Search results for: Statistical Approach
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17293

Search results for: Statistical Approach

15823 Modelling Patient Condition-Based Demand for Managing Hospital Inventory

Authors: Esha Saha, Pradip Kumar Ray

Abstract:

A hospital inventory comprises of a large number and great variety of items for the proper treatment and care of patients, such as pharmaceuticals, medical equipment, surgical items, etc. Improper management of these items, i.e. stockouts, may lead to delay in treatment or other fatal consequences, even death of the patient. So, generally the hospitals tend to overstock items to avoid the risk of stockout which leads to unnecessary investment of money, difficulty in storing, more expiration and wastage, etc. Thus, in such challenging environment, it is necessary for hospitals to follow an inventory policy considering the stochasticity of demand in a hospital. Statistical analysis captures the correlation of patient condition based on bed occupancy with the patient demand which changes stochastically. Due to the dependency on bed occupancy, the markov model is developed that helps to map the changes in demand of hospital inventory based on the changes in the patient condition represented by the movements of bed occupancy states (acute care state, rehabilitative state and long-care state) during the length-of-stay of patient in a hospital. An inventory policy is developed for a hospital based on the fulfillment of patient demand with the objective of minimizing the frequency and quantity of placement of orders of inventoried items. The analytical structure of the model based on probability calculation is provided to show the optimal inventory-related decisions. A case-study is illustrated in this paper for the development of hospital inventory model based on patient demand for multiple inpatient pharmaceutical items. A sensitivity analysis is conducted to investigate the impact of inventory-related parameters on the developed optimal inventory policy. Therefore, the developed model and solution approach may help the hospital managers and pharmacists in managing the hospital inventory in case of stochastic demand of inpatient pharmaceutical items.

Keywords: bed occupancy, hospital inventory, markov model, patient condition, pharmaceutical items

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15822 An Automatic Large Classroom Attendance Conceptual Model Using Face Counting

Authors: Sirajdin Olagoke Adeshina, Haidi Ibrahim, Akeem Salawu

Abstract:

large lecture theatres cannot be covered by a single camera but rather by a multicamera setup because of their size, shape, and seating arrangements. Although, classroom capture is achievable through a single camera. Therefore, a design and implementation of a multicamera setup for a large lecture hall were considered. Researchers have shown emphasis on the impact of class attendance taken on the academic performance of students. However, the traditional method of carrying out this exercise is below standard, especially for large lecture theatres, because of the student population, the time required, sophistication, exhaustiveness, and manipulative influence. An automated large classroom attendance system is, therefore, imperative. The common approach in this system is face detection and recognition, where known student faces are captured and stored for recognition purposes. This approach will require constant face database updates due to constant changes in the facial features. Alternatively, face counting can be performed by cropping the localized faces on the video or image into a folder and then count them. This research aims to develop a face localization-based approach to detect student faces in classroom images captured using a multicamera setup. A selected Haar-like feature cascade face detector trained with an asymmetric goal to minimize the False Rejection Rate (FRR) relative to the False Acceptance Rate (FAR) was applied on Raspberry Pi 4B. A relationship between the two factors (FRR and FAR) was established using a constant (λ) as a trade-off between the two factors for automatic adjustment during training. An evaluation of the proposed approach and the conventional AdaBoost on classroom datasets shows an improvement of 8% TPR (output result of low FRR) and 7% minimization of the FRR. The average learning speed of the proposed approach was improved with 1.19s execution time per image compared to 2.38s of the improved AdaBoost. Consequently, the proposed approach achieved 97% TPR with an overhead constraint time of 22.9s compared to 46.7s of the improved Adaboost when evaluated on images obtained from a large lecture hall (DK5) USM.

Keywords: automatic attendance, face detection, haar-like cascade, manual attendance

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15821 Information Literacy Skills of Legal Practitioners in Khyber Pakhtunkhwa-Pakistan: An Empirical Study

Authors: Saeed Ullah Jan, Shaukat Ullah

Abstract:

Purpose of the study: The main theme of this study is to explore the information literacy skills of the law practitioners in Khyber Pakhtunkhwa-Pakistan under the heading "Information Literacy Skills of Legal Practitioners in Khyber Pakhtunkhwa-Pakistan: An Empirical Study." Research Method and Procedure: To conduct this quantitative study, the simple random sample approach is used. An adapted questionnaire is distributed among 254 lawyers of Dera Ismail Khan through personal visits and electronic means. The data collected is analyzed through SPSS (Statistical Package for Social Sciences) software. Delimitations of the study: The study is delimited to the southern district of Khyber Pakhtunkhwa: Dera Ismael Khan. Key Findings: Most of the lawyers of District Dera Ismail Khan of Khyber Pakhtunkhwa can recognize and understand the needed information. A large number of lawyers are capable of presenting information in both written and electronic forms. They are not comfortable with different legal databases and using various searching and keyword techniques. They have less knowledge of Boolean operators for locating online information. Conclusion and Recommendations: Efforts should be made to arrange refresher courses and training workshops on the utilization of different legal databases and different search techniques for retrieval of information sources. This practice will enhance the information literacy skills of lawyers, which will ultimately result in a better legal system in Pakistan. Practical implication(s): The findings of the study will motivate the policymakers and authorities of legal forums to restructure the information literacy programs to fulfill the lawyers' information needs. Contribution to the knowledge: No significant work has been done on the lawyers' information literacy skills in Khyber Pakhtunkhwa-Pakistan. It will bring a clear picture of the information literacy skills of law practitioners and address the problems faced by them during the seeking process.

