Search results for: machine learning approach for neurological disorder assessment
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 24563

Search results for: machine learning approach for neurological disorder assessment

15503 Rare Case of Pyoderma Gangrenosum of the Upper Limb

Authors: Karissa A. Graham

Abstract:

Pyoderma gangrenosum (PG) is a prototypic autoinflammatory neutrophilic dermatosis that is a rare disorder. It presents a diagnostic challenge owing to its variable presentation, clinical overlap with other conditions, it is often associated with other systemic conditions, and there is no definitive histological or laboratory characteristic. The Delphai consensus for PG includes the presence of at least one ulcer on the anterior lower limb. Systemic corticosteroids and immunosuppressive therapies are the mainstay treatment for PG. We describe a case report of delayed diagnosis of ulcerative pyoderma gangrenosum in a 44-year-old male on his forearm. The patient presented with an infected ulcer on his right forearm that had been present for over three years. The patient was a Type 2 Diabetic with no personal or family history of inflammatory bowel disease or other autoimmune diseases. The patient was initially investigated for malignancy, but biopsies returned as chronic inflammatory tissue with neutrophilic infiltrate and no malignancy. The patient was commenced on systemic prednisone for the treatment of pyoderma gangrenosum. The diagnosis of ulcerative PG poses a challenge given the vast differential diagnosis for a cutaneous ulcer (i.e., malignant, vascular, autoimmune, trauma, infective, etc.). Diagnostic accuracy is important given that the treatment for PG with steroids does not go without risks and indeed may be contraindicated in other potential causes of the ulcer. Indeed, more common and more sinister causes of ulcers should be investigated first, as death from PG is quite rare.

Keywords: dermatological diagnosis, dermatosis, pyoderma gangrenosum, rare presentation

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15502 Gas While Drilling (GWD) Classification in Betara Complex; An Effective Approachment to Optimize Future Candidate of Gumai Reservoir

Authors: I. Gusti Agung Aditya Surya Wibawa, Andri Syafriya, Beiruny Syam

Abstract:

Gumai Formation which acts as regional seal for Talang Akar Formation becomes one of the most prolific reservoir in South Sumatra Basin and the primary exploration target in this area. Marine conditions were eventually established during the continuation of transgression sequence leads an open marine facies deposition in Early Miocene. Marine clastic deposits where calcareous shales, claystone and siltstones interbedded with fine-grained calcareous and glauconitic sandstones are the domination of lithology which targeted as the hydrocarbon reservoir. All this time, the main objective of PetroChina’s exploration and production in Betara area is only from Lower Talang Akar Formation. Successful testing in some exploration wells which flowed gas & condensate from Gumai Formation, opened the opportunity to optimize new reservoir objective in Betara area. Limitation of conventional wireline logs data in Gumai interval is generating technical challenge in term of geological approach. A utilization of Gas While Drilling indicator initiated with the objective to determine the next Gumai reservoir candidate which capable to increase Jabung hydrocarbon discoveries. This paper describes how Gas While Drilling indicator is processed to generate potential and non-potential zone by cut-off analysis. Validation which performed by correlation and comparison with well logs, Drill Stem Test (DST), and Reservoir Performance Monitor (RPM) data succeed to observe Gumai reservoir in Betara Complex. After we integrated all of data, we are able to generate a Betara Complex potential map and overlaid with reservoir characterization distribution as a part of risk assessment in term of potential zone presence. Mud log utilization and geophysical data information successfully covered the geological challenges in this study.

Keywords: Gumai, gas while drilling, classification, reservoir, potential

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15501 Oil Logistics for Refining to Northern Europe

Authors: Vladimir Klepikov

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To develop the programs to supply crude oil to North European refineries, it is necessary to take into account the refineries’ location, crude refining capacity, and the transport infrastructure capacity. Among the countries of the region, we include those having a marine boundary along the Northern Sea and the Baltic Sea (from France in the west to Finland in the east). The paper envisages the geographic allocation of the refineries and contains the evaluation of the refineries’ capacities for the region under review. The sustainable operations of refineries in the region are determined by the transportation system capacity to supply crude oil to them. The assessment of capacity of crude oil transportation to the refineries is conducted. The research is performed for the period of 2005/2015, using the quantitative analysis method. The countries are classified by the refineries’ aggregate capacities and the crude oil output on their territory. The crude oil output capacities in the region in the period under review are determined. The capacities of the region’s transportation system to supply crude oil produced in the region to the refineries are revealed. The analysis suggested that imported raw materials are the main source of oil for the refineries in the region. The main sources of crude oil supplies to North European refineries are reviewed. The change in the refineries’ capacities in the group of countries and each particular country, as well as the utilization of the refineries' capacities in the region in the period under review, was studied. The input suggests that the bulk of crude oil is supplied by marine and pipeline transport. The paper contains the assessment of the crude oil transportation by pipeline transport in the overall crude oil cargo flow. The refineries’ production rate for the groups of countries under the review and for each particular country was the subject of study. Our study yielded the trend towards the increase in the crude oil refining at the refineries of the region and reduction in the crude oil output. If this trend persists in the near future, the cargo flow of imported crude oil and the utilization of the North European logistics infrastructure may increase. According to the study, the existing transport infrastructure in the region is able to handle the increasing imported crude oil flow.

