it is an inexhaustible source. However, its high cost is a major constraint, especially on the less windy sites. The purpose of wind energy systems is to maximize energy efficiency, and extract maximum power from the wind speed. In other words, having a power coefficient is maximum and therefore the maximum power point tracking. In this case, the MPPT control becomes important.To realize this control, strategy conventional proportional and integral (PI) controller is usually used. However, this strategy cannot achieve better performance. This paper proposes a robust control of a turbine which optimizes its production, that is improve the quality and energy efficiency, namely, a strategy of sliding mode control. The proposed sliding mode control strategy presents attractive features such as robustness to parametric uncertainties of the turbine; the proposed sliding mode control approach has been simulated on three-blade wind turbine. The simulation result under Matlab\Simulink has validated the performance of the proposed MPPT strategy.

Keywords: wind turbine, maximum power point tracking, sliding mode, energy conversion systems

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Authors: Patricia Sanz-Cordoba, Bernd Theilen

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This article analyzes the conditions where decentralization and partial tax harmonization in a coalition of asymmetric jurisdictions plays a role in the fight of fiscal competition (i.e. the race to bottom). Starting from a centralized economies, we use the ZM-W model to analyze the fiscal competition and coordination among three countries. We find that the asymmetry of jurisdictions facilitates partial tax harmonization between jurisdictions when these asymmetries are not too large. Furthermore, when the asymmetries are large enough, the level of labor tax plays an important role in the decision of decentralize capital tax. Accordingly, decentralization is achievable when labor tax is low. This result indicates that decentralization and partial tax harmonization between jurisdictions can be possible results in order to fight the negative externalities from fiscal competition, and more in the European Union countries where the asymmetries are substantial.

Keywords: centralization, decentralization, fiscal competition, partial tax harmonization

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Authors: Punnoose A. K.

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This paper presents an approach for identifying noisy speech recording using a multi-layer perception (MLP) trained to predict phonemes from acoustic features. Characteristics of the MLP posteriors are explored for clean speech and noisy speech at the frame level. Appropriate density functions are used to fit the softmax probability of the clean and noisy speech. A function that takes into account the ratio of the softmax probability density of noisy speech to clean speech is formulated. These phoneme independent scoring is weighted using a phoneme-specific weightage to make the scoring more robust. Simple thresholding is used to identify the noisy speech recording from the clean speech recordings. The approach is benchmarked on standard databases, with a focus on precision.

Keywords: noisy speech identification, speech pre-processing, noise robustness, feature engineering

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Authors: Bryan Crompton, Daniel Giger, Tanay Mehta, Apurva Mody

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The task of classifying radio frequency (RF) signals has seen recent success in employing deep neural network models. In this work, we present a combined signal processing and machine learning approach to signal classification for cochannel anomalous signals. The power spectral density and cyclostationary signal processing features of a captured signal are computed and fed into a neural net to produce a classification decision. Our combined signal preprocessing and machine learning approach allows for simpler neural networks with fast training times and small computational resource requirements for inference with longer preprocessing time.

Keywords: signal processing, machine learning, cyclostationary signal processing, signal classification

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Authors: S. Ping Ho, R. Dahal