Keywords: information literacy-Pakistan, infromation literacy-lawyers, information literacy-lawyers-KP, law practitioners-Pakistan

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15820 Quantifying Stakeholders’ Values of Technical and Vocational Education and Training Provision in Nigeria

Authors: Lidimma Benjamin, Nimmyel Gwakzing, Wuyep Nanyi

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Technical and Vocational Education and Training (TVET) has many stakeholders, each with their own values and interests. This study will focus on the diversity of the values and interests within and across groups of stakeholders by quantifying the value that stakeholders attached to several quality attributes of TVET, and also find out to what extent TVET stakeholders differ in their values. The quality of TVET therefore, depends on how well it aligns with the values and interests of these stakeholders. The five stakeholders are parents, students, teachers, policy makers, and work place training supervisors. The 9 attributes are employer appreciation of students, graduation rate, obtained computer skills of students, mentoring hours in workplace learning/Students Industrial Work Experience Scheme (SIWES), challenge, structure, students’ appreciation of teachers, schooling hours, and attention to civic education. 346 respondents (comprising Parents, Students, Teachers, Policy Makers, and Workplace Training Supervisors) were repeatedly asked to rank a set of 4 programs, each with a specific value on the nine quality indicators. Conjoint analysis was used to obtain the values that the stakeholders assigned to the 9 attributes when evaluating the quality of TVET programs. Rank-ordered logistic regression was the statistical/tool used for ranking the respondents values assign to the attributes. The similarities and diversity in values and interests of the different stakeholders will be of use by both Nigerian government and TVET colleges, to improve the overall quality of education and the match between vocational programs and their stakeholders simultaneous evaluation and combination of information in product attributes. Such approach models the decision environment by confronting a respondent with choices that are close to real-life choices. Therefore, it is more realistically than traditional survey methods.

Keywords: TVET, vignette study, conjoint analysis, quality perception, educational stakeholders

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15819 Deep Learning Based Road Crack Detection on an Embedded Platform

Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

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It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

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15818 Exploring the Effect of Using Lesh Model in Enhancing Prospective Mathematics Teachers’ Number Sense

Authors: Areej Isam Barham

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Developing students’ number sense is an essential element in the learning of mathematics. Number sense is one of the foundational ideas in mathematics where students need to understand numbers, representing them in different ways, and realize the relationships among numbers. Number sense also reflects students’ understanding of the meaning of operations, how they related to one another, how to compute fluently and make reasonable estimates. Developing students’ number sense in the mathematics classroom requires good preparation for mathematics teachers, those who will direct their students towards the real understanding of numbers and its implementation in the learning of mathematics. This study describes the development of elementary prospective mathematics teachers’ number sense through a mathematics teaching methods course at Qatar University. The study examined the effect of using the Lesh model in enhancing mathematics prospective teachers’ number sense. Thirty-nine elementary prospective mathematics teachers involved in the current study. The study followed an experimental research approach, and quantitative research methods were used to answer the research questions. Pre-post number sense test was constructed and implemented before and after teaching by using the Lesh model. Data were analyzed using Statistical Packages for Social Sciences (SPSS). Descriptive data analysis and t-test were used to examine the impact of using the Lesh model in enhancing prospective teachers’ number sense. Finding of the study indicated poor number sense and limited numeracy skills before implementing the use of the Lesh model, which highly demonstrate the importance of the study. The results of the study also revealed a positive impact on the use of the Lesh model in enhancing prospective teachers’ number sense with statistically significant differences. The discussion of the study addresses different features and issues related to the participants’ number sense. In light of the study, the research presents recommendations and suggestions for the future development of mathematics prospective teachers’ number sense.

Keywords: number sense, Lesh model, prospective mathematics teachers, development of number sense

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15817 Modeling of International Financial Integration: A Multicriteria Decision

Authors: Zouari Ezzeddine, Tarchoun Monaem

Abstract:

Despite the multiplicity of advanced approaches, the concept of financial integration couldn’t be an explicit analysis. Indeed, empirical studies appear that the measures of international financial integration are one-dimensional analyses. For the ambivalence of the concept and its multiple determinants, it must be analyzed in multidimensional level. The interest of this research is a proposal of a decision support by multicriteria approach for determining the positions of countries according to their international and financial dependencies links with the behavior of financial actors (trying to make governance decisions or diversification strategies of international portfolio ...