Keywords: European region, infrastructure, oil terminal capacity, pipeline capacity, tanker draft

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15500 Critical and Strategic Issues in Compensation, Staffing and Personnel Management in Nigeria

Authors: Shonuga Olajumoke Adedoyinsola

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Staffing and Compensation are at the core of any employment exchange, and they serve as the defining characteristics of any employment relationship. Most organizations understand the benefits that a longer term approach to staff planning can bring and the answer to this problem lies not in trying to implement the traditional approach more effectively, but in implementing a completely different kind of process for strategic staffing. The study focuses on critical points of compensation, staffing and personnel management. The fundamentals of these programs include the elements of vision, potential, communication and motivation. The aim of the paper is to identify the most important attributes of compensation and incentives, staffing and personnel management. Research method is the analysis and synthesis of scientific literature, logical, comparative and graphic representation. On the basis of analysis, the author presents the models of these systems for positive employee attitudes and behaviors.

Keywords: compensation, employees, incentives, staffing, personnel management

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15499 Inventory Control for Purchased Part under Long Lead Time and Uncertain Demand: MRP vs Demand-Driven MRP Approach

Authors: M. J. Shofa, A. Hidayatno, O. M. Armand

Abstract:

MRP as a production control system is appropriate for the deterministic environment. Unfortunately, most production systems such as customer demands are stochastic. Demand-Driven MRP (DDMRP) is a new approach for inventory control system, and it deals with demand uncertainty. The objective of this paper is to compare the MRP and DDMRP work for a long lead time and uncertain demand in terms of on-hand inventory levels. The evaluation is conducted through a discrete event simulation using purchased part data from an automotive company. The result is MRP gives 50,759 pcs / day while DDMRP gives 34,835 pcs / day (reduce 32%), it means DDMRP is more effective inventory control than MRP in terms of on-hand inventory levels.

Keywords: Demand-Driven MRP, long lead time, MRP, uncertain demand

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15498 Assessing the Impacts of Folktales (Story Telling) On the Moral Advancement of Children Yoruba Communities in Ute-Owo, Nigeria

Authors: Felicia Titilayo Olanrewaju

Abstract:

Folktales are a subclass of folklores which are verbally told and passed down from one generation to another, from the elderly ones to their children, usually at moonlight. These tales are heavily laden with moral lessons of what should be done and what not within the society. Though these are oftentimes heavily embellished yet are related to guide, guard, train, and dishing out moral attributes and mores worthwhile for ethical progression of the young minds within our traditional settings. With the rapid advancement of technological know-how, the existence of most of these moral-inclined stories becomes questionable; hence this study appraised the influences of these traditional storytellings have in the upgrading of moral learning of ethical behavioral traits acceptable among the Yoruba people. Oral interviews couples with recording gadgets were used to collate both sample parents' and children’s responses within a particular community in Owo (ute) local government area of Owo Ondo State, Nigeria. Findings reveal that diverse tales told at moonlight periods have an untold impact on the speedy growth of the children intellectually than the modern happenings around them. These telltale stories become powerful aids in learning goodly traits and eschewing bad manners. It is recommended that folk stories be told within the household among the family after hard labour in the evenings as this would help develop human relationships and brings about a strong sense of community bindings.

Keywords: folktales, folklores, impact, advancement, ethical progression

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15497 Competition as an Appropriate Instructional Practice in the Physical Education Environment: Reflective Experiences

Authors: David Barney, Francis Pleban, Muna Muday

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The purpose of this study was to explore gender differences of former physical education students related to reflective experiences of competition in physical education learning environment. In the school environment, students are positioned in competitive situations, including in the physical education context. Therefore it is important to prepare future physical educators to address the role of competition in physical education. Participants for this study were 304 college-aged students and young adults (M = 1.53, SD = .500), from a private university and local community located in the western United States. When comparing gender, significant differences (p < .05) were reported for four (questions 5, 7, 12, and 14) of the nine scaling questions. Follow-up quantitative findings reported that males (41%) more than females (27%) witnessed fights in physical education environment during competitive games. Qualitative findings reported fighting were along the lines of verbal confrontation. Female participants tended to experience being excluded from games, when compared to male participants. Both male and female participants (total population; 95%, males; 98%; and females 92%) were in favor of including competition in physical education for students. Findings suggest that physical education teachers and physical education teacher education programs have a responsibility to develop gender neutral learning experiences that help students better appreciate the role competition plays, both in and out of the physical education classroom.

Keywords: competition, physical education, physical education teacher education, gender

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15496 A New OvS Approach in Assembly Line Balancing Problem

Authors: P. Azimi, B. Behtoiy, A. A. Najafi, H. R. Charmchi

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According to the previous studies, one of the most famous techniques which affect the efficiency of a production line is the assembly line balancing (ALB) technique. This paper examines the balancing effect of a whole production line of a real auto glass manufacturer in three steps. In the first step, processing time of each activity in the workstations is generated according to a practical approach. In the second step, the whole production process is simulated and the bottleneck stations have been identified, and finally in the third step, several improvement scenarios are generated to optimize the system throughput, and the best one is proposed. The main contribution of the current research is the proposed framework which combines two famous approaches including Assembly Line Balancing and Optimization via Simulation technique (OvS). The results show that the proposed framework could be applied in practical environments, easily.