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The global economy has drastically changed how firms operate and compete. Although the construction industry is ‘local’ by its nature, the internationalization of the construction industry has become an inevitable reality. As a result of global competition, staying domestic is no longer safe from competition and, on the contrary, to grow and become an MNE (multi-national enterprise) becomes one of the important strategies for a firm to survive in the global competition. For the successful entrance into competing markets, the firms need to re-define their competitive advantages and re-identify the sources of the competitive advantages. A firm’s initiation of internationalization is not necessarily a result of strategic planning but also involves certain idiosyncratic events that pave the path leading to a firm’s internationalization. For example, a local firm’s incidental or unintentional collaboration with an MNE can become the initiating point of its internationalization process. However, because of the intensive competition in today’s global movement, many firms were compelled to initiate their internationalization as a strategic response to the competition. Understandingly stepping in in the process of internationalization and appropriately implementing the strategies (in the process) at different stages lead the construction firms to a successful internationalization journey. This study is carried out to develop a model of the internationalization process, which derives appropriate strategies that the construction firms can implement at each stage. The proposed model integrates two major and complementary views of internationalization and expresses the dynamic process of internationalization in three stages, which are the pre-international (PRE) stage, the foreign direct investment (FDI) stage, and the multi-national enterprise (MNE) stage. The strategies implied in the proposed model are derived, focusing on capability building, market locations, and entry modes based on the resource-based views: value, rareness, imitability, and substitutability (VRIN). With the proposed dynamic process model the potential construction firms which are willing to expand their business market area can be benefitted. Strategies for internationalization, such as core competence strategy, market selection, partner selection, and entry mode strategy, can be derived from the proposed model. The internationalization process is expressed in two different forms. First, we discuss the construction internationalization process, identify the driving factor/s of the process, and explain the strategy formation in the process. Second, we define the stages of internationalization along the process and the corresponding strategies in each stage. The strategies may include how to exploit existing advantages for the competition at the current stage and develop or explore additional advantages appropriate for the next stage. Particularly, the additionally developed advantages will then be accumulated and drive forward the firm’s stage of internationalization, which will further determine the subsequent strategies, and so on and so forth, spiraling up the stages of a higher degree of internationalization. However, the formation of additional strategies for the next stage does not happen automatically, and the strategy evolution is based on the firm’s dynamic capabilities.

Keywords: construction industry, dynamic capabilities, internationalization process, internationalization strategies, strategic management

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Authors: Miriam Sebastian

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This research focused on the effects of bilingual education as medium of instruction to the academic performance of selected intermediate students of Miriam’s Academy of Valenzuela Inc. . An experimental design was used, with language of instruction as the independent variable and the different literacy skills as dependent variables. The sample consisted of experimental students comprises of 30 students were exposed to bilingual education (Filipino and English) . They were given pretests and were divided into three groups: Monolingual Filipino, Monolingual English, and Bilingual. They were taught different literacy skills for eight weeks and were then administered the posttests. Data was analyzed and evaluated in the light of the central processing and script-dependent hypotheses. Based on the data, it can be inferred that monolingual instruction in either Filipino or English had a stronger effect on the students’ literacy skills compared to bilingual instruction. Moreover, mother tongue-based instruction, as compared to second-language instruction, had stronger effect on the preschoolers’ literacy skills. Such results have implications not only for mother tongue-based (MTB) but also for English as a second language (ESL) instruction in the country

Keywords: bilingualism, effects, monolingual, function, multilingual, mother tongue

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Authors: Ainura Kairanbayeva

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Currently, the issue of maintaining the operational condition of highways at the required level is acute in Kazakhstan. The impact of landslides on the state of the road industry in Kazakhstan has been poorly studied. This article presents the classification of natural hazards and examines the influence of atmospheric natural processes on the operational condition of the sections of the highway "Ayusai–Kosmostantsia" passing along the mountain slopes of the Trans-Ili Alatau. According to the results of field studies, multi-turn reflected cracks have been identified, this is also due to the fact that the base of the road is made of a sand-gravel mixture and is not treated with reinforcing additives and the actual density of the asphalt concrete pavement is below regulatory requirements.

Keywords: building materials and products, construction of highways and engineering structures, construction processes, displacements of the earth's surface, geodynamic processes

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Authors: Sakapas Saengchai

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Study on the development of people's participation in environmental development was a qualitative research method. Data were collected by participant observation, in-depth interview and discussion group in Pathumthani province. The study indicated that 1) People should be aware of environmental information from government agencies. 2) People in the community should be able to brainstorm information, exchange information about community environment development. 3) People should have a role with community leaders. 4) People in the community should have a role to play in the implementation of projects and activities in the development of the environment and 5) citizens, community leaders, village committee have directed the development of the area. Maintaining a community environment with a shared decision. By emphasizing the process of participation, self-reliance, mutual help, and responsibility for one's own community. Community empowerment strengthens the sustainable spatial development of the environment.