Keywords: financial integration, decision support, behavior, multicriteria approach, governance and diversification

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15816 Transforming Butterworth Low Pass Filter into Microstrip Line Form at LC-Band Applications

Authors: Liew Hui Fang, Syed Idris Syed Hassan, Mohd Fareq Abd. Malek, Yufridin Wahab, Norshafinash Saudin

Abstract:

The paper implementation new approach method applied into transforming lumped element circuit into microstrip line form for Butterworth low pass filter which is operating at LC band. The filter’s lumped element circuits and microstrip line form were first designed and simulated using Advanced Design Software (ADS) to obtain the best filter characteristic based on S-parameter and implemented on FR4 substrate for order N=3,4,5,6,7,8 and 9. The importance of a new approach of transforming method as a correction factor has been considered into designed microstrip line. From ADS simulation results proved that the response of microstrip line circuit of Butterworth low pass filter with fringing correction factor has an excellent agreement with its lumped circuit. This shows that the new approach of transforming lumped element circuit into microstrip line is able to solve the conventional design of complexity size of circuit of Butterworth low pass filter (LPF) into microstrip line.

Keywords: Butterworth low pass filter, number of order, microstrip line, microwave filter, maximally flat

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15815 Construction of India’s Largest Blast Furnace (4554 cum) Foundation at JSPL, Angul, Odisha: A Qualitative Approach

Authors: N. S. S. Rao, Tapan Kumar Das, Latiful Pasha

Abstract:

Tata Projects Limited (TPL) located in Hyderabad, India has taken up the challenging venture of executing the entire civil works for India’s largest Blast Furnace with a capacity of 4554 cum at Jindal Steel and Power Limited (JSPL), Angul, Odisha, India. The following write-up briefly elaborates the various steps and methodologies involved in the construction of the foundation for this India’s largest blast furnace.

Keywords: blast furnace, construction, qualitative, approach

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15814 Trainees' Perception of Virtual Learning Skills in Setting up the Simulator Welding Technology

Authors: Mohd Afif Md Nasir, Mohd Faizal Amin Nur, Jamaluddin Hasim, Abd Samad Hasan Basari, Mohd Halim Sahelan

Abstract:

This study is aimed to investigate the suitability of Computer-Based Training (CBT) as one of the approaches in skills competency development at the Centre of Instructor and Advanced Skills Training (CIAST) Shah Alam Selangor and National Youth Skills Institute (NYSI) Pagoh Muar Johor. This study has also examined the perception among trainees toward Virtual Learning Environment (VLE) as to realize the development of skills in Welding Technology. The significance of the study is to create a computer-based skills development approach in welding technology among new trainees in CIAST and IKBN as well as to cultivate the element of general skills among them. This study is also important in elevating the number of individual knowledge workers (K-Workers) working in manufacturing industry in order to achieve the national vision which is to be an industrial nation in the year 2020. The design is a survey of research which using questionnaires as the instruments and is conducted towards 136 trainees from CIAST and IKBN. Data from the questionnaires is proceeding in a Statistical Package for Social Science (SPSS) in order to find the frequency, mean and chi-square testing. The findings of the study show the welding technology skills have developed in the trainees as a result of the application of the Virtual Reality simulator at a high level (mean=3.90) and the respondents agreed the skills could be embedded through the application of the Virtual Reality simulator (78.01%). The Study also found that there is a significant difference between trainee skill characteristics through the application of the Virtual Reality simulator (p<0.05). Thereby, the Virtual Reality simulator is suitable to be used in the development of welding skills among trainees through the skills training institute.

Keywords: computer-based training, virtual learning environment, welding technology, virtual reality simulator, virtual learning environment

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15813 Optimal Solutions for Real-Time Scheduling of Reconfigurable Embedded Systems Based on Neural Networks with Minimization of Power Consumption

Authors: Ghofrane Rehaiem, Hamza Gharsellaoui, Samir Benahmed

Abstract:

In this study, Artificial Neural Networks (ANNs) were used for modeling the parameters that allow the real-time scheduling of embedded systems under resources constraints designed for real-time applications running. The objective of this work is to implement a neural networks based approach for real-time scheduling of embedded systems in order to handle real-time constraints in execution scenarios. In our proposed approach, many techniques have been proposed for both the planning of tasks and reducing energy consumption. In fact, a combination of Dynamic Voltage Scaling (DVS) and time feedback can be used to scale the frequency dynamically adjusting the operating voltage. Indeed, we present in this paper a hybrid contribution that handles the real-time scheduling of embedded systems, low power consumption depending on the combination of DVS and Neural Feedback Scheduling (NFS) with the energy Priority Earlier Deadline First (PEDF) algorithm. Experimental results illustrate the efficiency of our original proposed approach.