Keywords: assembly line balancing problem, optimization via simulation, production planning

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15495 Metal Ship and Robotic Car: A Hands-On Activity to Develop Scientific and Engineering Skills for High School Students

Authors: Jutharat Sunprasert, Ekapong Hirunsirisawat, Narongrit Waraporn, Somporn Peansukmanee

Abstract:

Metal Ship and Robotic Car is one of the hands-on activities in the course, the Fundamental of Engineering that can be divided into three parts. The first part, the metal ships, was made by using engineering drawings, physics and mathematics knowledge. The second part is where the students learned how to construct a robotic car and control it using computer programming. In the last part, the students had to combine the workings of these two objects in the final testing. This aim of study was to investigate the effectiveness of hands-on activity by integrating Science, Technology, Engineering and Mathematics (STEM) concepts to develop scientific and engineering skills. The results showed that the majority of students felt this hands-on activity lead to an increased confidence level in the integration of STEM. Moreover, 48% of all students engaged well with the STEM concepts. Students could obtain the knowledge of STEM through hands-on activities with the topics science and mathematics, engineering drawing, engineering workshop and computer programming; most students agree and strongly agree with this learning process. This indicated that the hands-on activity: “Metal Ship and Robotic Car” is a useful tool to integrate each aspect of STEM. Furthermore, hands-on activities positively influence a student’s interest which leads to increased learning achievement and also in developing scientific and engineering skills.

Keywords: hands-on activity, STEM education, computer programming, metal work

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15494 Notice and Block?

Authors: Althaf Marsoof

Abstract:

The blocking injunction, giving rise to a ‘notice and block’ regime, has become the new approach to curtail the infringement of Intellectual Property rights on the Internet. As such, the blocking injunction is an addition to the arsenal of copyright owners, and more recently has also benefited trademark owners, in their battle against piracy and counterfeiting. Yet, the blocking injunction, notwithstanding the usefulness of its ‘notice and block’ outcome, is not without limitations. In the circumstances, it is argued that ‘notice and takedown’, the approach that has been adopted by right-holders for some years, is still an important remedy against the proliferation of online content that infringe the rights of copyright and trademark owners, which is both viable and effective. Thus, it is suggested that the battle against online piracy and counterfeiting could be won only if both the blocking injunction and the practice of ‘notice and takedown’ are utilised by right-holders as complementary and simultaneous remedies.

Keywords: blocking injunctions, internet intermediaries, notice and takedown, intellectual property

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15493 The Effectiveness of Non-surgical Treatment for Androgenetic Alopecia in Men: A Systematic Review and Meta-Analysis

Authors: Monica Trifitriana, Rido Mulawarman

Abstract:

Introduction: Androgenetic alopecia (AGA) is a genetically predetermined disorder due to an excessive response to dihydrotestosterone (DHT). Currently, non-surgical treatment of androgenetic alopecia is more in demand by the patient. There are many non-surgical treatments, ranging from topical treatments oral medications, and procedure treatments. Objective: We aim to assess the latest evidence of the efficacy of non-surgical treatments of androgenetic alopecia in men in comparison to placebo for improving hair density, thickness, and growth. Method: We performed a comprehensive search on topics that assess non-surgical treatments of androgenetic alopecia in men from inception up until November 2021. Result: There were 24 studies out of a total of 2438 patients divided into five non-surgical treatment groups to assess the effectiveness of hair growth, namely: minoxidil 2% (MD: 8.11 hairs/cm²), minoxidil 5% (MD: 12.02 hairs/cm²), low-level laser light therapy/LLLT (MD: 12.35 hairs/cm²), finasteride 1mg (MD: 20.43 hairs/cm²), and Platelete-Rich Plasma/PRP with microneedling (MD: 26.33 hairs/cm²). All treatments had significant results for increasing hair growth, particularly in cases of androgenetic alopecia in men (P<0.00001). Conclusion: From the results, it was found that the five non-surgical treatment groups proved to be effective and significant for hair growth, particularly in cases of androgenetic alopecia in men. In order of the best non-surgical treatment for hair growth is starting from PRP with microneedling, Finasteride 1mg, LLLT, minoxidil 5%, to minoxidil 2%.