Keywords: people, participation, community, environment

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Authors: Margarida Porfírio Tomás, Paula Pereira, José Manuel Palma Oliveira

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The decline in employment rates across sectors like industry and construction is exacerbated by an aging workforce. This has far-reaching implications for the economy, including skills gaps, labour shortages, productivity challenges due to physical limitations, and workplace safety concerns. To sustain the workforce and pension systems, technology plays a pivotal role. Robots provide valuable support to human workers, and effective human-robot interaction is essential. FORTIS, a Horizon project, aims to address these challenges by creating a comprehensive Human-Robot Interaction (HRI) solution. This solution focuses on multi-modal communication and multi-aspect interaction, with a primary goal of maintaining a human-centric approach. By meeting the needs of both human workers and robots, FORTIS aims to facilitate efficient and safe collaboration. The project encompasses three key activities: 1) A Human-Centric Approach involving data collection, annotation, understanding human behavioural cognition, and contextual human-robot information exchange. 2) A Robotic-Centric Focus addressing the unique requirements of robots during the perception and evaluation of human behaviour. 3) Ensuring Human-Robot Trustworthiness through measures such as human-robot digital twins, safety protocols, and resource allocation. Factor Social, a project partner, will analyse psycho-physiological signals that influence human factors, particularly in hazardous working conditions. The analysis will be conducted using a combination of case studies, structured interviews, questionnaires, and a comprehensive literature review. However, the adoption of novel technologies, particularly those involving human-robot interaction, often faces hurdles related to acceptance. To address this challenge, FORTIS will draw upon insights from Social Sciences and Humanities (SSH), including risk perception and technology acceptance models. Throughout its lifecycle, FORTIS will uphold a human-centric approach, leveraging SSH methodologies to inform the design and development of solutions. This project received funding from European Union’s Horizon 2020/Horizon Europe research and innovation program under grant agreement No 101135707 (FORTIS).

Keywords: skills gaps, productivity challenges, workplace safety, human-robot interaction, human-centric approach, social sciences and humanities, risk perception

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Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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Authors: Chang Li-Yu

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Aims: This study investigates the impact of psychological capital on the mental health of economically disadvantaged youth and examines whether family cohesion acts as a mediating variable between psychological capital and mental health. Methods: The sample for the study was drawn from the "Taiwan Poverty Children's Database: Survey on the Living Trends of Disadvantaged Children and Youth." The data analysis methods included descriptive statistics, confirmatory factor analysis, and structural equation modeling. Results: The results indicated that both psychological capital and family cohesion can significantly negatively predict mental health, with psychological capital significantly positively predicting family cohesion. The mediation effect analysis revealed that family cohesion fully mediates the relationship between psychological capital and mental health, meaning that psychological capital influences mental health through family cohesion. Recommendations: Based on these findings, the study concretely discusses the significance of psychological capital and family cohesion for the mental health of economically disadvantaged youth and offers suggestions for psychological counseling, therapy, and future research.

Keywords: psychological capital, mental health, economically disadvantaged youth, family cohesion

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Authors: Sara Saboonian, Pierre Filion

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There are two distinct planning approaches attempting to transform the North American suburb so as to reduce its adverse environmental impacts. The first one, the recentralization approach, proposes intensification, multi-functionality and more reliance on public transit and walking. It thus offers an alternative to the prevailing low-density, spatial specialization and automobile dependence of the North American suburb. The second approach concentrates instead on the provision of green infrastructure, which rely on natural systems rather than on highly engineered solutions to deal with the infrastructure needs of suburban areas. There are tensions between these two approaches as recentralization generally overlooks green infrastructure, which can be space consuming (as in the case of water retention systems), and thus conflicts with the intensification goals of recentralization. The research investigates three Canadian planned suburban centres in the Greater Toronto Area, where recentralization is the current planning practice, despite rising awareness of the benefits of green infrastructure. Methods include reviewing the literature on green infrastructure planning, a critical analysis of the Ontario provincial plans for recentralization, surveying residents’ preferences regarding alternative suburban development models, and interviewing officials who deal with the local planning of the three centres. The case studies expose the difficulties in creating planned suburban centres that accommodate green infrastructure while adhering to recentralization principles. Until now, planners have been mostly focussed on recentralization at the expense of green infrastructure. In this context, the frequent lack of compatibility between recentralization and the space requirements of green infrastructure explains the limited presence of such infrastructures in planned suburban centres. Finally, while much attention has been given in the planning discourse to the economic and lifestyle benefits of recentralization, much less has been made of the wide range of advantages of green infrastructure, which explains limited public mobilization over the development of green infrastructure networks. The paper will concentrate on ways of combining recentralization with green infrastructure strategies and identify the aspects of the two approaches that are most compatible with each other. The outcome of such blending will marry high density, public-transit oriented developments, which generate walkability and street-level animation, with the presence of green space, naturalized settings and reliance on renewable energy. The paper will advance a planning framework that will fuse green infrastructure with recentralization, thus ensuring the achievement of higher density and reduced reliance on the car along with the provision of critical ecosystem services throughout cities. This will support and enhance the objectives of both green infrastructure and recentralization.