Keywords: optimization, neural networks, real-time scheduling, low-power consumption

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15812 Saudi Women Facing Challenges in a Mixed-Gender Work Environment

Authors: A. Aldawsari

Abstract:

The complex issue of women working in a mixed-gender work environment has its roots in social and cultural factors. This research was done to identify and explore the social and cultural challenges Saudi women face in a mixed-gender work environment in Saudi Arabia. Over the years, Saudi women in mixed-gender work environments in Saudi Arabia have been of interest in various research areas, especially within the context of a hospital work environment. This research, which involves a female researcher interacting one-on-one with Saudi women, will address this issue as well as the effect of the 2030 Vision in Saudi Arabia, and it will aim to include several new fields of work environments for women in Saudi Arabia. The aim of this research is to examine the perceptions of Saudi women who work in a mixed gender environment regarding the general empowerment of women in these settings. The objective of this research is to explore the cultural and social challenges that influence Saudi women's rights to work in a mixed-gender environment in Saudi Arabia. The significance of this research lies in the fact that there is an urgency to resolve issue of female employment in Saudi Arabia, where Saudi women still suffer from inequality in employment opportunity. Although the Saudi government is seeking to empower women by integrating them into a mixed-gender work environment, which is a key goal and prominent social change advocated for in the 2030 Vision, this same goal is one of the main challenges in the face of achieving female empowerment. The methodology section focuses on appropriate methods that can be used to study the effect of social and cultural challenges on the employment of women. It then determines the conditions and limitations of the research by applying a qualitative research approach to the investigation and analysing the data collected from the interviews. A statistical analysis tool, such as NVivo, will be used for the qualitative analysis of the interviews. The study found that the factor most responsible for creating social and cultural challenges is family—whether close family or distant family—more so than tribe or community.

Keywords: women, work, mixed-gender, environment

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15811 Feature Extraction and Classification Based on the Bayes Test for Minimum Error

Authors: Nasar Aldian Ambark Shashoa

Abstract:

Classification with a dimension reduction based on Bayesian approach is proposed in this paper . The first step is to generate a sample (parameter) of fault-free mode class and faulty mode class. The second, in order to obtain good classification performance, a selection of important features is done with the discrete karhunen-loeve expansion. Next, the Bayes test for minimum error is used to classify the classes. Finally, the results for simulated data demonstrate the capabilities of the proposed procedure.

Keywords: analytical redundancy, fault detection, feature extraction, Bayesian approach

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15810 The Effectiveness of Using Functional Rehabilitation with Children of Cerebral Palsy

Authors: Bara Yousef

Abstract:

The development of independency and functional participation is an important therapeutic goal for many children with cerebral palsy,They was many therapeutic approach have been used for treatment those children like neurodevelopment treatment, balance training strengthening and stretching exercise. More recently, therapy for children with cerebral palsy has focused on achieving functional goals using task-oriented interventions and summer camping model, which focus on activities that relevant and meaningful to the child, to learn more efficient and effective motor skills. We explore the effectiveness of using functional rehabilitation comparing with regular rehabilitation among 40 Saudi children with cerebral palsy in pediatric unit at Sultan Bin Abdul Aziz Humanitarian City-Ksa ,where 20 children randomly assign in control group who received rehabilitation based on regular therapy approach and other 20 children assign on experiment group who received rehabilitation based on functional therapy approach with an average of 45min OT treatment and 45 min PT treatment- daily within a period of 6 week. Our finding reported that children in experiment group has improved in gross motor function with an average from 49.4 to 57.6 based on GMFM 66 as primary outcome measure and improved in WeeFIM with an average from 52 to 62 while children in control group has improved with an average from 48.4 to 53.7 in GMFM and from 53 to and 58 in WeeFIM. Consequently, there has been growing interest in determining the effects of functional training programs as promising approach for these children.

Keywords: Cerebral Palsy (CP), gross motor function measure (GMFM66), pediatric Functional Independent Measure (WeeFIM), rehabilitation, disability

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15809 Earthquake Identification to Predict Tsunami in Andalas Island, Indonesia Using Back Propagation Method and Fuzzy TOPSIS Decision Seconder

Authors: Muhamad Aris Burhanudin, Angga Firmansyas, Bagus Jaya Santosa

Abstract:

Earthquakes are natural hazard that can trigger the most dangerous hazard, tsunami. 26 December 2004, a giant earthquake occurred in north-west Andalas Island. It made giant tsunami which crushed Sumatra, Bangladesh, India, Sri Lanka, Malaysia and Singapore. More than twenty thousand people dead. The occurrence of earthquake and tsunami can not be avoided. But this hazard can be mitigated by earthquake forecasting. Early preparation is the key factor to reduce its damages and consequences. We aim to investigate quantitatively on pattern of earthquake. Then, we can know the trend. We study about earthquake which has happened in Andalas island, Indonesia one last decade. Andalas is island which has high seismicity, more than a thousand event occur in a year. It is because Andalas island is in tectonic subduction zone of Hindia sea plate and Eurasia plate. A tsunami forecasting is needed to mitigation action. Thus, a Tsunami Forecasting Method is presented in this work. Neutral Network has used widely in many research to estimate earthquake and it is convinced that by using Backpropagation Method, earthquake can be predicted. At first, ANN is trained to predict Tsunami 26 December 2004 by using earthquake data before it. Then after we get trained ANN, we apply to predict the next earthquake. Not all earthquake will trigger Tsunami, there are some characteristics of earthquake that can cause Tsunami. Wrong decision can cause other problem in the society. Then, we need a method to reduce possibility of wrong decision. Fuzzy TOPSIS is a statistical method that is widely used to be decision seconder referring to given parameters. Fuzzy TOPSIS method can make the best decision whether it cause Tsunami or not. This work combines earthquake prediction using neural network method and using Fuzzy TOPSIS to determine the decision that the earthquake triggers Tsunami wave or not. Neural Network model is capable to capture non-linear relationship and Fuzzy TOPSIS is capable to determine the best decision better than other statistical method in tsunami prediction.