Keywords: androgenetic alopecia, non-surgical, men, meta-analysis, systematic review

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15492 Developing a Decision-Making Tool for Prioritizing Green Building Initiatives

Authors: Tayyab Ahmad, Gerard Healey

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Sustainability in built environment sector is subject to many development constraints. Building projects are developed under different requirements of deliverables which makes each project unique. For an owner organization, i.e., a higher-education institution, involved in a significant building stock, it is important to prioritize some of the sustainability initiatives over the others in order to align the sustainable building development with organizational goals. The point-based green building rating tools i.e. Green Star, LEED, BREEAM are becoming increasingly popular and are well-acknowledged worldwide for verifying a sustainable development. It is imperative to synthesize a multi-criteria decision-making tool that can capitalize on the point-based methodology of rating systems while customizing the sustainable development of building projects according to the individual requirements and constraints of the client organization. A multi-criteria decision-making tool for the University of Melbourne is developed that builds on the action-learning and experience of implementing Green Buildings at the University of Melbourne. The tool evaluates the different sustainable building initiatives based on the framework of Green Star rating tool of Green Building Council of Australia. For each different sustainability initiative the decision-making tool makes an assessment based on at least five performance criteria including the ease with which a sustainability initiative can be achieved and the potential of a sustainability initiative to enhance project objectives, reduce life-cycle costs, enhance University’s reputation, and increase the confidence in quality construction. The use of a weighted aggregation mathematical model in the proposed tool can have a considerable role in the decision-making process of a Green Building project by indexing the Green Building initiatives in terms of organizational priorities. The index value of each initiative will be based on its alignment with some of the key performance criteria. The usefulness of the decision-making tool is validated by conducting structured interviews with some of the key stakeholders involved in the development of sustainable building projects at the University of Melbourne. The proposed tool is realized to help a client organization in deciding that within limited resources which sustainability initiatives and practices are more important to be pursued than others.

Keywords: higher education institution, multi-criteria decision-making tool, organizational values, prioritizing sustainability initiatives, weighted aggregation model

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15491 Grid Computing for Multi-Objective Optimization Problems

Authors: Aouaouche Elmaouhab, Hassina Beggar

Abstract:

Solving multi-objective discrete optimization applications has always been limited by the resources of one machine: By computing power or by memory, most often both. To speed up the calculations, the grid computing represents a primary solution for the treatment of these applications through the parallelization of these resolution methods. In this work, we are interested in the study of some methods for solving multiple objective integer linear programming problem based on Branch-and-Bound and the study of grid computing technology. This study allowed us to propose an implementation of the method of Abbas and Al on the grid by reducing the execution time. To enhance our contribution, the main results are presented.

Keywords: multi-objective optimization, integer linear programming, grid computing, parallel computing

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15490 An Improved Two-dimensional Ordered Statistical Constant False Alarm Detection

Authors: Weihao Wang, Zhulin Zong

Abstract:

Two-dimensional ordered statistical constant false alarm detection is a widely used method for detecting weak target signals in radar signal processing applications. The method is based on analyzing the statistical characteristics of the noise and clutter present in the radar signal and then using this information to set an appropriate detection threshold. In this approach, the reference cell of the unit to be detected is divided into several reference subunits. These subunits are used to estimate the noise level and adjust the detection threshold, with the aim of minimizing the false alarm rate. By using an ordered statistical approach, the method is able to effectively suppress the influence of clutter and noise, resulting in a low false alarm rate. The detection process involves a number of steps, including filtering the input radar signal to remove any noise or clutter, estimating the noise level based on the statistical characteristics of the reference subunits, and finally, setting the detection threshold based on the estimated noise level. One of the main advantages of two-dimensional ordered statistical constant false alarm detection is its ability to detect weak target signals in the presence of strong clutter and noise. This is achieved by carefully analyzing the statistical properties of the signal and using an ordered statistical approach to estimate the noise level and adjust the detection threshold. In conclusion, two-dimensional ordered statistical constant false alarm detection is a powerful technique for detecting weak target signals in radar signal processing applications. By dividing the reference cell into several subunits and using an ordered statistical approach to estimate the noise level and adjust the detection threshold, this method is able to effectively suppress the influence of clutter and noise and maintain a low false alarm rate.

Keywords: two-dimensional, ordered statistical, constant false alarm, detection, weak target signals

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15489 Nursing Experience of Helping the Mother of a Dying Baby by Applying Watson's Theory of Human Caring

Authors: Ya-Ping Chang

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Starting from the early stages of pregnancy, parents begin to form hopes and dreams about the future of their child. They will think about the appearance and personality of their child and may even develop many expectations. The patient in this study experienced a successful pregnancy following multiple attempts at artificial insemination. However, due to arrested embryonic development, and based on the physician’s evaluation, a caesarean section was performed at week 25. However, the baby suffered from infections and subsequently died from multiple organ failures. This study collected and analyzed objective and subjective data through observation, interviews, recording, and interactions with the patient. The following nursing issues of the patient were identified: anxiety, anticipatory grief, and adjustment disorder. The psychology of caring as proposed in Watson’s theory was applied to address these nursing issues. Comprehensive and continuous care was provided to the patient on the basis of mutual trust and individual nursing guidelines in order to alleviate the patient’s anxiety, help her to cope with grief, and prepare her for the eventual death of her child. The author helped the patient to say goodbye to her child and accept the child’s death calmly, such that she had no regrets about the experience. This nursing experience may serve as a reference to nurses managing similar cases in the future.

