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Journal articles on the topic 'Employment and training (DEET)'
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1
Foley, Dennis. "Perspectives on Effective Student Support for Indigenous Students in a Tertiary Institution." Australian Journal of Indigenous Education 24, no. 2 (1996): 53–55. http://dx.doi.org/10.1017/s1326011100002477.
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In 1994 I was employed as a consultant in the Office of HRM working on a DEET (Department of Employment Education and Training) funded project in the compilation of an Indigenous employment strategy which resulted in the development of the university ‘Recruitment and Career Development Strategy for Indigenous Australians’.
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Liethof, Mary-Ann. "Want a Job? Join a Job Club!" Australian Journal of Career Development 4, no. 2 (July 1995): 10–11. http://dx.doi.org/10.1177/103841629500400205.
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Job Clubs funded by the Department of Employment, Education and Training (DEET) have been assisting long-term pre-employed people develop the means to effectively compete for and obtain work since being introduced to Australia from Canada in 1986–87.
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Whatman, Sue. "Promoting Indigenous Participation at Tertiary Institutions: Past Attempts and Future Strategies." Aboriginal Child at School 23, no. 1 (March 1995): 36–43. http://dx.doi.org/10.1017/s0310582200005046.
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Since 1967, enormous progress has been made by Aboriginal and Torres Strait Islander people in Australia in gaining access to, and participating in, tertiary education. National statistics provided by the Department of Employment, Education and Training (DEET, 1992), show that Aboriginal and Torres Strait Islander students are enrolling in, and graduating from, a wider variety of courses in ever increasing numbers.
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Norman, Pam. "Getting Going with Genres a National Aboriginal & Torres Strait Islander Education Policy Curriculum Initiative." Aboriginal Child at School 21, no. 2 (May 1993): 18–33. http://dx.doi.org/10.1017/s0310582200005629.
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The Northern Territory Department of Education was given a unique opportunity to implement an Aboriginal Schools Curriculum Materials Project (ASCMP) with funding from the Department of Employment, Education and Training (DEET) and the implementation of the National Aboriginal and Torres Strait Islander Education Policy (NAEP). One package of resources that has resulted from this initiative is known as Getting Going with Genres. A feature of the development of these resources was the involvement of large numbers of Aboriginal people in writing workshops in Northern Territory Aboriginal communities.
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Harrigan, Neil, Marion Taubman, and Youth Bureau. "Seeing is Believing." Australian Journal of Career Development 2, no. 2 (June 1993): 38–41. http://dx.doi.org/10.1177/103841629300200211.
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Veritable libraries of career information appear on shelves each year. Well-intentioned influencers, particularly parents and teachers, make use of this material as do career information seekers themselves. Decisions are made on the content, yet the industry of Career Information still remains highly deregulated. Any person/organisation with any motive can produce quite influential career information. The Department of Employment Education and Training (DEET) is one of the largest agencies responsible for provision of career information. It is the major Australian provider of national and local occupational information data and products with an overall expenditure of approximately $15 million per annum (DEET, 1991). It was afforded an opportunity during the deliberations of an Australian Education Council Working Party on Career Education (McCowan, 1992) to take the first step in the development of standards for career information. This article explores these issues, as well as presenting a checklist of standards for career information providers.
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Inglis, Alistair, Murray Cropley, and Richard Trembath. "Ozjac: Australia's National Course Information Database." Australian Journal of Career Development 5, no. 1 (April 1996): 15–18. http://dx.doi.org/10.1177/103841629600500104.
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The results of an investigation commissioned by the Department of Employment, Education and Training (DEET) for the development of an implementation strategy for Australia's new national course information system — OZJAC — are reported. The rationale for the establishment of a national course information database is explained; the major user needs that were identified for such a database are given; the type of organisational structure that was judged likely to provide the most effective support for such a system is discussed; and the implementation strategy that was recommended for the establishment of the new database is described. Finally an update on the developments since the presentation of the report is provided.
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Garrido Medina, Luis. "Estudios y trabajo de los españoles en la crisis de empleo." Studies of Applied Economics 30, no. 1 (April 11, 2020): 29. http://dx.doi.org/10.25115/eea.v30i1.3379.
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This article analyses how male employment have behaved so closely in the three last economic and employment crises, although there has been a very relevant increase in the average education level by birth cohort. This is a contradiction respect to the expectation of higher levels of employment and job quality with higher educational levels. The reasoning leads to deep concerns about the role of training and education solving jobless problems of workers, especially for those low-skilled.
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Helminiak, David, Hang Hu, Julia Laskin, and Dong Hye Ye. "Deep Learning Approach for Dynamic Sparse Sampling for High-Throughput Mass Spectrometry Imaging." Electronic Imaging 2021, no. 15 (January 18, 2021): 290–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.15.coimg-290.
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A Supervised Learning Approach for Dynamic Sampling (SLADS) addresses traditional issues with the incorporation o stochastic processes into a compressed sensing method. Statistical features, extracted from a sample reconstruction, estimate entropy reduction with regression models, in order to dynamically determine optimal sampling locations. This work introduces an enhanced SLADS method, in the form of a Deep Learning Approach for Dynamic Sampling (DLADS), showing reductions in sample acquisition times for high-fidelity reconstructions between ˜ 70–80% over traditional rectilinear scanning. These improvements are demonstrated for dimensionally asymmetric, high-resolution molecular images of mouse uterine and kidney tissues, as obtained using Nanospray Desorption Electro- Spray Ionization (nano-DESI) Mass Spectrometry Imaging (MSI). The methodology for training set creation is adjusted to mitigate stretching artifacts generated when using prior SLADS approaches. Transitioning to DLADS removes the need for feature extraction, further advanced with the employment of convolutional layers to leverage inter-pixel spatial relationships. Additionally, DLADS demonstrates effective generalization, despite dissimilar training and testing data. Overall, DLADS is shown to maximize potential experimental throughput for nano-DESI MSI.
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Fleming, Peter. "The Human Capital Hoax: Work, Debt and Insecurity in the Era of Uberization." Organization Studies 38, no. 5 (January 24, 2017): 691–709. http://dx.doi.org/10.1177/0170840616686129.
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Human capital theory – developed by neoclassical economists like Gary Becker and Theodore Schultz – is widely considered a useful way to explain how employees might enhance their value in organizations, leading to improved skill, autonomy and socio-economic wellbeing. This essay argues the opposite. Human capital theory implies that employees should bear the costs (and benefits) of their investment. Highly individualized training and work practices are an inevitable corollary. Self-employment, portfolio careers, the ‘gig economy’ and on-demand business models (including Uber and Deliveroo) faithfully reflect the assumptions that inform human capital theory. I term this the radical responsibilization of the workforce and link it to growing economic insecurity, low productivity, diminished autonomy and worrying levels of personal debt. The essay concludes by proposing some possible solutions.
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Cantika, Sri Budi. "OPTIMALISASI PERAN WAKAF DALAM PEMBERDAYAAN USAHA MIKRO, KECIL DAN MENENGAH (UMKM)." Journal of Innovation in Business and Economics 6, no. 1 (March 2, 2015): 1. http://dx.doi.org/10.22219/jibe.vol6.no1.1-16.
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The potential of Zakat, Infaq, Shodaqoh (ZIS), and Waqaf (endowments) to help society economic improvement are very important, yet the role of Islamic Finance Institution, as the executing agency that administer these four pious deed, were still not optimal yet. This article reveals the important role of Endowments in assisting the empowerment of Micro, Small, and Medium Enterprises (MSMEs) which is one of the strengths in poverty alleviation, employment creation and increase the strength of family income. Waqaf (endowments) Management Institute, an organization that empowers MSMEs through microfinance and business assistance, offers some strategic steps that must be carried out in managing successful business namely providing investment capital and working capital, presenting training and skills improvement, business consulting, improving product quality, market, business networking, and technology.
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Feng, Wei, Yuqin Wu, and Yexian Fan. "A new method for the prediction of network security situations based on recurrent neural network with gated recurrent unit." International Journal of Intelligent Computing and Cybernetics 13, no. 1 (August 1, 2018): 25–39. http://dx.doi.org/10.1108/ijicc-06-2017-0066.