Keywords: earthquake, fuzzy TOPSIS, neural network, tsunami

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15808 Sensor and Sensor System Design, Selection and Data Fusion Using Non-Deterministic Multi-Attribute Tradespace Exploration

Authors: Matthew Yeager, Christopher Willy, John Bischoff

Abstract:

The conceptualization and design phases of a system lifecycle consume a significant amount of the lifecycle budget in the form of direct tasking and capital, as well as the implicit costs associated with unforeseeable design errors that are only realized during downstream phases. Ad hoc or iterative approaches to generating system requirements oftentimes fail to consider the full array of feasible systems or product designs for a variety of reasons, including, but not limited to: initial conceptualization that oftentimes incorporates a priori or legacy features; the inability to capture, communicate and accommodate stakeholder preferences; inadequate technical designs and/or feasibility studies; and locally-, but not globally-, optimized subsystems and components. These design pitfalls can beget unanticipated developmental or system alterations with added costs, risks and support activities, heightening the risk for suboptimal system performance, premature obsolescence or forgone development. Supported by rapid advances in learning algorithms and hardware technology, sensors and sensor systems have become commonplace in both commercial and industrial products. The evolving array of hardware components (i.e. sensors, CPUs, modular / auxiliary access, etc…) as well as recognition, data fusion and communication protocols have all become increasingly complex and critical for design engineers during both concpetualization and implementation. This work seeks to develop and utilize a non-deterministic approach for sensor system design within the multi-attribute tradespace exploration (MATE) paradigm, a technique that incorporates decision theory into model-based techniques in order to explore complex design environments and discover better system designs. Developed to address the inherent design constraints in complex aerospace systems, MATE techniques enable project engineers to examine all viable system designs, assess attribute utility and system performance, and better align with stakeholder requirements. Whereas such previous work has been focused on aerospace systems and conducted in a deterministic fashion, this study addresses a wider array of system design elements by incorporating both traditional tradespace elements (e.g. hardware components) as well as popular multi-sensor data fusion models and techniques. Furthermore, statistical performance features to this model-based MATE approach will enable non-deterministic techniques for various commercial systems that range in application, complexity and system behavior, demonstrating a significant utility within the realm of formal systems decision-making.

Keywords: multi-attribute tradespace exploration, data fusion, sensors, systems engineering, system design

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15807 The Effect of Core Training on Physical Fitness Characteristics in Male Volleyball Players

Authors: Sibel Karacaoglu, Fatma Ç. Kayapinar

Abstract:

The aim of the study is to investigate the effect of the core training program on physical fitness characteristics and body composition in male volleyball players. 26 male university volleyball team players aged between 19 to 24 years who had no health problems and injury participated in the study. Subjects were divided into training (TG) and control groups (CG) as randomly. Data from twenty-one players who completed all training sessions were used for statistical analysis (TG,n=11; CG,n=10). A core training program was applied to the training group three days a week for 10 weeks. On the other hand, the control group did not receive any training. Before and after the 10-week training program, pre- and post-testing comprised of body composition measurements (weight, BMI, bioelectrical impedance analysis) and physical fitness measurements including flexibility (sit and reach test), muscle strength (back, leg and grip strength by dynamometer), muscle endurance (sit-ups and push-ups tests), power (one-legged jump and vertical jump tests), speed (20m sprint, 30m sprint) and balance tests (one-legged standing test) were performed. Changes of pre- and post- test values of the groups were determined by using dependent t test. According to the statistical analysis of data, no significant difference was found in terms of body composition in the both groups for pre- and post- test values. In the training group, all physical fitness measurements improved significantly after core training program (p<0.05) except 30m speed and handgrip strength (p>0.05). On the hand, only 20m speed test values improved after post-test period (p<0.05), but the other physical fitness tests values did not differ (p>0.05) between pre- and post- test measurement in the control group. The results of the study suggest that the core training program has positive effect on physical fitness characteristics in male volleyball players.

Keywords: body composition, core training, physical fitness, volleyball

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15806 Assessment the Quality of Telecommunication Services by Fuzzy Inferences System

Authors: Oktay Nusratov, Ramin Rzaev, Aydin Goyushov

Abstract:

Fuzzy inference method based approach to the forming of modular intellectual system of assessment the quality of communication services is proposed. Developed under this approach the basic fuzzy estimation model takes into account the recommendations of the International Telecommunication Union in respect of the operation of packet switching networks based on IP-protocol. To implement the main features and functions of the fuzzy control system of quality telecommunication services it is used multilayer feedforward neural network.