Keywords: environmental-based planning, green infrastructure, multi-functionality, recentralization

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Authors: Ahmad FAROOQ, Xinfeng Zhang, Fahad Sabah, Raheem Sarwar

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In Traditional Chinese Medicine, tongue diagnosis is a vital inspection tool (TCM). In this study, we explore the potential of machine learning in tongue diagnosis. It begins with the cataloguing of the various classifications and characteristics of the human tongue. We infer 24 kinds of tongues from the material and coating of the tongue, and we identify 21 attributes of the tongue. The next step is to apply machine learning methods to the tongue dataset. We use the Weka machine learning platform to conduct the experiment for performance analysis. The 457 instances of the tongue dataset are used to test the performance of five different machine learning methods, including SVM, Random Forests, Decision Trees, and Naive Bayes. Based on accuracy and Area under the ROC Curve, the Support Vector Machine algorithm was shown to be the most effective for tongue diagnosis (AUC).

Keywords: medical imaging, image retrieval, machine learning, tongue

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Authors: Runglaksamee Rodkam

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The purpose of this research was to study the influence of accountants’ potential performance on their working process, a case study of Government Savings Banks in the northeast of Thailand. The independent variables included accounting knowledge, accounting skill, accounting value, accounting ethics, and accounting attitude, while the dependent variable included the success of the working process. A total of 155 accountants working for Government Savings Banks were selected by random sampling. A questionnaire was used as a tool for collecting data. Descriptive statistics in this research included percentage, mean, and multiple regression analyses. The findings revealed that the majority of accountants were female with an age between 35-40 years old. Most of the respondents had an undergraduate degree with ten years of experience. Moreover, the factors of accounting knowledge, accounting skill, accounting a value and accounting ethics and accounting attitude were rated at a high level. The findings from regression analysis of observation data revealed a causal relationship in that the observation data could explain at least 51 percent of the success in the accountants’ working process.

Keywords: influence, potential performance, success, working process

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Authors: Abouzar Kaboudian, Boo Cheong Khoo

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The Ghost Solid Method (GSM) based algorithms have been extensively used for numerical calculation of wave propagation in the limit of abrupt changes in materials. In this work, we present a unified version of the GSMs that can be successfully applied to both abrupt as well as smooth changes of the material properties in a medium. The application of this method enables us to use the previously-matured numerical algorithms which were developed to be applied to homogeneous mediums, with only minor modifications. This method is developed for one-dimensional settings and its extension to multi-dimensions is briefly discussed. Various numerical experiments are presented to show the applicability of this unified GSM to wave propagation problems in sharply as well as smoothly varying mediums.

Keywords: elastic solid, functionally graded material, ghost solid method, solid-solid interaction

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Authors: Mohammad Alshawaf, Rahmat Poudineh, Nawaf Alhajeri

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The power generated from photovoltaic (PV) modules is non-dispatchable on demand due to the stochastic nature of solar radiation. The random variations in the measured intensity of solar irradiance are due to clouds and, in the case of arid regions, dust storms which decrease the intensity of intensity of solar irradiance. Therefore, modeling PV power output using average, maximum, or minimum solar irradiance values is inefficient to predict power generation reliably. The overall objective of this paper is to predict the power output of PV modules using Monte Carlo approach based the weather and solar conditions measured in Kuwait. Given the 250 Wp PV module used in study, the average daily power output is 1021 Wh/day. The maximum power was generated in April and the minimum power was generated in January 1187 Wh/day and 823 Wh/day respectively. The certainty of the daily predictions varies seasonally and according to the weather conditions. The output predictions were far more certain in the summer months, for example, the 80% certainty range for August is 89 Wh/day, whereas the 80% certainty range for April is 250 Wh/day.