Keywords: dying baby, mother, grief, Watson’s theory

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15488 A Comparative Study of Active Release Technique and Myofascial Release Technique in Treatment of Patients with Upper Trapezius Spasm

Authors: Daxa Mishra, R. Harihara, Ankita

Abstract:

Trapezius muscle pain is the most common musculoskeletal disorder occurring in individuals who work with awkward positions, have repetitive movements and movements with precision demands. Treatment techniques like active release technique (ART) and myofascial release (MFR) can be used to relieve muscle spasm. The aim of the study is to compare the effect of ART and MFR on the upper trapezius muscle spasm. Methodology: A series of 60 patients of both sexes between the age group of 20 and 55 with upper trapezius spasm were divided into two groups by computerized randomization. Subjects in each group received treatment in the form of either ART or MFR for the period of seven days. cervical range of motion (ROM), neck disability index scale (NDI) and visual analog scale (VAS) tools were used to measure the outcome. Results: Paired Sample ‘t’ test was used to compare the Outcome differences within each group, while Independent ‘t’ test was used to compare the differences between the two groups for the same outcome measures. The improvement was found in both the groups at 7th day following intervention, but the group which received ART showed significant improvements as compared to group which received MFR. Conclusion: Although both techniques are effective in alleviation of symptoms and associated disability in upper trapezius muscle spasm, ART gave better results as compared to MRF.

Keywords: goniometer, myofascial release, active release, physiotherapy

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15487 Long-Term Effects of Psychosocial Interventions for Adolescents on Depression and Anxiety: A Systematic Review and Meta-Analysis

Authors: Denis Duagi, Ben Carter, Maria Farrelly, Stephen Lisk, June S. L. Brown

Abstract:

Background: Adolescence represents a distinctive phase of development, and variables linked to this developmental period could affect the efficiency of prevention and treatment for depression and anxiety, as well as the long-term prognosis. The objectives of this study were to investigate the long-term effectiveness of psychosocial interventions for adolescents on depression and anxiety symptoms and to assess the influence of different intervention parameters on the long-term effects. Methods: Searches were carried out on the 11ᵗʰ of August 2022 using five databases (Cochrane Library, Embase, Medline, PsychInfo, Web of Science), as well as trial registers. Randomized controlled trials of psychosocial interventions targeting specifically adolescents were included if they assessed outcomes at 1-year post-intervention or more. The Cochrane risk of bias-2 quality assessment tool was used. The primary outcome was depression, and studies were pooled using a standardised mean difference, with an associated 95% confidence interval, p-value, and I². The study protocol was pre-registered (CRD42022348668). Findings: A total of 57 reports (n= 46,678 participants) were included in the review. Psychosocial interventions led to small reductions in depressive symptoms, with a standardised mean difference (SMD) at 1-year of -0.08 (95%CI -0.20, -0.03, p=0.002, I²=72%), 18-months SMD=-0.12, 95% CI -0.22, -0.01, p=0.03, I²=63%) and 2-years SMD=-0.12 (95% CI -0.20, -0.03, p=0.01, I²=68%). Sub-group analyses indicated that targeted interventions produced stronger effects, particularly when delivered by trained mental health professionals (K=18, SMD=-0.24, 95% CI -0.38, -0.10, p=0.001, I²=60%). No effects were detected for anxiety at any assessment. Conclusion: Psychosocial interventions specifically targeting adolescents were shown to have small but positive effects on depression symptoms but not anxiety symptoms, which were sustained for up to 2 years. These findings highlight the potential population-level preventive effects if such psychosocial interventions become widely implemented in accessible settings such as schools.

Keywords: psychosocial, adolescent, interventions, depression, anxiety, meta-analysis, randomized controlled trial

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15486 Impact of Drainage Defect on the Railway Track Surface Deflections; A Numerical Investigation

Authors: Shadi Fathi, Moura Mehravar, Mujib Rahman

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The railwaytransportation network in the UK is over 100 years old and is known as one of the oldest mass transit systems in the world. This aged track network requires frequent closure for maintenance. One of the main reasons for closure is inadequate drainage due to the leakage in the buried drainage pipes. The leaking water can cause localised subgrade weakness, which subsequently can lead to major ground/substructure failure.Different condition assessment methods are available to assess the railway substructure. However, the existing condition assessment methods are not able to detect any local ground weakness/damageand provide details of the damage (e.g. size and location). To tackle this issue, a hybrid back-analysis technique based on artificial neural network (ANN) and genetic algorithm (GA) has been developed to predict the substructurelayers’ moduli and identify any soil weaknesses. At first, afinite element (FE) model of a railway track section under Falling Weight Deflection (FWD) testing was developed and validated against field trial. Then a drainage pipe and various scenarios of the local defect/ soil weakness around the buried pipe with various geometriesand physical properties were modelled. The impact of the soil local weaknesson the track surface deflection wasalso studied. The FE simulations results were used to generate a database for ANN training, and then a GA wasemployed as an optimisation tool to optimise and back-calculate layers’ moduli and soil weakness moduli (ANN’s input). The hybrid ANN-GA back-analysis technique is a computationally efficient method with no dependency on seed modulus values. The modelcan estimate substructures’ layer moduli and the presence of any localised foundation weakness.