Keywords: quality of communication, IP-telephony, fuzzy set, fuzzy implication, neural network

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15805 Theorizing Optimal Use of Numbers and Anecdotes: The Science of Storytelling in Newsrooms

Authors: Hai L. Tran

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When covering events and issues, the news media often employ both personal accounts as well as facts and figures. However, the process of using numbers and narratives in the newsroom is mostly operated through trial and error. There is a demonstrated need for the news industry to better understand the specific effects of storytelling and data-driven reporting on the audience as well as explanatory factors driving such effects. In the academic world, anecdotal evidence and statistical evidence have been studied in a mutually exclusive manner. Existing research tends to treat pertinent effects as though the use of one form precludes the other and as if a tradeoff is required. Meanwhile, narratives and statistical facts are often combined in various communication contexts, especially in news presentations. There is value in reconceptualizing and theorizing about both relative and collective impacts of numbers and narratives as well as the mechanism underlying such effects. The current undertaking seeks to link theory to practice by providing a complete picture of how and why people are influenced by information conveyed through quantitative and qualitative accounts. Specifically, the cognitive-experiential theory is invoked to argue that humans employ two distinct systems to process information. The rational system requires the processing of logical evidence effortful analytical cognitions, which are affect-free. Meanwhile, the experiential system is intuitive, rapid, automatic, and holistic, thereby demanding minimum cognitive resources and relating to the experience of affect. In certain situations, one system might dominate the other, but rational and experiential modes of processing operations in parallel and at the same time. As such, anecdotes and quantified facts impact audience response differently and a combination of data and narratives is more effective than either form of evidence. In addition, the present study identifies several media variables and human factors driving the effects of statistics and anecdotes. An integrative model is proposed to explain how message characteristics (modality, vividness, salience, congruency, position) and individual differences (involvement, numeracy skills, cognitive resources, cultural orientation) impact selective exposure, which in turn activates pertinent modes of processing, and thereby induces corresponding responses. The present study represents a step toward bridging theoretical frameworks from various disciplines to better understand the specific effects and the conditions under which the use of anecdotal evidence and/or statistical evidence enhances or undermines information processing. In addition to theoretical contributions, this research helps inform news professionals about the benefits and pitfalls of incorporating quantitative and qualitative accounts in reporting. It proposes a typology of possible scenarios and appropriate strategies for journalists to use when presenting news with anecdotes and numbers.

Keywords: data, narrative, number, anecdote, storytelling, news

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15804 Improvements in OpenCV's Viola Jones Algorithm in Face Detection–Skin Detection

Authors: Jyoti Bharti, M. K. Gupta, Astha Jain

Abstract:

This paper proposes a new improved approach for false positives filtering of detected face images on OpenCV’s Viola Jones Algorithm In this approach, for Filtering of False Positives, Skin Detection in two colour spaces i.e. HSV (Hue, Saturation and Value) and YCrCb (Y is luma component and Cr- red difference, Cb- Blue difference) is used. As a result, it is found that false detection has been reduced. Our proposed method reaches the accuracy of about 98.7%. Thus, a better recognition rate is achieved.

Keywords: face detection, Viola Jones, false positives, OpenCV

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15803 Fathers’ Rights to Contact and Care: Moving Beyond the Adversarial Approach

Authors: Wesahl Domingo, Prinslean Mahery

Abstract:

Our paper focuses on the rights’ to contact and care of fathers in the heterosexual context, despite the reality of same sex parenting in South Africa. We argue that despite the new South African Children’s Act framework creating a shift from the idea of parental power over a child to the notion that parents have parental responsibilities and rights in respect of a child. This shift has however not fundamentally changed the constant battle that parents and other interested parties have over children. In most cases it is fathers who must battle to either maintain contact with their child/ren or fight to have care (which includes custody) of their child/ren. This is the case whether or not the father was married to the mother of the child in question. In part one of the paper, we deal with the historical development of rights to care and contact and describe the current system in the context of case law and legislation in South Africa. Part two provides a critical analysis of a few anthologies of “what fathers are complaining about.” In conclusion, in part three, we outline the way forward –“moving beyond the adversarial approach” through the “care of ethics approach.” So what is the care perspective? The care perspective is a relational ethic which views the primary moral concern as of creating and sustaining responsive connection to others. We apply the care of ethics approach to parenting plans and family law mediation in the context of fathers’ rights to care and contact. We argue by avoiding the adversarial system and engaging in a problem solving process focused on finding solutions for the future, divorcing parents can turn their attention to their children rather than battling each other.