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Purpose The purpose of this paper is to solve the shortage of the existing methods for the prediction of network security situations (NSS). Because the conventional methods for the prediction of NSS, such as support vector machine, particle swarm optimization, etc., lack accuracy, robustness and efficiency, in this study, the authors propose a new method for the prediction of NSS based on recurrent neural network (RNN) with gated recurrent unit. Design/methodology/approach This method extracts internal and external information features from the original time-series network data for the first time. Then, the extracted features are applied to the deep RNN model for training and validation. After iteration and optimization, the accuracy of predictions of NSS will be obtained by the well-trained model, and the model is robust for the unstable network data. Findings Experiments on bench marked data set show that the proposed method obtains more accurate and robust prediction results than conventional models. Although the deep RNN models need more time consumption for training, they guarantee the accuracy and robustness of prediction in return for validation. Originality/value In the prediction of NSS time-series data, the proposed internal and external information features are well described the original data, and the employment of deep RNN model will outperform the state-of-the-arts models.
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Hussain, Mumtaz, Sofia Sofia Anwar, and Shaoan Huang. "Socioeconomic and Demographic Factors Affecting Labor Force Participation in Pakistan." Journal of Sustainable Development 9, no. 4 (July 30, 2016): 70. http://dx.doi.org/10.5539/jsd.v9n4p70.
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Labor Force Participation is the indication of relative supply of labor in the labor market and it is also very useful for the formulation of employment and human resource development. The main purpose of present study is to explore the demographic factors that directly or indirectly influence the labor force participation. The study is based on Micro-level data on different socioeconomic and demographic factors that have a deep effect on the labor force participation in Pakistan. The collected set of information of about 1,43,587 frequencies of 36,400 households was used in this study from the Labor Force Survey of Pakistan 2008-09. The research concluded that the level of education, training, age, location, residential period and being male has positive and significant impact on labor force participation.
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Ferber, Jenny. "AIM for one Workforce: Aboriginal Employment Strategies Branch, DEET." Australian Journal of Career Development 3, no. 1 (March 1994): 16–17. http://dx.doi.org/10.1177/103841629400300107.
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AL-Huseiny, Muayed S., and Ahmed Sattar Sajit. "Transfer learning with GoogLeNet for detection of lung cancer." Indonesian Journal of Electrical Engineering and Computer Science 22, no. 2 (May 1, 2021): 1078. http://dx.doi.org/10.11591/ijeecs.v22.i2.pp1078-1086.
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<p class="p1">The use of computer algorithms has gained momentum in filling/assisting roles of specialists especially in early diagnosis scenarios. This paper proposes the employment of deep neural networks (DNN) to detect images with malignant nodules of lung computed tomography (CT). The method includes subjecting input images to a simple and fast pre-processing which isolates regions of interest (ROI), that’s the lungs dominated area, ridding the images of other surrounding tissues and artefacts. Centered and size normalized images are then fed to a deep neural network for training and validation. In this work transfer learning is used to readjust GoogLeNet DNN to learn this medical data. This includes allowing final layers of the DNN to evolve while restricting deep layers. In this setting, a rough, unprocessed dataset, the IQ-OTH/NCCD lung cancer dataset was used to train/validate the proposed algorithm. Experimental results show that this algorithm scores 94.38% accuracy, which outperforms benchmark method previously used with this dataset.</p>
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Yu, Ta-Chuan, Wen-Chien Chou, Chao-Yuan Yeh, Cheng-Kun Yang, Sheng-Chuan Huang, Feng Ming Tien, Chi-Yuan Yao, et al. "Automatic Bone Marrow Cell Identification and Classification By Deep Neural Network." Blood 134, Supplement_1 (November 13, 2019): 2084. http://dx.doi.org/10.1182/blood-2019-125322.
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Purpose Differential counting of blood cells is the basis of diagnostic hematology. In many circumstances, identification of cells in bone marrow smears is the golden standard for diagnosis. Presently, methods for automatic differential counting of peripheral blood are readily available commercially. However, morphological assessment and differential counting of bone marrow smears are still performed manually. This procedure is tedious, time-consuming and laden with high inter-operator variation. In recent years, deep neural networks have proven useful in many medical image recognition tasks, such as diagnosis of diabetic retinopathy, and detection of cancer metastasis in lymph nodes. However, there has been no published work on using deep neural networks for complete differential counting of entire bone marrow smear. In this work, we present the results of using deep convolutional neural network for automatic differential counting of bone marrow nucleated cells. Materials & Methods The bone marrow smears from patients with either benign or malignant disorders in National Taiwan University Hospital were recruited in this study. The bone marrow smears are stained with Liu's stain, a modified Romanowsky stain. Digital images of the bone marrow smears were taken using 1000x oil immersion lens and 20MP color CCD camera on a single microscope with standard illumination and white-balance settings. The contour of each nucleated cell was artificially defined. These cells were then divided into a training/validation set and a test set. Each cell was then classified into 1 of the 11 categories (blast, promyelocyte, neutrophilic myelocyte, neutrophilic metamyelocyte, neutrophils, eosinophils and precursors, basophil, monocyte and precursors, lymphocyte, erythroid lineage cells, and invalid cell). In training/validation set, the classification of each cell was annotated once by experienced medical technician or hematologist. The annotated dataset was used to train a Path-Aggregation Network for instance segmentation task. In test set, cell classification was annotated by three medical technicians or hematologists; only over 2/3 consensus was regarded as valid. After the neural network model was fully trained, the ability of the model to classify and detect bone marrow nucleated cells was evaluated in terms of precision, recall and accuracy. During the model training, we used group normalization and stochastic gradient descent optimizer for training. Random noise, Gaussian blur, rotation, contrast and color shift were also used as means for data augmentation. Results The digital images of 150 bone marrow aspirate smears were taken for this study. They included 61 for acute leukemia, 39 for lymphoma, 2 for myelodysplastic syndrome (MDS), 2 for myeloproliferative neoplasm (MPN), 10 for MDS/MPN, 12 for multiple myeloma, 4 for hemolytic anemia, 9 for aplastic anemia, 8 for infectious etiology and 3 for solid cancers. The final data contained 5927 images and 187730 nucleated bone marrow cells, which were divided into 2 sets: 5630 images containing 170966 cells as the training/validation set, and 297 images containing 16764 cells as the test set. Among the 16764 cells annotated in test set, 15676 cells (93.6 %) reached over 2/3 consensus. The trained neural network achieved 0.832 recall and 0.736 precision for cell detection task, 0.79 mean intersection over union (IOU) for cell segmentation task, mean average precision of 0.659 and accuracy of 0.801 for cell classification. For individual cell categories, the model performs the best with "erythroid-lineage-cells" (0.971 recall, 0.935 precision) and the worst with "monocyte-and-precursors" (0.825 recall, 0.337 precision). Conclusions We have created the largest and the most comprehensive annotated bone marrow smear image dataset for deep neural network training. Compared with previous works, our approach is more practical for clinical application because it is able to take in an entire field of smear and generate differential counts without any other preprocessing steps. Current results are highly encouraging. With continued expansion of dataset, our model would be more precise and clinically useful. Figure Disclosures Yeh: aether AI: Other: CEO and co-founder. Yang:aether AI: Employment. Tien:Novartis: Honoraria; Daiichi Sankyo: Honoraria; Celgene: Research Funding; Roche: Honoraria; Johnson &Johnson: Honoraria; Alexion: Honoraria; BMS: Honoraria; Roche: Research Funding; Celgene: Honoraria; Pfizer: Honoraria; Abbvie: Honoraria. Hsu:aether AI: Employment.
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Malyugin, Aleksey, Inga Tretyakova, and Natalia Dorozhkina. "Key Aspects of Preparing College Graduates for a Competitive Job Market." Standards and Monitoring in Education 7, no. 6 (February 3, 2020): 18–21. http://dx.doi.org/10.12737/1998-1740-2019-18-21.
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Today the threat of unemployment is one of the most pressing socio-economic problems for young professionals. The article examines the current state of the educational curriculum as well as infl uential factors, which determine the level of training competitive specialists must receive in order to succeed. Methods are proposed for solving the problem of employment and increasing the competitiveness of graduates in the job market. One of the main priorities for universities should be a creation of favorable conditions for students to acquire a number of specifi c skills, i.e. personal leadership, development of confi dent behavior skills, business communication, stress management, knowledge of general legal, economic and fundamental aspects. These skills will help in future activities to perform their basic daily duties. For this purpose, the methodology of implementing extracurricular activities is defined and the ways to integrate them into a higher educational program are proposed.
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Demertzis, Konstantinos, Lazaros Iliadis, and Elias Pimenidis. "Geo-AI to aid disaster response by memory-augmented deep reservoir computing." Integrated Computer-Aided Engineering 28, no. 4 (August 27, 2021): 383–98. http://dx.doi.org/10.3233/ica-210657.