Keywords: Monte Carlo, solar energy, variable renewable energy, Kuwait

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Authors: A. Bhatt, C. Bassi, H. Farragher, J. Musk

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Background: All medicines placed on the EU market are legally required to be accompanied by labeling and package leaflet, which provide comprehensive information, enabling its safe and appropriate use. Mock-ups with results of assessments using a target patient group must be submitted for a marketing authorisation application. Consumers need confidence in non-prescription, OTC medicines in order to manage their minor ailments and umbrella brands assist purchasing decisions by assisting easy identification within a particular therapeutic area. A number of regulatory agencies have risk management tools and guidelines to assist in developing umbrella brands for OTC medicines, however assessment and decision making is subjective and inconsistent. This study presents an evaluation in the UK following the US FDA warning concerning methaemoglobinaemia following 21 reported cases (11 children under 2 years) caused by OTC oral analgesics containing benzocaine. METHODS: A standard face to face, 25 structured task based user interview testing methodology using a standard questionnaire and rating scale in consumers aged 15-91 years, was conducted independently between June and October 2015 in their homes. Whether individuals could discriminate between the labelling, safety information and warnings on cartons and PILs between 3 different OTC medicines packs with the same umbrella name was evaluated. Each pack was presented with differing information hierarchy using, different coloured cartons, containing the 3 different active ingredients, benzocaine (oromucosal spray) and two lozenges containing 2, 4, dichlorobenzyl alcohol, amylmetacresol and hexylresorcinol respectively (for the symptomatic relief of sore throat pain). The test was designed to determine whether warnings on the carton and leaflet were prominent, accessible to alert users that one product contained benzocaine, risk of methaemoglobinaemia, and refer to the leaflet for the signs of the condition and what to do should this occur. Results: Two consumers did not locate the warnings on the side of the pack, eventually found them on the back and two suggestions to further improve accessibility of the methaemoglobinaemia warning. Using a gold pack design for the oromucosal spray, all consumers could differentiate between the 3 drugs, minimum age particulars, pharmaceutical form and the risk factor methaemoglobinaemia. The warnings for benzocaine were deemed to be clear or very clear; appearance of the 3 packs were either very well differentiated or quite well differentiated. The PIL test passed on all criteria. All consumers could use the product correctly, identify risk factors ensuring the critical information necessary for the safe use was legible and easily accessible so that confusion and errors were minimised. Conclusion: Patients with known methaemoglobinaemia are likely to be vigilant in checking for benzocaine containing products, despite similar umbrella brand names across a range of active ingredients. Despite these findings, the package design and spray format were not deemed to be sufficient to mitigate potential safety risks associated with differences in target populations and contraindications when submitted to the Regulatory Agency. Although risk management tools are increasingly being used by agencies to assist in providing objective assurance of package safety, further transparency, reduction in subjectivity and proportionate risk should be demonstrated.

Keywords: labelling, OTC, risk, user testing

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Authors: Valencia P. L. Rodrigo, Morita A. Adelina, Vargas V. Martin

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This proposal consists of an analysis of macro concepts involved within an organization growth using educational technologies, which will relate each concept, in a mathematical way with a vision of harmonic work. Working collaboratively, competitively and cooperatively so that this growth is harmonious and homogenous, coining a new term, Harmonic Work. The Harmonic Work ensures that the organization grows in all business directions, allowing managers to project a much more accurate growth, making clear the contribution of each department, resulting in an algorithm that analyzes each of the variables both endogenous and exogenous, establishing different performance indicators in its process of growth.