Keywords: fathers' right to care, contact, custody, family law

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15802 Secularism and Political Inclusion: Turkey in the 2000s

Authors: Edgar Sar

Abstract:

For more than a decade, secularism’s compatibility with religion has been called into question. Particularly, secular states’ exclusionary practices were raised to prove that secularism is not necessary for democracy. Meanwhile, with the debut of Turkey’s Justice and Development Party (AKP) in 2002, Turkish state’s approach to religion has gradually changed. It is argued in that presentation that this change has led Turkey to a process of de-secularization, which refers to a considerable regress in state’s inclusionary and pluralist credentials. In this regard, this study both reflects on the relationship between secularism and democracy within the context of Turkish experience and analyses the consequences of the process of de-secularization of state in Turkey. To analyze Turkish state’s changing approach to religion and measure the de-secularization of the state, the connection between state and religion will be examined in three levels: ends, institutions, and law and policies. The presentation will indicate that Turkish state’s connection with religion in all three levels significantly weakened its secular credentials, which at the same time risked state’s commitment to neutrality, freedom of conscience and equality. In this regard, the change in Turkish state’s approach to religion throughout the 2000s, which this study refers to as the process of the de-secularization of the state, also brought about a process of de-democratization for Turkey.

Keywords: AKP, political inclusion, secularism, Turkey

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15801 Implementation of Gender Policy in the Georgian National Defence: Key Issues and Challenges

Authors: Vephkhvia Grigalashvili

Abstract:

The defense of Georgia is every citizen’s duty. The present article reviews the principles and standards of gender policy in the Georgian national defense sector. In addition, it looks at mechanisms for ensuring gender equality, going through the relevant Georgian legislation. Furthermore, this work aims to conduct a comparative analysis of defense models of Georgia, Finland, and the Baltic States in order to identify core institutional challenges. The study produced the following findings:(a) The national defense planning is based on the Total Defense approach, which implies a wide involvement of the country`s population in state defense. (b) This political act does not specify gender equality aspects of the Total Defense strategy; (c) According to the Constitution of Georgia, irrespective of gender factors, every citizen of Georgia is legally obliged to participate in state security activities. However, the state has an authority (power of choice) to decide which gender group (male or/and female citizen) must fulfill above mentioned their constitutional commitment. For instance, completion of compulsory military and reserve military services is a male citizen’s duty, whereas professional military service is equally accessible to both genders. The study concludes that effective implementation of the Total Defense concept largely depends on how Georgia uses its capabilities and human resources. Based on the statistical fact that more than 50% of the country’s population are women, Georgia has to elaborate on relevant institutional mechanisms for implementation of gender equality in the national defense organization. In this regard, it would be advisable: (i) to give the legal opportunity to women to serve in compulsory military service, and (ii) to develop labor reserve service as a part of the anti-crisis management system of Georgia.

Keywords: gender in defense organisation, gender mechanisms, gender in defense policy, gender policy

Procedia PDF Downloads 164
15800 A Machine Learning Approach for Classification of Directional Valve Leakage in the Hydraulic Final Test

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

Due to increasing cost pressure in global markets, artificial intelligence is becoming a technology that is decisive for competition. Predictive quality enables machinery and plant manufacturers to ensure product quality by using data-driven forecasts via machine learning models as a decision-making basis for test results. The use of cross-process Bosch production data along the value chain of hydraulic valves is a promising approach to classifying the quality characteristics of workpieces.

Keywords: predictive quality, hydraulics, machine learning, classification, supervised learning

Procedia PDF Downloads 233
15799 Comparative Assessment on the Impact of Sedatives on the Stress and Anxiety of Patients with a Heart Disease before and during Surgery in Iran

Authors: Farhad Fakoursevom

Abstract:

Heart disease is one of the diseases which is found in abundance today. Various types of surgeries, such as bypasses, angiography, angioplasty, etc., are used to treat patients. People may receive such surgeries, some of which are invasive and some non-invasive, throughout their lives. People might cope with pre-surgery anxiety and stress, which can disrupt their normal life and even reduce the effects of the surgery, so the desired result can not be achieved in surgery. Considering this issue, the present study aimed to do a comparative assessment of people who received sedatives before surgery and people who did not receive sedatives. In terms of the purpose, this is an applied research and descriptive survey in terms of method. The statistical population included patients who underwent surgeries in the specialist heart hospitals of Mashhad, Iran; 60 people were considered as a statistical population, 30 of them received sedatives before surgery, and 30 others had not received sedatives before surgery. Valid and up-to-date articles were systematically used to collect theoretical bases, and a researcher-made questionnaire was used to examine the level of stress and anxiety of people. The questionnaire content validity was assessed by a panel of experts in psychology and medicine. The construct validity was tested using the software. Cronbach's alpha and composite reliability were used for reliability, which shows the appropriate reliability of the questionnaire. SPSS software was used to compare the research results between two groups, and the research findings showed that there is no significant association between the people who received sedatives and those who did not receive sedatives in terms of the amount of stress and anxiety. The longer the time of taking the drugs before the surgery, the more the mental peace of the patients will be. According to the results, it can be said that if we don't need to have an emergency operation and need more time, we have to use sedative drugs with different doses compared to the severity of the surgery, and also in case of a medical emergency such as heart surgery due to a stroke, we have to take advantage of psychological services during and before the operation and sedative drugs so that the patients can control their stress and anxiety and achieve better outcomes.

