Search results for: military training

Authors: Jennifer Leach, Umashanger Thayasivam

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The use of technology has benefited society in more ways than one ever thought possible. Unfortunately, though, as society’s knowledge of technology has advanced, so has its knowledge of ways to use technology to manipulate people. This has led to a simultaneous advancement in the world of fraud. Machine learning techniques can offer a possible solution to help decrease this advancement. This research explores how the use of various machine learning techniques can aid in detecting fraudulent activity across two different types of fraudulent data, and the accuracy, precision, recall, and F1 were recorded for each method. Each machine learning model was also tested across five different training and testing splits in order to discover which testing split and technique would lead to the most optimal results.

Keywords: data science, fraud detection, machine learning, supervised learning

Procedia PDF Downloads 182

Authors: Lewis Mehl-Madrona, Barbara Mainguy

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We describe the type of counseling done by traditional cultural healers in North America. We follow an autoethnographic course development through the first author’s integration of mainstream training and Native-American heritage and study with traditional medicine people. We assemble traditional healing elders from North America and discuss with them their practices and their philosophies of healing. We draw parallels for their approaches in some European-based philosophies and religion, including the work of Heidegger, Levin, Fox, Kierkegaard, and others. An example of the treatment process with a depressed client is provided and similarities and differences with conventional psychotherapies are described.

Keywords: indigenous approaches to counseling, indigenous bodywork, indigenous healing, North American indigenous people

Procedia PDF Downloads 266

Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

Procedia PDF Downloads 164

Authors: Choi Sang Long

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It is vital for Human Resource (HR) managers to address and overcome employees’ turnover intention in their organization. Ability to keep good employees is critical for ensuring success of the organization in future. People are seeking many ways of live that is meaningful and less complicated and this new lifestyle actually has an impact on how an employee must be motivated and managed. Therefore, this paper discusses extensively on the impact of human resource practices that can alter the negative effect on the organization due to high employees’ turnover. These critical practices are employees’ career development, performance management, training and a fair compensation scheme.

Keywords: turnover intention, career development, performance management, compensation, human resource management, organization

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Authors: David Ofosu-Hamilton, John K. E. Edumadze

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Universities have come to recognize the role Information and Communication Technology (ICT) skills plays in the daily activities of tertiary students. The ability to use ICT – essentially, computers and their diverse applications – are important resources that influence an individual’s economic and social participation and human capital development. Our society now increasingly relies on the Internet, and the Cloud as a means to communicate and disseminate information. The educated individual should, therefore, be able to use ICT to create and share knowledge that will improve society. It is, therefore, important that universities require incoming students to demonstrate a level of computer proficiency or trained to do so at a minimal cost by deploying advanced educational technologies. The training and standardized assessment of all in-coming first-year students of the University of Cape Coast in Information Technology Skills (ITS) have become a necessity as students’ most often than not highly overestimate their digital skill and digital ignorance is costly to any economy. The one-semester course is targeted at fresh students and aimed at enhancing the productivity and software skills of students. In this respect, emphasis is placed on skills that will enable students to be proficient in using Microsoft Office and Google Apps for Education for their academic work and future professional work whiles using emerging digital multimedia technologies in a safe, ethical, responsible, and legal manner. The course is delivered in blended mode - online and self-paced (student centered) using Alison’s free cloud-based tutorial (Moodle) of Microsoft Office videos. Online support is provided via discussion forums on the University’s Moodle platform and tutor-directed and assisted at the ICT Centre and Google E-learning laboratory. All students are required to register for the ITS course during either the first or second semester of the first year and must participate and complete it within a semester. Assessment focuses on Alison online assessment on Microsoft Office, Alison online assessment on ALISON ABC IT, Peer assessment on e-portfolio created using Google Apps/Office 365 and an End of Semester’s online assessment at the ICT Centre whenever the student was ready in the cause of the semester. This paper, therefore, focuses on the digital culture approach of hybrid teaching, learning and paperless examinations and the possible adoption by other courses or programs at the University of Cape Coast.

Keywords: assessment, blended, cloud, paperless

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Authors: Mustafa Taskin, Ozgur Demir, M. Mert Serveren

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The precise study of the impact of underwater explosions on structures is of great importance in the design and engineering calculations of floating structures, especially those used for military purposes, as well as power generation facilities such as offshore platforms that can become a target in case of war. Considering that ship and submarine structures are mostly curved surfaces, it is extremely important and interesting to examine the destructive effects of underwater explosions on curvilinear surfaces. In this study, geometric nonlinear dynamic analysis of cylindrical composite sandwich shells subjected to instantaneous pressure load is performed. The instantaneous pressure load is defined as an underwater explosion and the effects of the liquid medium are taken into account. There are equations in the literature for pressure due to underwater explosions, but these equations have been obtained for flat plates. For this reason, the instantaneous pressure load equations are arranged to be suitable for curvilinear structures before proceeding with the analyses. Fluid-solid interaction is defined by using Taylor's Plate Theory. The lower and upper layers of the cylindrical composite sandwich shell are modeled as composite laminate and the middle layer consists of soft core. The geometric nonlinear dynamic equations of the shell are obtained by Hamilton's principle, taken into account the von Kàrmàn theory of large displacements. Then, time dependent geometric nonlinear equations of motion are solved with the help of generalized differential quadrature method (GDQM) and dynamic behavior of cylindrical composite sandwich shells exposed to underwater explosion is investigated. An algorithm that can work parametrically for the solution has been developed within the scope of the study.