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It is a fact that natural disasters often cause severe damage both to ecosystems and humans. Moreover, man-made disasters can have enormous moral and economic consequences for people. A typical example is the large deadly and catastrophic explosion in Beirut on 4 August 2020, which destroyed a very large area of the city. This research paper introduces a Geo-AI disaster response computer vision system, capable to map an area using material from Synthetic Aperture Radar (SAR). SAR is a unique form of radar that can penetrate the clouds and collect data day and night under any weather conditions. Specifically, the Memory-Augmented Deep Convolutional Echo State Network (MA/DCESN) is introduced for the first time in the literature, as an advanced Machine Vision (MAV) architecture. It uses a meta-learning technique, which is based on a memory-augmented approach. The target is the employment of Deep Reservoir Computing (DRC) for domain adaptation. The developed Deep Convolutional Echo State Network (DCESN) combines a classic Convolutional Neural Network (CNN), with a Deep Echo State Network (DESN), and analog neurons with sparse random connections. Its training is performed following the Recursive Least Square (RLS) method. In addition, the integration of external memory allows the storage of useful data from past processes, while facilitating the rapid integration of new information, without the need for retraining. The proposed DCESN implements a set of original modifications regarding training setting, memory retrieval mechanisms, addressing techniques, and ways of assigning attention weights to memory vectors. As it is experimentally shown, the whole approach produces remarkable stability, high generalization efficiency and significant classification accuracy, significantly extending the state-of-the-art Machine Vision methods.
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RADIUK, P. "AN APPROACH TO ACCELERATE THE TRAINING OF CONVOLUTIONAL NEURAL NETWORKS BY TUNING THE HYPERPARAMETERS OF LEARNING." Computer Systems and Information Technologies 2, no. 2 (November 3, 2020): 32–37. http://dx.doi.org/10.31891/csit-2020-2-5.
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Over the last decade, a set of machine learning algorithms called deep learning has led to significant improvements in computer vision, natural language recognition and processing. This has led to the widespread use of a variety of commercial, learning-based products in various fields of human activity. Despite this success, the use of deep neural networks remains a black box. Today, the process of setting hyperparameters and designing a network architecture requires experience and a lot of trial and error and is based more on chance than on a scientific approach. At the same time, the task of simplifying deep learning is extremely urgent. To date, no simple ways have been invented to establish the optimal values of learning hyperparameters, namely learning speed, sample size, data set, learning pulse, and weight loss. Grid search and random search of hyperparameter space are extremely resource intensive. The choice of hyperparameters is critical for the training time and the final result. In addition, experts often choose one of the standard architectures (for example, ResNets and ready-made sets of hyperparameters. However, such kits are usually suboptimal for specific practical tasks. The presented work offers an approach to finding the optimal set of hyperparameters of learning ZNM. An integrated approach to all hyperparameters is valuable because there is an interdependence between them. The aim of the work is to develop an approach for setting a set of hyperparameters, which will reduce the time spent during the design of ZNM and ensure the efficiency of its work. In recent decades, the introduction of deep learning methods, in particular convolutional neural networks (CNNs), has led to impressive success in image and video processing. However, the training of CNN has been commonly mostly based on the employment of quasi-optimal hyperparameters. Such an approach usually requires huge computational and time costs to train the network and does not guarantee a satisfactory result. However, hyperparameters play a crucial role in the effectiveness of CNN, as diverse hyperparameters lead to models with significantly different characteristics. Poorly selected hyperparameters generally lead to low model performance. The issue of choosing optimal hyperparameters for CNN has not been resolved yet. The presented work proposes several practical approaches to setting hyperparameters, which allows reducing training time and increasing the accuracy of the model. The article considers the function of training validation loss during underfitting and overfitting. There are guidelines in the end to reach the optimization point. The paper also considers the regulation of learning rate and momentum to accelerate network training. All experiments are based on the widespread CIFAR-10 and CIFAR-100 datasets.
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Kimura, Konobu, Yoko Tabe, Tomohiko Ai, Akihiko Matsuzaki, Kumiko Nishibe, Miki Ebihara, Kimiko Kaniyu, Ikki Takehara, Kinya Uchihashi, and Akimichi Ohsaka. "A Novel Automated Image Analysis System Using Deep Convolutional Neural Networks to Diagnose MDS." Blood 134, Supplement_1 (November 13, 2019): 4670. http://dx.doi.org/10.1182/blood-2019-129524.
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Detection of dysmorphic cells in peripheral blood (PB) smears is essential for diagnosis of hematological malignancies. Myelodysplastic syndromes (MDS) are heterogeneous hematopoietic stem cell disorders that can lead to acute leukemia. Although examinations of bone marrow aspiration and biopsy as well as chromosomal and genetic tests are essential to diagnose these disorders, conventional tests such as complete blood count (CBC) and peripheral blood (PB) smear examinations remain to be initial diagnostic work ups. Detection of dysplastic cells in PB smears and evaluation of CBCs are particularly useful for rapid screening. Thanks to the recent advancement of computational and laboratory technologies, routine manual microscopic examinations have been replaced by automated hematology analyzers in many hematology laboratories. However, detection of dysmorphic cells is still challenging. Therefore, more sophisticated image recognition systems need to be developed. In this study, we developed a novel MDS diagnostic system using PB smears. The system consists of a convolutional neural network (CNN)-based image recognition deep learning system (DLS) and an EGB-based decision-making algorithm (XGBoost). All PB smears were prepared at Juntendo University Hospital. The slides were stained with May Grunwald-Giemsa using a fully automated slide-maker. A total of 703,970 digitalized cell images were collected. First, we trained the CNN-based image-recognition system using 695,030 blood cell images taken from 3,261 PB smears of which 1,165 were obtained from patients with hematological disorders. The hematological disorders included MDS (n=94 cases), myeloproliferative neoplasms (n=127), acute myeloid leukemia (n= 38), acute lymphoblastic leukemia (ALL, n=27), malignant lymphoma (n=324), multiple myeloma (n=82) and AA (n=42). Of all images, these 695,030 images were used to train the CNN-based image-recognition system (Fig 1), and rest of the images (n=8,940) were used for validation. The datasets were classified into 17 cell types and 97 abnormal morphological features by two board-certified laboratory technologists and one senior hematopathologist using the morphological criteria of the Clinical and Laboratory Standards Institute (CLSI) H20-A2 guideline and the 2017 WHO classification of myeloid neoplasms and acute leukemia. After accumulating the image patterns using the training datasets, the performance of the DLS was evaluated using the validation datasets that were prepared for testing the DLS. The internal features learnt by the DLS using t-distributed Stochastic Neighbor Embedding (t-SNE)(Fig 2). In this context, our CNN-based image-recognition system exhibited a sensitivity of >93.5% and a specificity of >96.0% when classifying cells in subsets of the validation datasets. We then created an automated MDS diagnostic system by combining the CNN-based image-recognition system with a form of XGBoost. To establish diagnostic algorithm, the training datasets obtained from 75 MDS and 36 Aplastic Anemia (AA) cases were used for learning of the cell image pattern for each disease. The diagnosis of all datasets was validated by independent hematopathologists using clinical information, laboratory, flow cytometric, and genetic data, and bone marrow aspiration and biopsy findings. The accuracy of the system was tested using validation datasets (26 MDS and 11 AA cases). The system differentiated MDS from AA with the sensitivity and specificity of 96.2% and 100%, respectively (AUC 0.990). In conclusion, this is the first CNN-based automated initial diagnostic system for MDS using PB smears, which is applicable to develop new automated image diagnostic systems for various hematological disorders. Currently, we are collecting more data to improve the accuracy. Disclosures Kimura: Sysmex Corporation: Employment. Takehara:Sysmex Corporation: Employment. Uchihashi:Sysmex Corporation: Employment.
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Khalifa, Rihab. "Enhancing female graduate employment through a women-only professional services firm in an economically remote city." Journal of Economic and Administrative Sciences 34, no. 1 (May 8, 2018): 36–47. http://dx.doi.org/10.1108/jeas-06-2017-0051.