Keywords: finite element (FE) model, drainage defect, falling weight deflectometer (FWD), hybrid ANN-GA

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15485 Small Scale Mobile Robot Auto-Parking Using Deep Learning, Image Processing, and Kinematics-Based Target Prediction

Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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15484 A Hybrid-Evolutionary Optimizer for Modeling the Process of Obtaining Bricks

Authors: Marius Gavrilescu, Sabina-Adriana Floria, Florin Leon, Silvia Curteanu, Costel Anton

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Natural sciences provide a wide range of experimental data whose related problems require study and modeling beyond the capabilities of conventional methodologies. Such problems have solution spaces whose complexity and high dimensionality require correspondingly complex regression methods for proper characterization. In this context, we propose an optimization method which consists in a hybrid dual optimizer setup: a global optimizer based on a modified variant of the popular Imperialist Competitive Algorithm (ICA), and a local optimizer based on a gradient descent approach. The ICA is modified such that intermediate solution populations are more quickly and efficiently pruned of low-fitness individuals by appropriately altering the assimilation, revolution and competition phases, which, combined with an initialization strategy based on low-discrepancy sampling, allows for a more effective exploration of the corresponding solution space. Subsequently, gradient-based optimization is used locally to seek the optimal solution in the neighborhoods of the solutions found through the modified ICA. We use this combined approach to find the optimal configuration and weights of a fully-connected neural network, resulting in regression models used to characterize the process of obtained bricks using silicon-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. Thus, the purpose of our approach is to determine by simulation the working conditions, including the manufacturing mix recipe with the addition of different materials, to minimize the emissions represented by CO and CH4. Our approach determines regression models which perform significantly better than those found using the traditional ICA for the aforementioned problem, resulting in better convergence and a substantially lower error.

Keywords: optimization, biologically inspired algorithm, regression models, bricks, emissions

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15483 Hair Regrowth Effect of Herbal Formula on Androgenic Alopecia Rat Model

Authors: Jian-You Wang, Feng Yi Hsu, Chieh-Hsi Wu

Abstract:

Androgenetic alopecia (AGA) is an androgen-dependent disorder caused by excess testosterone in blood capillaries or excess enzyme activity of 5α- reductase in hair follicles. Plants, alone or in combination, have been widely used for hair growth promotion since ancient times in Asia. In this study, the efficacy of a traditional Chinese herbal formula, Shen-Ying-Yang-Zhen-Dan (SYYZD) with different kinds of extract solvents, facilitating hair regrowth in testosterone-induced hair loss have been determined. The study was performed by treating with either 95 % ethanol aqueous extracts, 50% ethanol aqueous extracts or deionized water extracts orally in four-week-old male S.D. rats that experienced hair regrowth interruption induced by testosterone treatment. The 50% ethanol aqueous extracts group showed better hair regrowth promotion activities than either 95% ethanol aqueous extracts or deionized water extracts groups in 14 days treatment. In conclusion, our results suggest that 50% ethanol aqueous SYYZD extracts have hair growth promoting potential and may be beneficial as an alternative medicine for androgenetic alopecia treatment.

Keywords: Shen-Ying-Yang-Zhen-Dan, androgenic alopecia, hair loss, hair growth promotion, hair regrowth effect

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15482 Assessment of Predictive Confounders for the Prevalence of Breast Cancer among Iraqi Population: A Retrospective Study from Baghdad, Iraq

Authors: Nadia H. Mohammed, Anmar Al-Taie, Fadia H. Al-Sultany

Abstract:

Although breast cancer prevalence continues to increase, mortality has been decreasing as a result of early detection and improvement in adjuvant systemic therapy. Nevertheless, this disease required further efforts to understand and identify the associated potential risk factors that could play a role in the prevalence of this malignancy among Iraqi women. The objective of this study was to assess the perception of certain predictive risk factors on the prevalence of breast cancer types among a sample of Iraqi women diagnosed with breast cancer. This was a retrospective observational study carried out at National Cancer Research Center in College of Medicine, Baghdad University from November 2017 to January 2018. Data of 100 patients with breast cancer whose biopsies examined in the National Cancer Research Center were included in this study. Data were collected to structure a detailed assessment regarding the patients’ demographic, medical and cancer records. The majority of study participants (94%) suffered from ductal breast cancer with mean age 49.57 years. Among those women, 48.9% were obese with body mass index (BMI) 35 kg/m2. 68.1% of them had positive family history of breast cancer and 66% had low parity. 40.4% had stage II ductal breast cancer followed by 25.5% with stage III. It was found that 59.6% and 68.1% had positive oestrogen receptor sensitivity and positive human epidermal growth factor (HER2/neu) receptor sensitivity respectively. In regard to the impact of prediction of certain variables on the incidence of ductal breast cancer, positive family history of breast cancer (P < 0.0001), low parity (P< 0.0001), stage I and II breast cancer (P = 0.02) and positive HER2/neu status (P < 0.0001) were significant predictive factors among the study participants. The results from this study provide relevant evidence for a significant positive and potential association between certain risk factors and the prevalence of breast cancer among Iraqi women.