Keywords: cylindrical composite sandwich shells, generalized differential quadrature method, geometric nonlinear dynamic analysis, underwater explosion

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Authors: Varsha Kheradiya, Ganga Prasad Pandey

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The use of wearable antennas is rising because wireless devices become small. The wearable antenna is part of clothes used in communication applications, including energy harvesting, medical application, navigation, and tracking. In current years, Antennas embroidered on clothes, conducting antennas based on fabric, polymer embedded antennas, and inkjet-printed antennas are all attractive ways. Also shows the analysis required for wearable antennas, such as wearable antennae interacting with the human body. The primary requirements for the antenna are small size, low profile minimizing radiation absorption by the human body, high efficiency, structural integrity to survive worst situations, and good gain. Therefore, research in energy harvesting, biomedicine, and military application design is increasingly favoring flexible wearable antennas. Textile materials that are effectively used for designing and developing wearable antennas for body area networks. The wireless body area network is primarily concerned with creating effective antenna systems. The antenna should reduce their size, be lightweight, and be adaptable when integrated into clothes. When antennas integrate into clothes, it provides a convenient alternative to those fabricated using rigid substrates. This paper presents a study of U slot loaded wearable textile antenna. U slot patch antenna design is illustrated for wideband from 1GHz to 6 GHz using textile material jeans as substrate and pure copper polyester taffeta fabric as conducting material. This antenna design exhibits dual band results for WLAN at 2.4 GHz and 3.6 GHz frequencies. Also, study U slot position horizontal and vertical shifting. Shifting the horizontal positive X-axis position of the U slot produces the third band at 5.8 GHz.

Keywords: microstrip patch antenna, textile material, U slot wearable antenna, wireless body area network

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Authors: Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

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Current state-of-the-art classification and detection algorithms rely on supervised training. In this work we study unsupervised feature learning in the context of temporally coherent video data. We focus on feature learning from unlabeled video data, using the assumption that adjacent video frames contain semantically similar information. This assumption is exploited to train a convolutional pooling auto-encoder regularized by slowness and sparsity. We establish a connection between slow feature learning to metric learning and show that the trained encoder can be used to define a more temporally and semantically coherent metric.

Keywords: machine learning, pattern clustering, pooling, classification

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Authors: Vladimira Hornackova, Jana Kottasova, Zuzana Vanova, Anna Jungrova

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Present study deals with drama education in preschool education. The research made in this field brings a qualitative comparative survey with the aim to find out the use of methods and techniques of drama education in preschool education at university or secondary school graduate preschool teachers. The research uses a content analysis and an unstandardized questionnaire for preschool teachers and obtained data are processed with the help of descriptive methods and correlations. The results allow a comparison of aspects applied through drama in preschool education. The research brings impulses for education improvement in kindergartens and inspiration for university study programs of drama education in the professional training of preschool teachers.

Keywords: drama education, preschool education, preschool teacher, research

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Authors: Ankur Chaudhuri, Sibani Sen Chakraborty