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Purpose The purpose of this paper is to report on a study that investigated the feasibility of a women-only professional accounting firm in the city of Al Ain in the United Arab Emirates (UAE) that could help reduce female graduate unemployment in the city. Practically, the study sought to find out if, and under what conditions, a women-only professional accounting firm in Al Ain might be useful in providing employment for women in professional accountancy and facilitating the entry of female graduates into the job market by providing them with professional training. Theoretically, the study sought to add to the literature on positive discrimination to help women’s job prospects. Design/methodology/approach The study followed a qualitative research approach. It sought to show some specific connections between various professional, cultural, and economic factors by crystallising them through a hypothetical, innovative solution to the problem of local female unemployment, namely, a women-only professional accounting firm in a location of limited employment opportunities. It did so by investigating the views of male and female accounting graduates and other stakeholders. Findings The main finding is that the model women-only professional accounting firm could be used to overcome family objections to female graduate employment by removing the requirement that women work a long distance away from their families. The study also showed the deep cultural entrenchment of gendered stereotypes of female professionals. Research limitations/implications The study could have had a larger sample size with the survey, but it is important to note that this was not the focus of the study. However, the strength of the paper is in the qualitative aspect of canvassing views from various stakeholders. Practical implications The study brought to light key opportunities and challenges for policy makers who are seeking to address female graduate unemployment in economically remote locations. Originality/value The paper adds to the literature on positive discrimination for female job seekers in an adverse cultural and economic context.
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Nagata, Yasunobu, Vera Grossmann, Yusuke Okuno, Ulrike Bacher, Genta Nagae, Susanne Schnittger, Yusuke Shiozawa, et al. "Landscape Of Genetic Lesions In 944 Patients With Myelodysplastic Syndromes." Blood 122, no. 21 (November 15, 2013): 521. http://dx.doi.org/10.1182/blood.v122.21.521.521.
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Abstract Background Myelodysplastic syndromes (MDS) are a heterogeneous group of myeloid neoplasms characterized by varying degrees of cytopenias and a predisposition to acute myeloid leukemia (AML). With conspicuous clinical and biological heterogeneity in MDS, an optimized choice of treatment based on accurate diagnosis and risk stratification in individual patients is central to the current therapeutic strategy. Diagnosis and prognostication in patients with myelodysplastic syndromes (MDS) may be improved by high-throughput mutation/copy number profiling. Methods A total of 944 patients with various MDS subtypes were screened for gene mutations and deletions in 104 known/putative genes relevant to MDS using targeted deep-sequencing and/or array-based genomic hybridization. Impact of genetic lesions on overall survival (OS) was investigated by univariate analysis and a conventional Cox regression, in which the Least Absolute Shrinkage and Selection Operator (lasso) was used for selecting variables. The linear predictor from the Cox regression was then used to assign the patients into discrete risk groups. Prognostic models were constructed in a training set (n=611) and confirmed using an independent validation cohort (n=175). Results After excluding sequencing/mapping errors and known or possible polymorphisms, a total of 2,764 single nucleotide variants (SNVs) and insertions/deletions (indels) were called in 96 genes as high-probability somatic changes. A total of 47 genes were considered as statistically significantly mutated (p<0.01). Only 6 genes (TET2, SF3B1, ASXL1, SRSF2, DNMT3A, and RUNX1) were mutated in >10% of the cases. Less common mutations (2−10%) involved U2AF1, ZRSR2, STAG2, TP53, EZH2, CBL, JAK2, BCOR, IDH2, NRAS, MPL, NF1, ATM, IDH1, KRAS, PHF6, BRCC3, ETV6, and LAMB4. Intratumoral heterogeneity was evident in as many as 456 cases (48.3%), even though the small number of gene mutations available for evaluation was thought substantially to underestimate the real frequency. The number of observed intratumoral subpopulations tended to correlate with the number of detected mutations and therefore, advanced WHO subtypes and risk groups with poorer prognosis. Mean variant allele frequencies (VAFs) showed significant variations among major gene targets, suggesting the presence of clonogenic hierarchy among these common mutations during clonal evolution in MDS. The impact of these genetic lesions on clinical outcomes was initially investigated in 875 patients. In univariate analysis, 25 out of 48 genes tested significantly affected overall survival negatively (P<0.05), and only SF3B1mutations were associated with a significantly better clinical outcome. Next, to evaluate the combined effect of these multiple gene mutations/deletions, together with common clinical/cytogenetic variables used for IPSS-R, OS was modeled by a conventional Cox regression. A total of 14 genes, together with age, gender, white blood cell counts, hemoglobin, platelet counts, cytogenetic score in IPSS-R, were finally selected for the Cox regression in a proportional hazard model and based on the linear predictor of the regression model, we constructed a prognostic model (novel molecular model), in which patients were classified into 4 risk groups showing significantly different OS (“low”, “intermediate”, “high”, and “very high risk”) with 3-year survival of 95.2%, 69.3%, 32.8%, and 5.3%, respectively (P<0.001). These results demonstrated that the mutation/deletion status of a set of genes could be used as variables independent of clinical parameters to build a clinically relevant prognostic score. When applied to the validation cohort, the novel molecular model was even shown to outperform the IPSS-R. Conclusions Large-scale genetic and molecular profiling by cytogenetics, NGS and array-CGH not only provided novel insights into the pathogenesis and clonal evolution of MDS, but also helped to develop a powerful prognostic model based on gene mutations and other clinical variables that could be used for risk prediction. Molecular profiling of multiple target genes in MDS is feasible and provides an invaluable tool for improved diagnosis, biologic subclassification and especially prognostication for patients with MDS. Disclosures: Grossmann: MLL Munich Leukemia Laboratory: Employment. Bacher:MLL Munich Leukemia Laboratory: Employment. Schnittger:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Alpermann:MLL Munich Leukemia Laboratory: Employment. Roller:MLL Munich Leukemia Laboratory: Employment. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Kohlmann:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.
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Zeer, E. F., V. S. Tretyakova, and V. I. Miroshnichenko. "Strategic Directions of Pedagogical Personnel Training for the System of Continuing Vocational Education." Education and science journal 21, no. 6 (July 3, 2019): 93–121. http://dx.doi.org/10.17853/1994-5639-2019-6-93-121.
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. Introduction. Transition to a post-industrial socio-economic structure and information society caused education crisis, which is common for world space. Dynamic development of high technologies and rapid obsolescence of knowledge significantly reduced life cycle of professions and caused deep structural changes in the sphere of employment. The need of economics for workers with qualitatively new qualification characteristics - a flexible person with meta-professional competencies, capable to solve complex professional problems and ready for innovative activity not just for today, but with the future in mind - has necessitated a significant updating of the system of vocational training and its reorganisation facilitating the implementation of a formula “lifelong learning”. The solution of problems of education begins with qualitative training of teachers, since the qualities of future professionals - graduates of the educational organisation, primarily depend on the level of teachers’ competencies.The aim of the present article is to determine the strategic directions of innovative development of vocational education and preparation of highly qualified pedagogical personnel.Methodology and research methods. The hypothetico-inductive method, theoretic-methodological analysis and synthesis of the content of scientific literature were the major research methods. The research work was carried out on the basis of the principle of convergence, which determines cross-disciplinary and supra-professional communications, acts as a factor of design and a statement in professiology of a new phenomenon - transprofessionalism. The authors described the concept of transprofessionalism through the process- and project-based approaches.Results and scientific novelty. The developmental trends and directions of vocational education are considered. The principal defining factor of vocational education is close integration of all its processes and subsystems (prevocational training - secondary vocational education - higher education institutions - postgraduate training), which integrity is provided by the continuing and advanced education. The concept of transprofessionalism and convergence in multidisciplinary training of specialists is proved. The innovative educational programmes based on this concept are characterised. The logical-semantic model of a modern specialist is designed. This model can form an empirical basis to design vocational education platform, which integrates socio-humanistic, natural-science disciplines and related innovative technologies for teachers’ training in the system of continuing vocational education. Strategic directions for realisation of such preparation are formulated: transprofessionalism, cooperation / collaboration, advanced and “high-speed” training, digital transformation.Practical significance. The research materials can be useful for specialists in the field of vocational education, heads of the educational organisations in order to develop and make managerial decisions and to effectively organise the process of vocational training of pedagogical personnel.
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Nugroho, Suray Agung. "Pendampingan EPS-TOPIK (Employment Permit System–Test of Profciency in Korean) bagi Calon Pekerja Migran Indonesia dari Propinsi D.I. Yogyakarta." Bakti Budaya 2, no. 1 (April 15, 2019): 74. http://dx.doi.org/10.22146/bb.45042.