Keywords: business projection, collaboration, competitiveness, educational technology, harmonious growth

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Authors: Vladislav Grigorovitch, Marina Grigorovitch, David Pearlmutter, Erez Gal

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The concept of “electric island” is involved with achieving the balance between the self-power generation ability of each educational institution and energy consumption demand. Photo-Voltaic (PV) solar system installed on the roofs of educational buildings is a common way to absorb the available solar energy and generate electricity for self-consumption and even for returning to the grid. The main objective of this research is to develop and implement an “electric island” monitoring infrastructure for promoting energy efficiency in educational buildings. A microscale monitoring methodology will be developed to provide a platform to estimate energy consumption performance classified by rooms and subspaces rather than the more common macroscale monitoring of the whole building. The monitoring platform will be established on the experimental sites, enabling an estimation and further analysis of the variety of environmental and physical conditions. For each building, separate measurement configurations will be applied taking into account the specific requirements, restrictions, location and infrastructure issues. The direct results of the measurements will be analyzed to provide deeper understanding of the impact of environmental conditions and sustainability construction standards, not only on the energy demand of public building, but also on the energy consumption habits of the children that study in those schools and the educational and administrative staff that is responsible for providing the thermal comfort conditions and healthy studying atmosphere for the children. A monitoring methodology being developed in this research is providing online access to real-time data of Interferential Therapy (IFTs) from any mobile phone or computer by simply browsing the dedicated website, providing powerful tools for policy makers for better decision making while developing PV production infrastructure to achieve “electric islands” in educational buildings. A detailed measurement configuration was technically designed based on the specific conditions and restriction of each of the pilot buildings. A monitoring and analysis methodology includes a large variety of environmental parameters inside and outside the schools to investigate the impact of environmental conditions both on the energy performance of the school and educational abilities of the children. Indoor measurements are mandatory to acquire the energy consumption data, temperature, humidity, carbon dioxide and other air quality conditions in different parts of the building. In addition to that, we aim to study the awareness of the users to the energy consideration and thus the impact on their energy consumption habits. The monitoring of outdoor conditions is vital for proper design of the off-grid energy supply system and validation of its sufficient capacity. The suggested outcomes of this research include: 1. both experimental sites are designed to have PV production and storage capabilities; 2. Developing an online information feedback platform. The platform will provide consumer dedicated information to academic researchers, municipality officials and educational staff and students; 3. Designing an environmental work path for educational staff regarding optimal conditions and efficient hours for operating air conditioning, natural ventilation, closing of blinds, etc.

Keywords: sustainability, electric island, IOT, smart building

Procedia PDF Downloads 167

Authors: Le Chen

Abstract:

This paper presents an efficient tool platform scheme to ensure quality protection throughout the software development process. The main principle is to manage the information of requirements, design, development, testing, operation and maintenance process with proper tools, and to set up the quality standards of each process. Through the tools’ display and summary of quality standards, the quality standards can be visualizad and ready for policy decision, which is called Quality Gate in this paper. In addition, the tools are also integrated to achieve the exchange and relation of information which highly improving operational efficiency. In this paper, the feasibility of the scheme is verified by practical application of development projects, and the overall information display and data mining are proposed to be further improved.

Keywords: efficiency, quality gate, software process, tools

Procedia PDF Downloads 349

Authors: Igor Pejic

Abstract:

The main focus of this research will be on analyzing correlative links between terrorism as an asymmetrical threat and the consequences it leaves on conventional security forces. The methodology behind the research will include qualitative research methods focusing on comparative analysis of books, scientific papers, documents and other sources, in order to deduce, explore and formulate the results of the research. With the coming of the 21^st century and the rising multi-polar, new world threats quickly emerged. The realistic approach in international relations deems that relations among nations are in a constant state of anarchy since there are no definitive rules and the distribution of power varies widely. International relations are further characterized by egoistic and self-orientated human nature, anarchy or absence of a higher government, security and lack of morality. The asymmetry of power is also reflected on countries' security capabilities and its abilities to project power. With the coming of the new millennia and the rising multi-polar world order, the asymmetry of power can be also added as an important trait of the global society which consequently brought new threats. Among various others, terrorism is probably the most well-known, well-based and well-spread asymmetric threat. In today's global political arena, terrorism is used by state and non-state actors to fulfill their political agendas. Terrorism is used as an all-inclusive tool for regime change, subversion or a revolution. Although the nature of terrorist groups is somewhat inconsistent, terrorism as a security and social phenomenon has a one constant which is reflected in its political dimension. The state's security apparatus, which was embodied in the form of conventional armed forces, is now becoming fragile, unable to tackle new threats and to a certain extent outdated. Conventional security forces were designed to defend or engage an exterior threat which is more or less symmetric and visible. On the other hand, terrorism as an asymmetrical threat is a part of hybrid, special or asymmetric warfare in which specialized units, institutions or facilities represent the primary pillars of security. In today's global society, terrorism is probably the most acute problem which can paralyze entire countries and their political systems. This problem, however, cannot be engaged on an open field of battle, but rather it requires a different approach in which conventional armed forces cannot be used traditionally and their role must be adjusted. The research will try to shed light on the phenomena of modern day terrorism and to prove its correlation with the state conventional armed forces. States are obliged to adjust their security apparatus to the new realism of global society and terrorism as an asymmetrical threat which is a side-product of the unbalanced world.