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In human, glutaminyl cyclase activity is highly abundant in neuronal and secretory tissues and is preferentially restricted to hypothalamus and pituitary. The N-terminal modification of β-amyloids (Aβs) peptides by the generation of a pyro-glutamyl (pGlu) modified Aβs (pE-Aβs) is an important process in the initiation of the formation of neurotoxic plaques in Alzheimer’s disease (AD). This process is catalyzed by glutaminyl cyclase (QC). The expression of QC is characteristically up-regulated in the early stage of AD, and the hallmark of the inhibition of QC is the prevention of the formation of pE-Aβs and plaques. A computer-aided drug design (CADD) process was employed to give an idea for the designing of potentially active compounds to understand the inhibitory potency against human glutaminyl cyclase (QC). This work elaborates the ligand-based and structure-based pharmacophore exploration of glutaminyl cyclase (QC) by using the known inhibitors. Three dimensional (3D) quantitative structure-activity relationship (QSAR) methods were applied to 154 compounds with known IC50 values. All the inhibitors were divided into two sets, training-set, and test-sets. Generally, training-set was used to build the quantitative pharmacophore model based on the principle of structural diversity, whereas the test-set was employed to evaluate the predictive ability of the pharmacophore hypotheses. A chemical feature-based pharmacophore model was generated from the known 92 training-set compounds by HypoGen module implemented in Discovery Studio 2017 R2 software package. The best hypothesis was selected (Hypo1) based upon the highest correlation coefficient (0.8906), lowest total cost (463.72), and the lowest root mean square deviation (2.24Å) values. The highest correlation coefficient value indicates greater predictive activity of the hypothesis, whereas the lower root mean square deviation signifies a small deviation of experimental activity from the predicted one. The best pharmacophore model (Hypo1) of the candidate inhibitors predicted comprised four features: two hydrogen bond acceptor, one hydrogen bond donor, and one hydrophobic feature. The Hypo1 was validated by several parameters such as test set activity prediction, cost analysis, Fischer's randomization test, leave-one-out method, and heat map of ligand profiler. The predicted features were then used for virtual screening of potential compounds from NCI, ASINEX, Maybridge and Chembridge databases. More than seven million compounds were used for this purpose. The hit compounds were filtered by drug-likeness and pharmacokinetics properties. The selective hits were docked to the high-resolution three-dimensional structure of the target protein glutaminyl cyclase (PDB ID: 2AFU/2AFW) to filter these hits further. To validate the molecular docking results, the most active compound from the dataset was selected as a reference molecule. From the density functional theory (DFT) study, ten molecules were selected based on their highest HOMO (highest occupied molecular orbitals) energy and the lowest bandgap values. Molecular dynamics simulations with explicit solvation systems of the final ten hit compounds revealed that a large number of non-covalent interactions were formed with the binding site of the human glutaminyl cyclase. It was suggested that the hit compounds reported in this study could help in future designing of potent inhibitors as leads against human glutaminyl cyclase.

Keywords: glutaminyl cyclase, hit lead, pharmacophore model, simulation

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Authors: Racheli Magnezi, Inbal Gazit, Michal Rassin, Joseph Barr, Orna Tal

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An effective process for transmitting patient critical information is essential for patient safety and for improving communication among healthcare staff. Previous studies have discussed handover tools such as SBAR (Situation, Background, Assessment, Recommendation) or SOFI (Short Observational Framework for Inspection). Yet, these formats lack flexibility, and require special training. In addition, nurses and physicians have different procedures for handing over information. The objectives of this study were to establish a universal, structured tool for handover, for both physicians and nurses, based on parameters that were defined as ‘important’ and ‘appropriate’ by the medical team, and to implement this tool in various hospital departments, with flexibility for each ward. A questionnaire, based on established procedures and on the literature, was developed to assess attitudes towards the most important information for effective handover between shifts (Cronbach's alpha 0.78). It was distributed to 150 senior physicians and nurses in 62 departments. Among senior medical staff, 12 physicians and 66 nurses responded to the questionnaire (52% response rate). Based on the responses, a handover form suitable for all hospital departments was designed and implemented. Important information for all staff included: Patient demographics (full name and age); Health information (diagnosis or patient complaint, changes in hemodynamic status, new medical treatment or equipment required); and Social Information (suspicion of violence, mental or behavioral changes, and guardianship). Additional information relevant to each unit included treatment provided, laboratory or imaging required, and change in scheduled surgery in surgical departments. ICU required information on background illnesses, Pediatrics required information on diet and food provided and Obstetrics required the number of days after cesarean section. Based on the model described, a flexible tool was developed that enables handover of both common and unique information. In addition, it includes general logistic information that must be transmitted to the next shift, such as planned disruptions in service or operations, staff training, etc. Development of a simple, clear, comprehensive, universal, yet flexible tool designed for all medical staff for transmitting critical information between shifts was challenging. Physicians and nurses found it useful and it was widely implemented. Ongoing research is needed to examine the efficiency of this tool, and whether the enthusiasm that accompanied its initial use is maintained.

Keywords: handover, nurses, hospital, critical information

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Authors: Najeebullah Soomro, Habib Noorbhai, Mariam Soomro, Ross Sanders