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The relatively low numbers of Indonesian migrant workers who passed the EPS-TOPIK (Employment Permit System–Test of Profciency in Korean) as a prerequisite to work in Korea as well as the relatively small numbers of Korean language instructors with experiences and backgrounds in Korean language teaching are the rationales that prompted Korean Language and Culture Program, Faculty of Cultural Sciences UGM to carry out this Community Engagement Activity. As an initial engagement, we carried out an EPS TOPIK Try Out test to 48 migrant worker candidates who currently learn Korean language at 5 Korean Language Courses in Yogyakarta Province. Tis is the frst engagement activity planned to be carried out continuously as our endeavor to solve the aforementioned problems. Based on the results of the Try Out test, we observed that they need to brush up their Korean competency in understanding Korean conversations and in using vocabularies in the right context. We will use these initial fndings as a basis to make a Learning and Teaching Material suitable for both the learners and the instructors. We plan to make the materials by incorporating both the learners and the instructors’ difculties in learning and teaching Korean language with EPS-TOPIK as the starting point. It is also worth to note that in many Korean Language Courses across the country, the main Korean language instructors are the returned migrant workers themselves. Albeit being able to write and talk in Korean, they had no prior educational background of Korean language. Tus, we also plan to continue setting up methods to teach them Korean language in a series of Training for Trainers program (the next Community Engagement Activities) in cooperation with related institutions like BNP2TKI (Agency for the Protection and Placement of Indonesian Migrant Workers). We deem it necessary to go on with the plan as the Government to Government Agreement between Korea and Indonesia in dispatching Indonesian migrant workers to Korea is still in effect. =================================================================Belum maksimalnya tingkat kelulusan para calon pekerja migran Indonesia (PMI) dalam ujian EPS-TOPIK (Employment Permit System–Test of Profciency in Korean) serta masih kurangnya jumlah pengajar bahasa Korea yang berlatar belakang pengajaran bahasa Korea di lembagalembaga pelatihan bahasa Korea mendorong Prodi Bahasa dan Kebudayaan Korea FIB UGM untuk memulai sebuah kegiatan Pengabdian kepada Masyarakat (PkM) dengan tema yang berkaitan dengan problema tersebut. Untuk itulah, sebagai langkah awal, prodi mengadakan try out ujian EPS-TOPIK kepada 48 calon PMI yang tengah belajar bahasa Korea di lima Lembaga Kursus & Pelatihan (LKP) Bahasa Korea di Provinsi DIY. Kegiatan ini adalah PkM perdana yang didesain untuk dilaksanakan secara berkelanjutan sebagai kontribusi langsung dalam pemecahan masalah. Berdasarkan hasil try out yang menunjukkan masih perlu ditingkatkannya kemampuan bahasa Korea para peserta, terutama dalam hal memahami percakapan dan pemakaian kosakata secara tepat, maka prodi berencana untuk menggunakan hasil ini sebagai landasan untuk membuat bahan ajar terkait EPS-TOPIK yang dapat digunakan oleh peserta didik ataupun para pengajar dalam mempelajari dan mengajarkan materi-materi dalam EPSTOPIK (Rencana PkM tahap 2). Selanjutnya, prodi bekerja sama dengan BP3TKI dan instansi lainnya berencana untuk menyelenggarakan Training of trainers, yaitu lokakarya pengajaran bahasa Korea untuk para pengajar bahasa Korea di LKP LKP seluruh Indonesia (Rencana PkM tahap 3). Semua itu didasari dengan fakta bahwa kerja sama Goverment to Government (G to G) antara Korea dan Indonesia dalam pengiriman PMI terus berjalan. Oleh karena itu, kegiatan PkM berkelanjutan ini didesain untuk memberikan sumbangan awal prodi dalam mengatasi rendahnya penyerapan calon PMI ke Korea yang disebabkan oleh rendahnya kemampuan bahasa Korea para calon PMI.
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Jemaa, Skander, Jill Fredrickson, Alexandre Coimbra, Richard AD Carano, Tarec Christoffer C. El-Galaly, Andrea Knapp, Tina G. Nielsen, Deniz Sahin, Thomas Bengtsson, and Alex de Crespigny. "A Fully Automated Measurement of Total Metabolic Tumor Burden in Diffuse Large B-Cell Lymphoma and Follicular Lymphoma." Blood 134, Supplement_1 (November 13, 2019): 4666. http://dx.doi.org/10.1182/blood-2019-124793.
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Introduction: Baseline total metabolic tumor volume (TMTV) from FDG-PET/CT scans has been shown to be prognostic for progression-free survival (PFS) in diffuse large B-cell lymphoma (DLBCL; Kostakoglu et al. Blood 2017) and follicular lymphoma (FL; Meignan et al. J Clin Oncol 2016). Fully automated TMTV measurements could increase reproducibility and enable results in real-time after a PET/CT scan. Although numerous methods for tumor segmentation on FDG PET images are published, they typically involve a manual step to identify a point within each tumor, performed by a trained reader, followed by semi-automatic identification of the tumor margins. To allow for rapid segmentation of whole body metabolic tumor burden, we developed a fully automated approach based on deep learning algorithms. Methods: An image processing pipeline was developed using FDG-PET/CT images from two large Phase III, multicenter trials, in first-line (1L) DLBCL (GOYA, NCT01287741, n=1418) and FL (GALLIUM, NCT01332968, n=1401). FDG-PET/CT scans were acquired according to a standardized imaging charter using a range of scanner models. Images were automatically preprocessed and used as inputs to cascaded 2D and region-specific 3D convolutional neural networks. The resulting tumor masks were then used for feature extraction. For simplicity, our prognostic analysis is limited to three variables: TMTV, number of identified lesions, and bulky disease (longest tumor diameter >7.5cm). For tumor segmentation, neural networks were trained on 2,266 scans from 1,133 patients in GOYA, and tested (out-of-sample) on 1,064 scans from 532 patients with evaluable baseline and end-of-treatment scans in GALLIUM. Manually directed, semi-automated tumor masks reviewed by board certified radiologists were used as ground truth for both training and testing. Based on the extracted tumor information, prognostic analyses for PFS were conducted on 1,139 evaluable pretreatment PET/CT scans from GOYA, and 541 patients from GALLIUM. Kaplan-Meier methodology was used for survival analysis, and a Cox proportional hazards (CPH) model was used for multivariate analysis. Results: From the out-of-sample validation step, the Dice Similarity Coefficient for the segmented tumor burden was 0.886, while the voxelwise sensitivity was 0.926. The lesion-level correlation between extracted and measured TMTV was 0.987. For PFS in the 1L DLBCL trial (GOYA), our calculated patient-level TMTV quartiles closely replicate the prognostic results of the semi-automated analysis reported by Kostakoglu et al. (Fig 1A, Table 1). A high lesion count above Q3 (>12 lesions [Fig 1B]) and bulky disease were also prognostic for PFS. To evaluate the prognostic value of the derived metrics, a simple risk score (RS) was constructed by considering the quantity: RS-DLBCL = 𝟙(TMTV >330ml) + 𝟙(nr. lesions ≥12) + 𝟙(bulky disease >1), where 𝟙(.) denotes the indicator function and 330ml is the median TMTV in GOYA. Multivariate CPH analysis verified the unique contribution of RS-DLBCL (p<0.0005) when added to the International Prognostic Index (IPI) score (p<0.01); derived from the multivariate model, the estimated HRs for RS-DLBCL are given in Table 2. In the 1L FL trial (GALLIUM), baseline TMTV >510mL was prognostic for PFS (HR, 1.59; p<0.013; Fig 1C). A high lesion count above Q3 (>18 lesions) and bulky disease (Fig 1D) were also prognostic. Three-year PFS for patients with TMTV <510mL was 85.1% (81.3-89.1%), while for TMTV >510mL, it was 77.3% (71.3-83.7%). A RS for 1L FL was defined similarly as for DLBCL: RS-FL = 𝟙(TMTV >510ml) + 𝟙(nr. lesions >18) + 𝟙(bulky disease). RS-FL (p<0.034) was significant when added to a CPH model with FLIPI (p<0.024). Estimated HRs for RS-FL after adjusting for FLIPI are given in Table 2. Conclusion: We present a novel approach for a fully automated whole body metabolic tumor burden segmentation on FDG-PET/CT scans for non-Hodgkin lymphoma patients. This method allows for the extraction of a range of tumor burden features from FDG-PET/CT. For example, TMTV, number of lesions, and bulky disease-features shown to be prognostic for PFS-in addition to known factors such as IPI/FLIPI. Our method is fast and produces a complete pt-level assessment in <5mins. Further development including clinical and biomarker covariates, and considering organ involvement, may yield better prognostic performance to identify pts who are likely to progress within 1-2 years. Disclosures Jemaa: Genentech, Inc./F. Hoffmann-La Roche Ltd: Employment. Fredrickson:Genentech, Inc.: Employment; F. Hoffmann-La Roche Ltd: Equity Ownership. Coimbra:Genentech, Inc.: Employment. Carano:Genentech, Inc.: Employment; F. Hoffmann-La Roche Ltd: Equity Ownership. El-Galaly:Takeda: Other: Travel support; Roche: Employment, Other: Travel support. Knapp:F. Hoffmann-La Roche Ltd: Employment. Nielsen:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. Sahin:F. Hoffmann-La Roche Ltd: Employment, Equity Ownership. Bengtsson:Genentech, Inc.: Employment; F. Hoffmann-La Roche Ltd: Equity Ownership. de Crespigny:Genentech, Inc.: Employment; F. Hoffmann-La Roche Ltd: Equity Ownership.