Keywords: asymmetrical warfare, conventional forces, security, terrorism

Procedia PDF Downloads 253

Authors: Si Mon Kueh, Tom J. Kazmierski

Abstract:

There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.

Keywords: Artificial Neural Networks (ANN), bit-serial neural processor, FPGA, Neural Processing Element (NPE)

Procedia PDF Downloads 307

Authors: Rizka Aisha Rahmi Hariadi, Chao Ou-Yang, Han-Cheng Wang, Rajesri Govindaraju

Abstract:

As the increasing of medical check-up popularity, there are a huge number of medical check-up data stored in database and have not been useful. These data actually can be very useful for future strategic planning if we mine it correctly. In other side, a lot of patients come with unpredictable coming and also limited available facilities make medical check-up service offered by hospital not maximal. To solve that problem, this study used those medical check-up data to predict patient re-coming. Sequential pattern mining (SPM) and association rules method were chosen because these methods are suitable for predicting patient re-coming using sequential data. First, based on patient personal information the data was grouped into … groups then discriminant analysis was done to check significant of the grouping. Second, for each group some frequent patterns were generated using SPM method. Third, based on frequent patterns of each group, pairs of variable can be extracted using association rules to get general pattern of re-coming patient. Last, discussion and conclusion was done to give some implications of the results.

Keywords: patient re-coming, medical check-up, health examination, data mining, sequential pattern mining, association rules, discriminant analysis

Procedia PDF Downloads 630

Authors: Jasmal A. Syamsu, Muhammad Yusuf, Hikmah M. Ali, Mawardi A. Asja, Zulkharnaim

Abstract:

This study was conducted and aimed in identifying and mapping the pasture as an ecological base of beef cattle. A survey was carried out during a period of April to June 2016, in Suppa, Mattirobulu, the district of Pinrang, South Sulawesi province. The mapping process of grazing area was conducted in several stages; inputting and tracking of data points into Google Earth Pro (version 7.1.4.1529), affirmation and confirmation of tracking line visualized by satellite with a variety of records at the point, a certain point and tracking input data into ArcMap Application (ArcGIS version 10.1), data processing DEM/SRTM (S04E119) with respect to the location of the grazing areas, creation of a contour map (a distance of 5 m) and mapping tilt (slope) of land and land cover map-making. Analysis of land cover, particularly the state of the vegetation was done through the identification procedure NDVI (Normalized Differences Vegetation Index). This procedure was performed by making use of the Landsat-8. The results showed that the topography of the grazing areas of hills and some sloping surfaces and flat with elevation vary from 74 to 145 above sea level (asl), while the requirements for growing superior grass and legume is an altitude of up to 143-159 asl. Slope varied between 0 - > 40% and was dominated by a slope of 0-15%, according to the slope/topography pasture maximum of 15%. The range of NDVI values for pasture image analysis results was between 0.1 and 0.27. Characteristics of vegetation cover of pasture land in the category of vegetation density were low, 70% of the land was the land for cattle grazing, while the remaining approximately 30% was a grove and forest included plant water where the place for shelter of the cattle during the heat and drinking water supply. There are seven types of graminae and 5 types of legume that was dominant in the region. Proportionally, graminae class dominated up 75.6% and legume crops up to 22.1% and the remaining 2.3% was another plant trees that grow in the region. The dominant weed species in the region were Cromolaenaodorata and Lantana camara, besides that there were 6 types of floor plant that did not include as forage fodder.

Keywords: pastoral, ecology, mapping, beef cattle

Procedia PDF Downloads 337