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The demands on cricketers are increasing with more matches being played in a shorter period of time with a greater intensity. A ten year report on injury incidence for Australian elite cricketers between the 2000- 2011 seasons revealed an injury incidence rate of 17.4%.1. In the 2009–10 season, 24 % of Australian fast bowlers missed matches through injury. 1 Injury rates are even higher in junior cricketers with an injury incidence of 25% or 2.9 injuries per 100 player hours reported. 2 Traditionally, injury surveillance has relied on the use of paper based forms or complex computer software. 3,4 This makes injury reporting laborious for the staff involved. The purpose of this presentation is to describe a smartphone based mobile application as a means of improving injury surveillance in cricket. Methods: The researchers developed CricPredict mobile App for the Android platforms, the world’s most widely used smartphone platform. It uses Qt SDK (Software Development Kit) as IDE (Integrated Development Environment). C++ was used as the programming language with the Qt framework, which provides us with cross-platform abilities that will allow this app to be ported to other operating systems (iOS, Mac, Windows) in the future. The wireframes (graphic user interface) were developed using Justinmind Prototyper Pro Edition Version (Ver. 6.1.0). CricPredict enables recording of injury and training status conveniently and immediately. When an injury is reported automated follow-up questions include site of injury, nature of injury, mechanism of injury, initial treatment, referral and action taken after injury. Direct communication with the player then enables assessment of severity and diagnosis. CricPredict also allows the coach to maintain and track each player’s attendance at matches and training session. Workload data can also be recorded by either the player or coach by recording the number of balls bowled or played in a day. This is helpful in formulating injury rates and time lost due to injuries. All the data are stored at a secured password protected data server. Outcomes and Significance: Use of CricPredit offers a simple, user friendly tool for the coaching or medical staff associated with teams to predict, record and report injuries. This system will assist teams to capture injury data with ease thus allowing better understanding of injuries associated with cricket and potentially optimize the performance of such cricketers.

Keywords: injury, cricket, surveillance, smartphones, mobile

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Authors: Jiahao Cui

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In the past centuries, due to climate change and intense whaling, the global whale population has dramatically declined. Among the various whale species, the fin whale experienced the most drastic drop in number due to its popularity in whaling. Under this background, identifying fin whale calls could be immensely beneficial to the preservation of the species. This paper uses feature extraction to process the input audio signal, then a network based on AlexNet and three networks based on the ResNet model was constructed to classify fin whale calls. A mixture of the DOSITS database and the Watkins database was used during training. The results demonstrate that a modified ResNet network has the best performance considering precision and network complexity.

Keywords: convolutional neural network, ResNet, AlexNet, fin whale preservation, feature extraction

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Authors: Amit Kumar Happy

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This paper is motivated by the importance of multi-sensor image fusion with a specific focus on infrared (IR) and visual image (VI) fusion for various applications, including military reconnaissance. Image fusion can be defined as the process of combining two or more source images into a single composite image with extended information content that improves visual perception or feature extraction. These images can be from different modalities like visible camera & IR thermal imager. While visible images are captured by reflected radiations in the visible spectrum, the thermal images are formed from thermal radiation (infrared) that may be reflected or self-emitted. A digital color camera captures the visible source image, and a thermal infrared camera acquires the thermal source image. In this paper, some image fusion algorithms based upon multi-scale transform (MST) and region-based selection rule with consistency verification have been proposed and presented. This research includes the implementation of the proposed image fusion algorithm in MATLAB along with a comparative analysis to decide the optimum number of levels for MST and the coefficient fusion rule. The results are presented, and several commonly used evaluation metrics are used to assess the suggested method's validity. Experiments show that the proposed approach is capable of producing good fusion results. While deploying our image fusion algorithm approaches, we observe several challenges from the popular image fusion methods. While high computational cost and complex processing steps of image fusion algorithms provide accurate fused results, they also make it hard to become deployed in systems and applications that require a real-time operation, high flexibility, and low computation ability. So, the methods presented in this paper offer good results with minimum time complexity.

Keywords: image fusion, IR thermal imager, multi-sensor, multi-scale transform

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Authors: P. Jost, L. Muckova, M. Matula, J. Pejchal, D. Jun, R. Stetina

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Sulfur mustard (bis(2-chlorethyl) sulfide) is highly toxic, chemical warfare agent that has been used in the past in several armed conflicts. Except for the skin, respiratory tract is one of the important routes of exposure. The elucidation and understanding of the mechanism of toxicity of SM have been effort intensive research. The multiple targets character of SM caused cellular damage resulted in activation of many different mechanisms which contribute to cellular response and participate in the final cytopathology effect. In our present work, we compared time-dependent changes in sulfur mustard exposed adult human lung fibroblasts NHLF and lung epithelial alveolar cell line A-549. Cell viability (MTT assay, Calcein-AM assay, and xCELLigence - real-time cell analysis), apoptosis (flow cytometry), mitochondrial membrane potential (Δψm, flow cytometry), reactive oxygen species induction (DC and cell cycle distribution (flow cytometry) were studied. We observed significantly decreased mitochondrial membrane potential and subsequent induction of apoptosis correlating with decreased cellular viability in the sulfur mustard exposed cells. In low concentrations, sulfur mustard-induced S-phase cell cycle arrest, on the other hand, high concentrations, cell cycle phase distribution of sulfur mustard exposed cells resembled cell cycle phase distribution of control group, which implies nonspecific cell cycle inhibition. Epithelial cells A-549 was found as more sensible to sulfur mustard toxicity. Acknowledgements: This work was supported by a long-term organization development plan Medical Aspects of Weapons of Mass Destruction of the Faculty of Military Health Sciences, University of Defence.