Keywords: Ductal Breast Cancer, Hormone Sensitivity, Iraq, Risk Factors

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15481 Ensuring Cyber Security Using Kippo Honeypots

Authors: S. Vivekananda Pandian

Abstract:

A major challenging task in this current scenario is protecting your computer and other electronic gadgets against Cyber-attacks. In this current era Cyber warfare becomes a major threat to the entire world which targets a particular organization or a country spreading the Malwares, Breaching the securities, causing major loss to the organization. Several sectors both public and private are computerized such as Energy sectors, Oil refinery sectors, Defense sectors and Aviation sectors are prone to attacks. Several attacks are unknown while accessing the internet. To study the characteristics and Intention of the Attacker Kippo Honeypots are used. Honeypots are the trap set by us which enables them to monitor the malicious activities and detailed study about attackers which leads to strengthening of the security.

Keywords: attackers, security, Kippo Honeypots, virtual machine

Procedia PDF Downloads 413
15480 Artificial Neural Network Model Based Setup Period Estimation for Polymer Cutting

Authors: Zsolt János Viharos, Krisztián Balázs Kis, Imre Paniti, Gábor Belső, Péter Németh, János Farkas

Abstract:

The paper presents the results and industrial applications in the production setup period estimation based on industrial data inherited from the field of polymer cutting. The literature of polymer cutting is very limited considering the number of publications. The first polymer cutting machine is known since the second half of the 20th century; however, the production of polymer parts with this kind of technology is still a challenging research topic. The products of the applying industrial partner must met high technical requirements, as they are used in medical, measurement instrumentation and painting industry branches. Typically, 20% of these parts are new work, which means every five years almost the entire product portfolio is replaced in their low series manufacturing environment. Consequently, it requires a flexible production system, where the estimation of the frequent setup periods' lengths is one of the key success factors. In the investigation, several (input) parameters have been studied and grouped to create an adequate training information set for an artificial neural network as a base for the estimation of the individual setup periods. In the first group, product information is collected such as the product name and number of items. The second group contains material data like material type and colour. In the third group, surface quality and tolerance information are collected including the finest surface and tightest (or narrowest) tolerance. The fourth group contains the setup data like machine type and work shift. One source of these parameters is the Manufacturing Execution System (MES) but some data were also collected from Computer Aided Design (CAD) drawings. The number of the applied tools is one of the key factors on which the industrial partners’ estimations were based previously. The artificial neural network model was trained on several thousands of real industrial data. The mean estimation accuracy of the setup periods' lengths was improved by 30%, and in the same time the deviation of the prognosis was also improved by 50%. Furthermore, an investigation on the mentioned parameter groups considering the manufacturing order was also researched. The paper also highlights the manufacturing introduction experiences and further improvements of the proposed methods, both on the shop floor and on the quotation preparation fields. Every week more than 100 real industrial setup events are given and the related data are collected.

Keywords: artificial neural network, low series manufacturing, polymer cutting, setup period estimation

Procedia PDF Downloads 233
15479 Construction Project Planning Using Fuzzy Critical Path Approach

Authors: Omar M. Aldenali

Abstract:

Planning is one of the most important phases of the management science and network planning, which represents the project activities relationship. Critical path is one of the project management techniques used to plan and control the execution of a project activities. The objective of this paper is to implement a fuzzy logic approach to arrange network planning on construction projects. This method is used to finding out critical path in the fuzzy construction project network. The trapezoidal fuzzy numbers are used to represent the activity construction project times. A numerical example that represents a house construction project is introduced. The critical path method is implemented on the fuzzy construction network activities, and the results showed that this method significantly affects the completion time of the construction projects.

Keywords: construction project, critical path, fuzzy network project, planning

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15478 The Influence of Emotional Intelligence Skills on Innovative Start-Ups Coaching: A Neuro-Management Approach

Authors: Alina Parincu, Giuseppe Empoli, Alexandru Capatina

Abstract:

The purpose of this paper is to identify the most influential predictors of emotional intelligence skills, in the case of 20 business innovation coaches, on the co-creation of knowledge through coaching services delivered to innovative start-ups from Europe, funded through Horizon 2020 – SME Instrument. We considered the emotional intelligence skills (self-awareness, self-regulation, motivation, empathy and social skills) as antecedent conditions of the outcome: the quality of coaching services, perceived by the entrepreneurs who received funding within SME instrument, using fuzzy-sets qualitative comparative analysis (fsQCA) approach. The findings reveal that emotional intelligence skills, trained with neuro-management techniques, were associated with increased goal-focused business coaching skills.