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Kim, Tae-Yeol, Brad Gilbreath, Emily M. David, and Sang-Pyo Kim. "Self-verification striving and employee outcomes." International Journal of Contemporary Hospitality Management 31, no. 7 (July 8, 2019): 2845–61. http://dx.doi.org/10.1108/ijchm-08-2018-0620.
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Purpose The purpose of this paper is to test whether self-verification striving serves as an individual difference antecedent of emotional labor and explore whether various emotional labor tactics acted as mediating mechanisms through which self-verification striving relates to employee outcomes. Design/methodology/approach The sample used in this paper consisted of supervisor–subordinate dyads working in six hotels in South Korea and used multi-level analyses and the Monte Carlo method to test the research hypotheses presented in this paper. Findings Self-verification striving was positively and directly related to job performance as well as two out of three forms of emotional labor (i.e. the expression of naturally felt emotions and deep acting). Self-verification striving also indirectly related to job satisfaction through the expression of naturally felt emotions and indirectly related to job performance through deep acting. Practical implications The findings of this paper suggest that organizations should consider self-verification striving as an employment selection criterion and provide training programs to help their customer service employees engage in appropriate types of emotional labor. Originality/value This paper is the first to explore the underlying mechanisms through which self-verification striving relates to employee outcomes. It also empirically bolsters the notion that expressing naturally felt emotions is an important means of authentic self-expression that positively contributes to job satisfaction. Further, the authors found that self-verification striving positively relates to job performance partially through deep acting. Moreover, they have shown that self-verification striving, as an individual differences variable, is an antecedent of different types of emotional labor.
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Mabaso, Simiso Lindokuhle. "The Economic Impacts of Tourism on the Local Community of Bergville, Kwazulu Natal, South Africa." Journal of Economics and Behavioral Studies 7, no. 5(J) (October 30, 2015): 29–36. http://dx.doi.org/10.22610/jebs.v7i5(j).603.
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Tourism is playing an increasingly important role in the local and national economy. The outstanding beauty of the northern Drakensberg is a prime tourist attraction in KwaZulu-Natal, attracting a regular flow of tourists throughout the year (Okhahlamba Municipality, 2013). The primary objective of this research is to investigate whether the benefits of tourism that are supposed to be reaped by the local community of Bergville, exist. If so, what are these benefits? There might be people from the local community, who are working within the tourism sector, but what are the types of jobs that they do, their level of job-satisfaction, and the extent to which they are able to earn a living from employment within the tourism sector? Do they have the necessary skills and training to allow them to make a successful career within the tourism sector? The White Paper on the Development and Promotion of Tourism (DEAT, 1996), states that with any tourism development in the local communities, local people should be involved in the decision making. They should be trained if they lack the necessary skills required to participate in that development. All these issues are relevant to Bergville as the region has a lot of tourism development, and it is a place that integrates tourism and conservation.
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Radiuk, Pavlo. "Applying 3D U-Net Architecture to the Task of Multi-Organ Segmentation in Computed Tomography." Applied Computer Systems 25, no. 1 (May 1, 2020): 43–50. http://dx.doi.org/10.2478/acss-2020-0005.
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AbstractThe achievement of high-precision segmentation in medical image analysis has been an active direction of research over the past decade. Significant success in medical imaging tasks has been feasible due to the employment of deep learning methods, including convolutional neural networks (CNNs). Convolutional architectures have been mostly applied to homogeneous medical datasets with separate organs. Nevertheless, the segmentation of volumetric medical images of several organs remains an open question. In this paper, we investigate fully convolutional neural networks (FCNs) and propose a modified 3D U-Net architecture devoted to the processing of computed tomography (CT) volumetric images in the automatic semantic segmentation tasks. To benchmark the architecture, we utilised the differentiable Sørensen-Dice similarity coefficient (SDSC) as a validation metric and optimised it on the training data by minimising the loss function. Our hand-crafted architecture was trained and tested on the manually compiled dataset of CT scans. The improved 3D UNet architecture achieved the average SDSC score of 84.8 % on testing subset among multiple abdominal organs. We also compared our architecture with recognised state-of-the-art results and demonstrated that 3D U-Net based architectures could achieve competitive performance and efficiency in the multi-organ segmentation task.
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Wagner, Richard K. "Intelligence, training, and employment." American Psychologist 52, no. 10 (October 1997): 1059–69. http://dx.doi.org/10.1037/0003-066x.52.10.1059.
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Allard, Gayle, and Vanina Farber. "Into the Abyss: Occupational Segregation of Immigrant Workers and the Spanish Crisis 2006-2012." Journal of Business Theory and Practice 4, no. 1 (April 15, 2016): 85. http://dx.doi.org/10.22158/jbtp.v4n1p85.
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<p><em>Spain became one of the world’s top immigration destinations in the 21<sup>st</sup> century, with the share of migrants in employment</em><em> </em><em>climbing to a peak of 17% just as the crisis hit the country. How did</em><em> </em><em>these immigrants fare in a rigid labour market as</em><em> </em><em>the housing bubble burst and recession brought soaring unemployment? Our paper explores the occupational segregation of Spain</em><em>’</em><em>s immigrants and finds that it declined in the wake of the crisis.</em><em> </em><em>The improvement, however, obscures massive job destruction in temporary jobs and in the low-skilled sectors where foreigners were concentrated. The results point to the need for better skills and training and measures to tackle the deep permanent/temporary contract divide in Spain,</em><em> </em><em>to protect migrant workers as well as unskilled Spaniards.</em></p>
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Hornstein Tomić, Caroline, and Karin Taylor. "Youth unemployment, the brain drain and education policy in Croatia: A call for joining forces and for new visions." Policy Futures in Education 16, no. 4 (February 23, 2018): 501–14. http://dx.doi.org/10.1177/1478210317751267.
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Since the economic recession and European Union accession, Croatia has seen a drastic increase in the emigration of tertiary-educated young people seeking further qualification and employment abroad. The brain drain has caused grave concern among political parties across the political spectrum and society as a whole. Recently, however, the tone of discourse has turned from accusations of national ‘disloyalty’ to engagement with how to mitigate the push factors for emigration on the one hand, and how to attract educated and successful migrants back to the country on the other. Changes to the education system are seen by experts and the public alike as one of the key factors in reducing the mismatch of prevailing education and training programmes with the specialist knowledge requirements of the domestic labour market and in improving youth employability. However, efforts to introduce urgently needed education reforms have recently been stalled by a lack of political consensus on aspects of a proposed reform package and its implementation rooted in the deep ideological rifts of post-socialist transformation. This contribution investigates how the impact of the brain drain, as well a shift towards recognition of the possible benefits of circular migration, have affected recent discourse on education policy and the growing involvement of non-governmental organizations and initiatives in introducing a more practice-based orientation to education on all levels.
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Lu, Quan, Bixuan Song, Jing Chen, Iris Xie, and Yutian Shen. "Information needs and services for autism in China: is there any gap between them?" Aslib Journal of Information Management 73, no. 4 (June 1, 2021): 497–516. http://dx.doi.org/10.1108/ajim-11-2020-0370.
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PurposeThis study aims to explore the gap between information needs and services for autism in China.Design/methodology/approachThe gap is revealed by investigating the status quo of autism information needs and services. The authors extracted categories and subcategories of information needs through content analysis of academic documents and then supplemented the subcategories through text mining of an online forum. Meanwhile, categories and subcategories of information services were extracted through content analysis of autism websites. Finally, the authors matched the two to explore the gap and designed a quantitative index to measure it.FindingsA total of eight and ten categories of information needs and services are extracted, respectively. In total, six categories of information needs can be partly matched, but nearly half of the subcategories failed. Huge gaps in economic support, sociality and policy mechanisms categories are observed through the quantitative index and medium gaps in social resource services and employment categories while almost no gaps in psychological/emotional counseling, rehabilitation skills training and professional knowledge/information categories.Originality/valueThis study takes a deep insight into the gap between autism information needs and services in China, providing evidences and suggestions for information providers to improve their services. Academic documents and online forum data are adopted to avoid the impact of stigmatization, which provides a multi-source data analysis approach for the information needs of special groups.