Keywords: apoptosis, cell cycle, cytotoxicity, sulfur mustard

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Authors: Abeer M. Orabi

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Midwives are being seen as a key factor in returning birth care to a normal physiologic process that is woman-centered. On the other hand, more needs to be done to increase access for every woman to professional midwifery care. Because of the nature of the midwifery specialty, the magnitude of the effect that can result from a lack of knowledge if midwives make a mistake in their care has the potential to affect a large number of the birthing population. So, the development, running, and management of midwifery educational programs should follow international standards and come after a thorough community needs assessment. At the same time, the number of accredited midwifery educational programs needs to be increased so that larger numbers of midwives will be educated and qualified, as well as access to skilled midwifery care will be increased. Indeed, the selection of promising midwives is important for the successful completion of an educational program, achievement of the program goals, and retention of graduates in the field. Further, the number of schooled midwives in midwifery education programs, their background, and their experience constitute some concerns in the higher education industry. Basically, preceptors and clinical sites are major contributors to the midwifery education process, as educational programs rely on them to provide clinical practice opportunities. In this regard, the selection of clinical training sites should be based on certain criteria to ensure their readiness for the intended training experiences. After that, communication, collaboration, and liaison between teaching faculty and field staff should be maintained. However, the shortage of clinical preceptors and the massive reduction in the number of practicing midwives, in addition to unmanageable workloads, act as significant barriers to midwifery education. Moreover, the medicalized approach inherent in the hospital setting makes it difficult to practice the midwifery model of care, such as watchful waiting, non-interference in normal processes, and judicious use of interventions. Furthermore, creating a motivating study environment is crucial for avoiding unnecessary withdrawal and retention in any educational program. It is well understood that research is an essential component of any profession for achieving its optimal goal and providing a foundation and evidence for its practices, and midwifery is no exception. Midwives have been playing an important role in generating their own research. However, the selection of novel, researchable, and sustainable topics considering community health needs is also a challenge. In conclusion, ongoing education and research are the lifeblood of the midwifery profession to offer a highly competent and qualified workforce. However, many challenges are being faced, and barriers are hindering their improvement.

Keywords: barriers, challenges, midwifery education, educational programs

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Authors: Kaddour Fellague Mohammed

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The world has seen in recent years, significant developments affected various aspects of life and influenced the different types of institutions, thus was born a new world is a world of globalization, which dominated the scientific revolution and the tremendous technological developments, and that contributed to the re-formation of human resources in contemporary organizations, and made patterns new regulatory and at the same time raised and strongly values and new ideas, the organizations have become more flexible, and faster response to consumer and environmental conditions, and exceeded the problem of time and place in the framework of communication and human interaction and use of advanced information technology and adoption mainly mechanism in running its operations , focused on performance and based strategic thinking and approach in order to achieve its strategic goals high degrees of superiority and excellence, this new reality created an increasing need for a new type of human resources, quality aims to renew and aspire to be a strategic player in managing the organization and drafting of various strategies, think globally and act locally, to accommodate local variables in the international markets, which began organizations tend to strongly as well as the ability to work under different cultures. Human resources management of the most important management functions to focus on the human element, which is considered the most valuable resource of the Department and the most influential in productivity at all, that the management and development of human resources Tattabra a cornerstone in the majority of organizations which aims to strengthen the organizational capacity, and enable companies to attract and rehabilitation of the necessary competencies and are able to keep up with current and future challenges, human resources can contribute to and strongly in achieving the objectives and profit organization, and even expand more than contribute to the creation of new jobs to alleviate unemployment and achieve full operation, administration and human resources mean short optimal use of the human element is available and expected, where he was the efficiency and capabilities, and experience of this human element, and his enthusiasm for the work stop the efficiency and success in reaching their goals, so interested administration scientists developed the principles and foundations that help to make the most of each individual benefit in the organization through human resources management, these foundations start of the planning and selection, training and incentives and evaluation, which is not separate from each other, but are integrated with each other as a system systemic order to reach the efficient functioning of the human resources management and has been the organization as a whole in the context of development sustainable.

Keywords: configuration, training, development, human resources, operating

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Authors: M. Towhidur Rahman, Nasim Zaman Piyas, M. Sadiqul Baree, Shahnewaz Ahmed

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The design of high-speed craft has recently become one of the most active areas of naval architecture. Speed increase makes these vehicles more efficient and useful for military, economic or leisure purpose. The planing hull is designed specifically to achieve relatively high speed on the surface of the water. Speed on the water surface is closely related to the size of the vessel and the installed power. The Savitsky method was first presented in 1964 for application to non-monohedric hulls and for application to stepped hulls. This method is well known as a reliable comparative to CFD analysis of hull resistance. A computer program based on Savitsky’s method has been developed using MATLAB. The power of high-speed vessels has been computed in this research. At first, the program reads some principal parameters such as displacement, LCG, Speed, Deadrise angle, inclination of thrust line with respect to keel line etc. and calculates the resistance of the hull using empirical planning equations of Savitsky. However, some functions used in the empirical equations are available only in the graphical form, which is not suitable for the automatic computation. We use digital plotting system to extract data from nomogram. As a result, value of wetted length-beam ratio and trim angle can be determined directly from the input of initial variables, which makes the power calculation automated without manually plotting of secondary variables such as p/b and other coefficients and the regression equations of those functions are derived by using data from different charts. Finally, the trim angle, mean wetted length-beam ratio, frictional coefficient, resistance, and power are computed and compared with the results of Savitsky and good agreement has been observed.