Keywords: neuro-management, innovative start-ups, business coaching, fsQCA

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15477 Multi-Agent TeleRobotic Security Control System: Requirements Definitions of Multi-Agent System Using The Behavioral Patterns Analysis (BPA) Approach

Authors: Assem El-Ansary

Abstract:

This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Multi-Agent TeleRobotic Security Control System (MTSCS). The event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are the Behavioral Pattern Analysis (BPA) modeling methodology, and the development of an interactive software tool (DECISION), which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, multi-agent, TeleRobotics control, security, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases

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15476 Theoretical Lens Driven Strategies for Emotional Wellbeing of Parents and Children in COVID-19 Era

Authors: Anamika Devi

Abstract:

Based on Vygotsky’s cultural, historical theory and Hedegaard’s concept of transition, this study aims to investigate to propose strategies to maintain digital wellbeing of children and parents during and post COVID pandemic. Due COVID 19 pandemic, children and families have been facing new challenges and sudden changes in their everyday life. While children are juggling to adjust themselves in new circumstance of onsite and online learning settings, parents are juggling with their work-life balance. A number of papers have identified that the COVID-19 pandemic has affected the lives of many families around the world in many ways, for example, the stress level of many parents increased, families faced financial difficulties, uncertainty impacted on long term effects on their emotional and social wellbeing. After searching and doing an intensive literature review from 2020 and 2021, this study has found some scholarly articles provided solution or strategies of reducing stress levels of parents and children in this unprecedented time. However, most of them are not underpinned by proper theoretical lens to ensure they validity and success. Therefore, this study has proposed strategies that are underpinned by theoretical lens to ensure their impact on children’s and parents' emotional wellbeing during and post COVID-19 era. The strategies will highlight on activities for positive coping strategies to the best use of family values and digital technologies.

Keywords: onsite and online learning, strategies, emotional wellbeing, tips, and strategies, COVID19

Procedia PDF Downloads 154
15475 A Study of Challenges Faced and Support Systems Available for Emirati Student Mothers Post-Childbirth

Authors: Martina Dickson, Lilly Tennant

Abstract:

The young Emirati female university students of today are the first generation of women in the UAE for whom higher education as become not only a possibility, but almost an expectation. Young women in the UAE today make up around 77% of students in higher education institutes in the country. However, the societal expectations placed upon these women in terms of early marriage, child-bearing and rearing are similar to those placed upon their mothers and grandmothers in a time where women were not expected to go to university. A large proportion of female university students in the UAE are mothers of young children, or become mothers whilst at the university. This creates a challenging situation for young student mothers, where two weeks’ maternity leave is typical across institutions. The context of this study is in one such institution in the UAE. We have employed a mixed method approach to gathering interview data from twenty mothers, and survey data from over one hundred mothers. The main findings indicate that mothers have strong desires for their institution to support them more, for example by the provision of nursery facilities and resting areas for new mothers, and giving them greater flexibility over course selections and schedules including the provision of online learning. However, the majority felt supported on a personal level by their tutors. The major challenges which they identified in returning to college after only two weeks’ leave included the inevitable health and lack of sleep issues when caring for a newborn, struggling to catch up with missed college work and handling their course load. We also explored the women's’ home support systems which were provided from a variety of extended family, spouses and paid domestic help.

Keywords: student mothers, challenges, supports, United Arab Emirates

Procedia PDF Downloads 206
15474 Interlayer-Mechanical Working: Effective Strategy to Mitigate Solidification Cracking in Wire-Arc Additive Manufacturing (WAAM) of Fe-based Shape Memory Alloy

Authors: Soumyajit Koley, Kuladeep Rajamudili, Supriyo Ganguly

Abstract:

In recent years, iron-based shape-memory alloys have been emerging as an inexpensive alternative to costly Ni-Ti alloy and thus considered suitable for many different applications in civil structures. Fe-17Mn-10Cr-5Si-4Ni-0.5V-0.5C alloy contains 37 wt.% of total solute elements. Such complex multi-component metallurgical system often leads to severe solute segregation and solidification cracking. Wire-arc additive manufacturing (WAAM) of Fe-17Mn-10Cr-5Si-4Ni-0.5V-0.5C alloy was attempted using a cold-wire fed plasma arc torch attached to a 6-axis robot. Self-standing walls were manufactured. However, multiple vertical cracks were observed after deposition of around 15 layers. Microstructural characterization revealed open surfaces of dendrites inside the crack, confirming these cracks as solidification cracks. Machine hammer peening (MHP) process was adopted on each layer to cold work the newly deposited alloy. Effect of MHP traverse speed were varied systematically to attain a window of operation where cracking was completely stopped. Microstructural and textural analysis were carried out further to correlate the peening process to microstructure.MHP helped in many ways. Firstly, a compressive residual stress was induced on each layer which countered the tensile residual stress evolved from solidification process; thus, reducing net tensile stress on the wall along its length. Secondly, significant local plastic deformation from MHP followed by the thermal cycle induced by deposition of next layer resulted into a recovered and recrystallized equiaxed microstructure instead of long columnar grains along the vertical direction. This microstructural change increased the total crack propagation length and thus, the overall toughness. Thirdly, the inter-layer peening significantly reduced the strong cubic {001} crystallographic texture formed along the build direction. Cubic {001} texture promotes easy separation of planes and easy crack propagation. Thus reduction of cubic texture alleviates the chance of cracking.

Keywords: Iron-based shape-memory alloy, wire-arc additive manufacturing, solidification cracking, inter-layer cold working, machine hammer peening

Procedia PDF Downloads 58