Keywords: sedative drugs, stress, anxiety, surgery

Procedia PDF Downloads 99
15798 A Statistical Approach to Predict and Classify the Commercial Hatchability of Chickens Using Extrinsic Parameters of Breeders and Eggs

Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

Abstract:

Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

Procedia PDF Downloads 88
15797 Business Intelligent to a Decision Support Tool for Green Entrepreneurship: Meso and Macro Regions

Authors: Anishur Rahman, Maria Areias, Diogo Simões, Ana Figeuiredo, Filipa Figueiredo, João Nunes

Abstract:

The circular economy (CE) has gained increased awareness among academics, businesses, and decision-makers as it stimulates resource circularity in the production and consumption systems. A large epistemological study has explored the principles of CE, but scant attention eagerly focused on analysing how CE is evaluated, consented to, and enforced using economic metabolism data and business intelligent framework. Economic metabolism involves the ongoing exchange of materials and energy within and across socio-economic systems and requires the assessment of vast amounts of data to provide quantitative analysis related to effective resource management. Limited concern, the present work has focused on the regional flows pilot region from Portugal. By addressing this gap, this study aims to promote eco-innovation and sustainability in the regions of Intermunicipal Communities Região de Coimbra, Viseu Dão Lafões and Beiras e Serra da Estrela, using this data to find precise synergies in terms of material flows and give companies a competitive advantage in form of valuable waste destinations, access to new resources and new markets, cost reduction and risk sharing benefits. In our work, emphasis on applying artificial intelligence (AI) and, more specifically, on implementing state-of-the-art deep learning algorithms is placed, contributing to construction a business intelligent approach. With the emergence of new approaches generally highlighted under the sub-heading of AI and machine learning (ML), the methods for statistical analysis of complex and uncertain production systems are facing significant changes. Therefore, various definitions of AI and its differences from traditional statistics are presented, and furthermore, ML is introduced to identify its place in data science and the differences in topics such as big data analytics and in production problems that using AI and ML are identified. A lifecycle-based approach is then taken to analyse the use of different methods in each phase to identify the most useful technologies and unifying attributes of AI in manufacturing. Most of macroeconomic metabolisms models are mainly direct to contexts of large metropolis, neglecting rural territories, so within this project, a dynamic decision support model coupled with artificial intelligence tools and information platforms will be developed, focused on the reality of these transition zones between the rural and urban. Thus, a real decision support tool is under development, which will surpass the scientific developments carried out to date and will allow to overcome imitations related to the availability and reliability of data.

Keywords: circular economy, artificial intelligence, economic metabolisms, machine learning

Procedia PDF Downloads 73
15796 The Work System Method for Designing Knowledge Mobilization Projects

Authors: Chihab Benmoussa

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Could the Work System Approach (WSA) function as a framework for designing high-impact knowledge mobilization systems? This paper put forward arguments in favor of the applicability of WSA for knowledge mobilization design based on evidences from a practical research. Normative approaches for practitioners are highly needed especially in the field of knowledge management (KM), given the abysmal rate of disappointment and failure of KM projects. The paper contrasts knowledge management and knowledge mobilization, presents the WSA and showed how the WSA’s concepts and ideas fit with the approach adopted by a multinational company in designing a successful knowledge mobilization initiative.

Keywords: knowledge management, knowledge mobilizations, work system method

Procedia PDF Downloads 524
15795 Numerical Investigation of a New Two-Fluid Model for Semi-Dilute Polymer Solutions

Authors: Soroush Hooshyar, Mohamadali Masoudian, Natalie Germann

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Many soft materials such as polymer solutions can develop localized bands with different shear rates, which are known as shear bands. Using the generalized bracket approach of nonequilibrium thermodynamics, we recently developed a new two-fluid model to study shear banding for semi-dilute polymer solutions. The two-fluid approach is an appropriate means for describing diffusion processes such as Fickian diffusion and stress-induced migration. In this approach, it is assumed that the local gradients in concentration and, if accounted for, also stress generate a nontrivial velocity difference between the components. Since the differential velocity is treated as a state variable in our model, the implementation of the boundary conditions arising from the derivative diffusive terms is straightforward. Our model is a good candidate for benchmark simulations because of its simplicity. We analyzed its behavior in cylindrical Couette flow, a rectilinear channel flow, and a 4:1 planar contraction flow. The latter problem was solved using the OpenFOAM finite volume package and the impact of shear banding on the lip and salient vortices was investigated. For the other smooth geometries, we employed a standard Chebyshev pseudospectral collocation method. The results showed that the steady-state solution is unique with respect to initial conditions, deformation history, and the value of the diffusivity constant. However, smaller the value of the diffusivity constant is, the more time it takes to reach the steady state.

Keywords: nonequilibrium thermodynamics, planar contraction, polymer solutions, shear banding, two-fluid approach

Procedia PDF Downloads 333
15794 Accelerating Quantum Chemistry Calculations: Machine Learning for Efficient Evaluation of Electron-Repulsion Integrals

Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs, and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine-learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient but not the magnitude. A neural network with two hidden layers were then used to learn the coefficient magnitudes along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction

Procedia PDF Downloads 116