Keywords: nomogram, planing hull, principal parameters, regression

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Authors: Chukwuka Justus Iwegbu

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Background: A major concern facing the world is providing senior citizens, individuals with disabilities, and other vulnerable groups with high-quality care. This issue is more serious in Nigeria's North Eastern area, where the burden of disease and disability is heavy, and access to care is constrained. This study aims to fill this gap by exploring the roles, challenges and support needs of caregivers, care home management, funding and administration in challenged communities in North Eastern Nigeria. The study will also provide a comprehensive understanding of the current situation and identify opportunities for improving the quality of care and support for caregivers and care recipients in these communities. Methods: A mixed-methods design, including both quantitative and qualitative data collection methods, will be used, and it will be guided by the stress process model of caregiving. The qualitative stage approach will comprise a survey, In-depth interviews, observations, and focus group discussion and the quantitative analysis will be used in order to comprehend the variations between caregiver's roles and care home management. A review of relevant documents, such as care home policies and funding reports, would be used to gather quantitative data on the administrative and financial aspects of care. The data collected will be analyzed using both descriptive statistics and thematic analysis. A sample size of around 200-300 participants, including caregivers, care recipients, care home managers and administrators, policymakers and health care providers, would be recruited. Findings: The study revealed that caregivers in challenged communities in North Eastern Nigeria face significant challenges, including lack of training and support, limited access to funding and resources, and high levels of burnout. Care home management and administration were also found to be inadequate, with a lack of clear policies and procedures and limited oversight and accountability. Conclusion: There is a need for increased investment in training and support for caregivers, as well as a need for improved care home management and administration in challenged communities in North Eastern Nigeria. It also highlights the importance of involving community members in decision-making and planning processes related to care homes and services. The study would contribute to the existing body of knowledge by providing a detailed understanding of the challenges faced by caregivers, care home managers and administrators.

Keywords: caregivers, care home management, funding, administration, challenge communities, North Eastern Nigeria

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Authors: Kemal Polat

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In this study, it has been estimated whether there is skin by using RBG values obtained from the camera and k-nearest neighbor (k-NN) classifier. The dataset used in this study has an unbalanced distribution and a linearly non-separable structure. This problem can also be called a big data problem. The Skin dataset was taken from UCI machine learning repository. As the classifier, we have used the k-NN method to handle this big data problem. For k value of k-NN classifier, we have used as 1. To train and test the k-NN classifier, 50-50% training-testing partition has been used. As the performance metrics, TP rate, FP Rate, Precision, recall, f-measure and AUC values have been used to evaluate the performance of k-NN classifier. These obtained results are as follows: 0.999, 0.001, 0.999, 0.999, 0.999, and 1,00. As can be seen from the obtained results, this proposed method could be used to predict whether the image is skin or not.

Keywords: k-NN classifier, skin or non-skin classification, RGB values, classification

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Authors: Buddhiprabha D. D. Pathirana

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Despite a rapid increase in the number of school counselors in the recent past; procuring the service of school counselors is a luxury that many Sri Lankan schools cannot afford. In addition, school counseling in Sri Lanka also faces new challenges in implementation due to the fact that a generally agreed consensus on training, ethical standards, role identity, counseling model, and structures for school counselors has not been reached. Therefore, this paper has several objectives. First, it reviews a brief history of school counseling in Sri Lanka and describes its current status. Second, it describes current trends/ problems specific to Sri Lankan school counseling milieu which have limited the progress of school counseling as a practice. Third, it discusses societal and cultural issues that are important to consider when implementing school counseling as a practices in Sri Lanka and provides recommendations to improve it.

Keywords: school counseling, Sri Lanka, current situation, recommendations

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Authors: Jheanel E. Estrada, Larry A. Vea

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This study developed model to detect proper/improper sitting posture using the built in web camera which detects the upper body points’ location and distances (chin, manubrium and acromion process). It also established relationships of human body frames and proper sitting posture. The models were developed by training some well-known classifiers such as KNN, SVM, MLP, and Decision Tree using the data collected from 60 students of different body frames. Decision Tree classifier demonstrated the most promising model performance with an accuracy of 95.35% and a kappa of 0.907 for head and shoulder posture. Results also showed that there were relationships between body frame and posture through Body Mass Index.