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Meng, Xiangmin, Jie Zhang, and Guoyan Ren. "The Evaluation Model of College Students’ Mental Health in the Environment of Independent Entrepreneurship Using Neural Network Technology." Journal of Healthcare Engineering 2021 (September 24, 2021): 1–9. http://dx.doi.org/10.1155/2021/4379623.
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In recent years, the employment of college students is becoming more and more prominent; no matter for the society, universities, college students themselves, and their families have formed a huge pressure, in the current situation, the success rate of college students to start their own business is not high; one of the important reasons is that college students generally have defects in entrepreneurial psychology. Therefore, effective evaluation of college students’ mental health under the environment of independent entrepreneurship is conducive to comprehensively improving the quality of talent training in colleges and universities. In this paper, we propose a novel three-channel multifeature fusion network based on neural network technology to identify and predict college students’ mental health problems in the self-entrepreneurship environment. Specifically, we first extract the behavior characteristics, visual characteristics, and social relations as a three-channel network input. Second, in view of the behavior characteristic, we use the length of the memory deep context dependent on network access. In view of visual features, we use the convolution neural network to face emotional characteristics and characteristics of social relations. The feature concat strategy is used for feature fusion. The experimental results on real datasets show that the method in this paper is effective, and it is expected to propose a new solution for college students’ mental health assessment.
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Monti, Luciano. "Generational Divide: A New Model to Measure and Prevent Youth Social and Economic Discrimination." Review of European Studies 9, no. 3 (August 16, 2017): 151. http://dx.doi.org/10.5539/res.v9n3p151.
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Measures concerning intergenerational inequality generally refer to youth unemployment or youth household income and wealth. The common conclusion is that the generational gap is represented by negative trend of youth unemployment and NEETS. In this paper, I argue that this phenomenon is not the cause of intergenerational unfairness, but one of its effects.The pioneering efforts to measure the intergenerational fairness through a set of multidimensional indicators are the starting point for deeper analysis. The purpose of this paper, however, is not only to measure unfairness, but to quantify the generational divide. The latter is defined as the intensity of material and immaterial barriers affecting a sound development of individuals.The way to measure such a phenomenon is to use a new and comprehensive, synthetic index, applied to the Italian youth emergency and social discrimination. For this reason some new indicators are added to the previous models, such as credit crunch, the scar inferred to NEET (Not in Education, Employment or Training), digital divide and barriers to mobility.The results of this pilot analysis in the selected country for the period 2004-2012 demonstrate a worsening of the generational divide over the last five years and these high negative trends are mainly due to housing costs, decreasing incomes and the pension burden. These results suggest the need for a deep and careful consideration on the real intergenerational sustainability of current European and development strategies and show a large discrimination towards the younger generations.
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Drodge, Stephen. "Education, training and employment dynamics." International Journal of Educational Development 23, no. 6 (November 2003): 686–88. http://dx.doi.org/10.1016/s0738-0593(03)00067-1.
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Waite, Richard K., and Stephen Holly. "Training and employment in pharmacology." British Journal of Pharmacology 105, no. 3 (March 1992): 507. http://dx.doi.org/10.1111/j.1476-5381.1992.tb09007.x.
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Christopher, Tony. "Training for employment: Countering disadvantage." Policy Studies 11, no. 3 (September 1990): 49–53. http://dx.doi.org/10.1080/01442879008423575.
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Hollister, Robinson G. "Youth Employment and Training Programs." ILR Review 41, no. 1 (October 1987): 141–45. http://dx.doi.org/10.1177/001979398704100112.
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The other men were easy to talk to, but they didn't know anything. If one stopped to think about it, it was depressing how little most men learned in their lifetimes. Pea Eye was a prime example. Though loyal and able and brave, Pea had never displayed the slightest ability to learn from his experience, though his experience was considerable. Time and again he would walk up on the wrong side of a horse that was known to kick, and then look surprised when he got kicked.
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Usher, Graham. "Employment Training: Britain's new Bantustans." Race & Class 32, no. 1 (July 1990): 45–56. http://dx.doi.org/10.1177/030639689003200104.
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Kisely, Steve, and Judy Jones. "Training and employment in Canada." Psychiatric Bulletin 20, no. 2 (February 1996): 100–103. http://dx.doi.org/10.1192/pb.20.2.100.
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Previous articles have dealt with aspects of training in Canada (Green, 1985), and in particular arrangements that exist for UK trainees to undertake a year's experience in Nova Scotia (Munro et al 1987). In addition, there have been accounts of trainees' experiences in particular settings (Ferguson, 1989; Gojo, 1992). Procedures required to enter Canada to practise psychiatry are complex and involve general and specialist medical registration (licensure to practise and certification as a specialist), remuneration and immigration procedures. This article is an introductory guide and highlights recent changes in registration and postgraduate training.
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Hodgson, David. "Training Policy and Employment Generation." International Journal of Manpower 12, no. 4 (April 1991): 28–31. http://dx.doi.org/10.1108/01437729110144899.
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Barnow, Burt S. "Evaluating employment and training programs." Evaluation and Program Planning 9, no. 1 (January 1986): 63–72. http://dx.doi.org/10.1016/0149-7189(86)90009-1.
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Zinchenko, Yu P., E. M. Dorozhkin, and E. F. Zeer. "Psychological and Pedagogical Bases for Determining the Future of Vocational Education: Vectors of Development." Education and science journal 22, no. 3 (April 29, 2020): 11–35. http://dx.doi.org/10.17853/1994-5639-2020-3-11-35.
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Introduction. Today, the field of education around the world is facing a protracted crisis caused by the transition to post-industrial society. The dynamic knowledge obsolescence due to the rapid development of science and high technology caused deep structural changes in employment and significantly shortened the life cycle of professions. Modern economy needs specialists with qualitatively new characteristics: a competent and flexible person with meta-professional competencies, who is capable to implement innovative activity and to work in multitasking regime in the situation of instability and uncertainty, and who is ready for active professional self-determination throughout life. Therefore, a radical reorganisation of vocational education system is necessary to be undertaken. It is significantly important to solve this problem through the conduction of professional and pedagogical training of teachers, since the level of their competency primarily depends on the qualitative characteristics of future employees for diverse sectors of the economy and production.The aim of the present article is to define strategic guidelines for predicting the development of professional education in the conditions of post-industrial society.Methodology and research methods. The theoretical and methodological framework of the research is based on the theory of vocational development, the concept of determining the immediate and long-term perspectives of educational sphere, as well as logical-evolutionary, system-dynamic, project-based, personal and convergent approaches. In the course of the research, the methods of analysis, synthesis, generalisation and hypothetical-inductive method were applied.Results and scientific novelty. The trends and directions of vocational education development are identified and described. The principal defining factor of vocational education is close integration of all its processes and subsystems (prevocational, primary vocational, vocational higher secondary and postgraduate education), which integrity is ensured by the continuity and compliance with the principle of advanced education. The concept of convergence and transprofessional in multi-disciplinary training of professionals is revealed. The process of convergence, determining interdisciplinary and prevocational links, ensures transprofessionalism formation – human readiness and participation in the development and realisation of new types of socio-professional activities. A logical and semantic model of a modern specialist is constructed. This model can serve as an empirical basis for designing and supporting a vocational educational platform, which integrates natural science, industrial-technological and socio-humanitarian disciplines and related innovative technologies when training teachers for the system of vocational education. Transprofessionalism, cooperation, collaboration, advanced and high-speed education are highlighted as the vocational training strategies in the conditions of digital transformation of the economy.Practical significance. The research materials can be useful for the specialists in the field of vocational education, for the managerial staff of educational organisations when developing management decisions and organising efficient preparation of teaching personnel.
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Müller, Martha-Lena, Niroshan Nadarajah, Kapil Jhalani, Inseok Heo, William Wetton, Claudia Haferlach, Torsten Haferlach, and Wolfgang Kern. "Employment of Machine Learning Models Yields Highly Accurate Hematological Disease Prediction from Raw Flow Cytometry Matrix Data without the Need for Visualization or Human Intervention." Blood 136, Supplement 1 (November 5, 2020): 11. http://dx.doi.org/10.1182/blood-2020-140927.