Keywords: posture, spinal points, gyroscope, image processing, ergonomics

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Authors: Supriya H. S., Chandrakala B. M.

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Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.

Keywords: MLHN, network traffic prediction

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Authors: Jiwon Lee, Yeong-Ju Go, Jong-Soo Choi

Abstract:

Drones were first developed for military use and were used in World War 1. But recently drones have been used in a variety of fields. Several companies actively utilize drone technology to strengthen their services, and in agriculture, drones are used for crop monitoring and sowing. Other people use drones for hobby activities such as photography. However, as the range of use of drones expands rapidly, problems caused by drones such as improperly flying, privacy and terrorism are also increasing. As the need for monitoring and tracking of drones increases, researches are progressing accordingly. The drone detection system estimates the position of the drone using the physical phenomena that occur when the drones fly. The drone detection system measures being developed utilize many approaches, such as radar, infrared camera, and acoustic detection systems. Among the various drone detection system, the acoustic detection system is advantageous in that the microphone array system is small, inexpensive, and easy to operate than other systems. In this paper, the acoustic signal is acquired by using minimum microphone when drone is flying, and direction of drone is estimated. When estimating the Direction of Arrival(DOA), there is a method of calculating the DOA based on the Time Difference of Arrival(TDOA) and a method of calculating the DOA based on the beamforming. The TDOA technique requires less number of microphones than the beamforming technique, but is weak in noisy environments and can only estimate the DOA of a single source. The beamforming technique requires more microphones than the TDOA technique. However, it is strong against the noisy environment and it is possible to simultaneously estimate the DOA of several drones. When estimating the DOA using acoustic signals emitted from the drone, it is impossible to measure the position of the drone, and only the direction can be estimated. To overcome this problem, in this work we show how to estimate the position of drones by arranging multiple microphone arrays. The microphone array used in the experiments was four tetrahedral microphones. We simulated the performance of each DOA algorithm and demonstrated the simulation results through experiments.

Keywords: acoustic sensing, direction of arrival, drone detection, microphone array

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Authors: Maikudi Umar

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This paper conceived Vocational and Technical Education as those aspects of educational process, in addition to general education leading to acquisition of practical skills, attitudes as well as basic scientific knowledge as it relates to occupations in various sectors of the economic and social life. The paper therefore viewed Vocational and Technical education as those aspects of educational training designed to provide the recipient with the skills abilities and understanding needed for efficient performance in chosen occupational carrier for self reliance. The paper also examined some major inhibitions to the attainment of self reliance through VTE. The paper also recommended a change of attitudes by governments in Nigeria by providing adequate equipment so as to meet up with the challenges.

Keywords: vocational education, technical education, skills and self reliance, issues and challenges

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Authors: Faris Alghamdi

Abstract:

Identifying which conflict management styles organizational members prefer, and what variables influence these selections, is an essential component of organizational conflict management as well as human resource management, particularly in training and development strategies. This study aims to examine the relationship between work experience and preferred conflict management styles. Utilizing the Rahim Organizational Conflict Inventory- II Form C, data were collected from 109 full-time employees of various organizations in the Eastern province of Saudi Arabia. The Pearson’s correlation coefficient analysis showed a statistically significant relationship between the integrating conflict management style and the length of work experience. Nevertheless, this relationship was negative, not positive as hypothesized.

Keywords: conflict management style, organizational members, work experience

Procedia PDF Downloads 398

Authors: Gilberto Goracci, Fabio Curti

Abstract:

This work presents a robust, light, and inexpensive algorithm to perform autonomous orbit determination using onboard magnetometer data in real-time. Magnetometers are low-cost and reliable sensors typically available on a spacecraft for attitude determination purposes, thus representing an interesting choice to perform real-time orbit determination without the need to add additional sensors to the spacecraft itself. Magnetic field measurements can be exploited by Extended/Unscented Kalman Filters (EKF/UKF) for orbit determination purposes to make up for GPS outages, yielding errors of a few kilometers and tens of meters per second in the position and velocity of a spacecraft, respectively. While this level of accuracy shows that Kalman filtering represents a solid baseline for autonomous orbit determination, it is not enough to provide a reliable state estimation in the absence of GPS signals. This work combines the solidity and reliability of the EKF with the versatility of a Recurrent Neural Network (RNN) architecture to further increase the precision of the state estimation. Deep learning models, in fact, can grasp nonlinear relations between the inputs, in this case, the magnetometer data and the EKF state estimations, and the targets, namely the true position, and velocity of the spacecraft. The model has been pre-trained on Sun-Synchronous orbits (SSO) up to 2126 kilometers of altitude with different initial conditions and levels of noise to cover a wide range of possible real-case scenarios. The orbits have been propagated considering J2-level dynamics, and the geomagnetic field has been modeled using the International Geomagnetic Reference Field (IGRF) coefficients up to the 13th order. The training of the module can be completed offline using the expected orbit of the spacecraft to heavily reduce the onboard computational burden. Once the spacecraft is launched, the model can use the GPS signal, if available, to fine-tune the parameters on the actual orbit onboard in real-time and work autonomously during GPS outages. In this way, the provided module shows versatility, as it can be applied to any mission operating in SSO, but at the same time, the training is completed and eventually fine-tuned, on the specific orbit, increasing performances and reliability. The results provided by this study show an increase of one order of magnitude in the precision of state estimate with respect to the use of the EKF alone. Tests on simulated and real data will be shown.

Keywords: artificial intelligence, extended Kalman filter, orbit determination, magnetic field

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Authors: Rose A. Yemson, Ping Jiang, Oyedeji L. Inumoh

Abstract:

The deployment of wireless sensor network has rapidly increased, however with the increased capacity and diversity of sensors, and applications ranging from biological, environmental, military etc. generates tremendous volume of data’s where more attention is placed on the distributed sensing and little on how to manage, analyze, retrieve and understand the data generated. This makes it more quite difficult to process live sensor data, run concurrent control and update because sensor data are either heavyweight, complex, and slow. This work will focus on developing a web service platform for automatic detection of sensors, acquisition of sensor data, storage of sensor data into a database, processing of sensor data using reconfigurable software components. This work will also create a web service based sensor data management system to monitor physical movement of an individual wearing wireless network sensor technology (SunSPOT). The sensor will detect movement of that individual by sensing the acceleration in the direction of X, Y and Z axes accordingly and then send the sensed reading to a database that will be interfaced with an internet platform. The collected sensed data will determine the posture of the person such as standing, sitting and lying down. The system is designed using the Unified Modeling Language (UML) and implemented using Java, JavaScript, html and MySQL. This system allows real time monitoring an individual closely and obtain their physical activity details without been physically presence for in-situ measurement which enables you to work remotely instead of the time consuming check of an individual. These details can help in evaluating an individual’s physical activity and generate feedback on medication. It can also help in keeping track of any mandatory physical activities required to be done by the individuals. These evaluations and feedback can help in maintaining a better health status of the individual and providing improved health care.

Keywords: HTML, java, javascript, MySQL, sunspot, UML, web-based, wireless network sensor

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Authors: Aswathi Thrivikraman, S. Advaith

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The study is aimed at designing encoders for deciphering intricacies in time series data by redescribing the dynamics operating on a lower-dimensional manifold. A semi-supervised LSTM autoencoder is devised and investigated to see if the latent representation of the time series data can better forecast the data. End-to-end training of the LSTM autoencoder, together with another LSTM network that is connected to the latent space, forces the hidden states of the encoder to represent the most meaningful latent variables relevant for forecasting. Furthermore, the study compares the predictions with those of a traditional seq2seq model.

Keywords: LSTM, autoencoder, forecasting, seq2seq model

Procedia PDF Downloads 148

Authors: Riddhi Chopra

Abstract:

While China’s friendship with a number of countries has waxed and waned over the decades, Sino-Pak relationship is said to have withstood the vicissitudes of larger international politics as well as changes in regional and domestic currents. Pakistan, one of the first countries to recognize the People’s Republic of China, thus providing China with a corridor into the energy rich Muslim states which was reciprocated with a continual stream of no-strings-attached military hardware and defense-related assistance from Beijing. The joint enmity towards India also provided the initial thrust to a burgeoning Sino-Pak friendship. This paper intends to provide a profound analysis of the strategic relation between China-Pakistan and examine India as a determining factor. The Pakistan-China strategic relationship has been conventionally viewed by India as a zero sum game, wherein any gains accrued by Pakistan or China through their partnership is seen as a direct detriment to the evolution of India-Pakistan or India-China relation. The paper evaluates various factors which were crucial for the synthesis of such a strong relation and presents a comprehensive study of the various policies and programs that have been undertaken by the two countries to tie India to South Asia and reduce its sphere of influence. The geographic dynamics is said to breed a natural coalition, dominating the strategic ambitions of both Beijing and Islamabad hence directing their relationship. In addition to the obvious geopolitical factors, there are several dense collaborations between the two nations knitting a relatively close partnership. Moreover, an attempt has been made to assess the irritants in China-Pak relations and the initiatives taken by the two to further strengthen it. Current trends in diplomatic, economic and defense cooperation – along with the staunch affinity rooted in history and consistent geo-strategic interests – points to a strong and strengthening relationship, significant in directing India’s foreign and security policies. This paper seeks to analyze the changing power dynamics of the China-Pak nexus with external actors such as US and India with an ulterior motive of their own and predict the change in power dynamics between the four countries.

Keywords: China, Pakistan, India, strategy

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