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Background: Machine Learning (ML) offers automated data processing substituting various analysis steps. So far it has been applied to flow cytometry (FC) data only after visualization which may compromise data by reduction of data dimensionality. Automated analysis of FC raw matrix data has not yet been pursued. Aim: To establish as proof of concept an ML-based classifier processing FC matrix data to predict the correct lymphoma type without the need for visualization or human analysis and interpretation. Methods: A set of 6,393 uniformly analyzed samples (Navios cytometers, Kaluza software, Beckman Coulter, Miami, FL) was used for training (n=5,115) and testing (n=1,278) of different ML models. Entities were chronic lymphatic leukemia (CLL) 1103 (training) and 279 (testing), monoclonal B-cell lymphocytosis (MBL, 831/203), CLL with increased prolymphocytes (CLL-PL, 649/161), lymphoplasmacytic lymphoma (LPL, 560/159), hairy cell leukemia (HCL, 328/88), mantle cell lymphoma (MCL, 259/53), marginal zone lymphoma (MZL, 90/28), follicular lymphoma (FL, 84/16), no lymphoma (1211/291). Three tubes comprising 11 parameters per tube were applied. Besides scatter signals analyzed antigens included: CD3, CD4, CD5, CD8, CD10, CD11c, CD19, CD20, CD22, CD23, CD25, CD38, CD45, CD56, CD79b, CD103, FMC7, HLA-DR, IgM, Kappa, Lambda. Measurements generated LMD files with 50,000 rows of data for each of the 11 parameters. After removing the saturated values (≥ 1023) we produced binned histograms with 16 predefined frequency bins per parameter. Histograms were converted to cumulative distribution functions (CDF) for respective parameters and concatenated to produce a 16x11 matrix per each tube. Following the assumption of independence of parameters this simplification of concatenating CDFs represents the same information as if they were jointly distributed. The first matrix-based classifier was a decision tree model (DT), the second a deep learning model (DL) and the third was an XGBoost (XG) model, an implementation of gradient boosted decision trees ideal for structured tabular data (such as LMD files). The first set of analyses included only three classes which are readily separated by human operators: 1) CLL, 2) HCL, 3) no lymphoma. The second set included all nine entities but grouped into four classes: 1) CD5+ lymphoma (CLL, MBL, CLL-PL, MCL), 2) HCL, 3) other CD5- lymphoma (LPL, MZL, FL), 4) no lymphoma. The third set included each of the nine entities as its own class. Results: Analyzing the three classes from the first set (CLL, HCL, no lymphoma) the models achieved accuracies of 94% (DT), 95% (DL) and 96% (XG) when including all cases. By analysis of cases with prediction probabilities above 90%, DT now reached 97%, DL 97% and XG 98% accuracy, whilst losing 38%, 8% and 6% of samples, respectively. We further observed that accuracy was also dependent on the size of the pathologic clone, which is in line with the experiences from human experts with very small clones (≤ 0.1% of leukocytes) representing a major challenge regarding their correct classification. Focusing on cases with clones > 0.1% but considering all prediction probabilities accuracies were 96% (DT), 97% (DL) and 98% (XG), with loss of 5% of samples for each model. Considering cases only with prediction probabilities > 90% and clones > 0.1% accuracies were 97% (DT), 99% (DL) and 99% (XG) whilst losing 38%, 9% and 9% of samples, respectively. Further analyses were performed applying the best model based on results above, i.e. XG. Analyzing four classes in the second set of analyses (CD5+ lymphoma, HCL, other CD5- lymphoma, no lymphoma) and considering cases only with prediction probabilities > 95% and clones > 0.1% accuracy was 96% while losing 28% of samples. In the third set of analyses with each entity assigned its own class and again considering cases only with prediction probabilities > 95% and clones > 0.1% accuracy was 93% while losing 28% of samples. Conclusions: This first ML-based classifier using the XGboost model with transforming FC matrix data to concatenated distributions, is capable of correctly assigning the vast majority of lymphoma samples analyzing FC raw data without visualization or human interpretation. Cases that need further attention by human experts will be flagged but will not account for more than 30% of all cases. This data will be extended in a prospective blinded study (clinicaltrials.gov NCT4466059). Disclosures Heo: AWS: Current Employment. Wetton:AWS: Current Employment.
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Nazha, Aziz, Rami S. Komrokji, Manja Meggendorfer, Sudipto Mukherjee, Najla Al Ali, Wencke Walter, Stephan Hutter, et al. "A Personalized Prediction Model to Risk Stratify Patients with Myelodysplastic Syndromes." Blood 132, Supplement 1 (November 29, 2018): 793. http://dx.doi.org/10.1182/blood-2018-99-114774.
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Abstract Background Patients (pts) with myelodysplastic syndromes (MDS) have heterogeneous outcomes that can range from months for some pts to decades for others. Although several prognostic scoring systems have been developed to risk stratify MDS pts, survival varies even within discrete categories, which may lead to over- or under-treatment. Deficits in discriminatory power likely derive from analytic approaches or lack of incorporation of molecular data. Here, we developed a model that uses a machine learning approach to analyze genomic and clinical data to provide a personalized overall outcome that is patient-specific. Method Clinical and mutational data from MDS pts diagnosed according to 2008 WHO criteria were analyzed. The model was developed in a combined cohort from the Cleveland Clinic and Munich Leukemia Laboratory and validated in a separate cohort from the Moffitt Cancer Center. Next generation targeted deep sequencing of 40 gene mutations commonly found in myeloid malignancies was performed. Pts who underwent hematopoietic cell transplant (HCT) were censored at the time of transplant. A random survival forest (RSF) algorithm was used to build the model, in which clinical and molecular variables are randomly selected for inclusion in determining survival, thereby avoiding the shortcomings of traditional Cox step-wise regression in accounting for variable interactions. Survival prediction is thus specific to each pt's particular clinical and molecular characteristics. The accuracy of the proposed model, compared to other models, was assessed by concordance (c-) index. Results Of 2302 pts, 1471 were included in the training cohort and 831 in the validation cohort. In the training cohort, the median age was 71 years (range, 19-99), 230 pts (16%) progressed to AML, 156 (11%) had secondary/therapy-related MDS, and 130(9%) underwent HCT. Risk stratification by IPSS: 391 (27%) low, 626 (43%) intermediate-1, 280 (19%) intermediate-2, 104 (7%) high, 104 (7%) missing, and by IPSS-R: 749 (51%) very low/ low, 336 (23%) intermediate, 190 (13%) high, 92 (6%) very high, and 104 (7%) missing. Cytogenetic analysis by IPSS-R criteria: 65 (4%) very good, 1060 (72%) good, 193 (13%) intermediate, 60 (4%) poor, and 93 (6%) very poor. The most commonly mutated genes were: SF3B1 (26%), TET2 (25%), ASXL1 (20%), SRSF2 (15%), DNMT3A (12%), STAG2 (8%), RUNX1 (8%), and TP53 (8%). All clinical variables and mutations were included in the RSF algorithm. To identify the most important variables that impacted the outcome and the least number of variables that produced the best prediction, we conducted several feature extraction analyses which identified the following variables that impacted OS (ranked from the most important to the least): cytogenetic risk categories by IPSS-R, platelets, mutation number, hemoglobin, bone marrow blasts %, 2008 WHO diagnosis, WBC, age, ANC, absolute lymphocyte count (ALC), TP53, RUNX1, STAG2, ASXL1, absolute monocyte counts (AMC), SF3B1, SRSF2, RAD21, secondary vs. de novo MDS, NRAS, NPM1, TET2, and EZH2. The clinical and mutational variables can be entered into a web application that can run the trained model and provide OS and AML transformation probabilities at different time points that are specific for a pt, Figure 1. The C-index for the new model was .74 for OS and .81 for AML transformation. The new model outperformed IPSS (c-index .66, .73) and IPSS-R (.67, .73) for OS and AML transformation, respectively. The geno-clinical model outperformed mutations only (c-index .64, .72), mutations + cytogenetics (c-index .68, .74), and mutations + cytogenetics +age (c-index .69, .75) for OS and AML transformation, respectively. Addition of mutational variant allelic frequency did not significantly improve prediction accuracy. When applying the new model to the validation cohort, the c-index for OS and AML transformation were .80, and .78, respectively. Conclusion We built a personalized prediction model based on clinical and genomic data that outperformed IPSS and IPSS-R in predicting OS and AML transformation. The new model gives survival probabilities at different time points that are unique for a given pt. Incorporating clinical and mutational data outperformed a mutations only model even when cytogenetics and age were added. Disclosures Nazha: MEI: Consultancy. Komrokji:Celgene: Honoraria, Research Funding; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Celgene: Honoraria, Research Funding. Meggendorfer:MLL Munich Leukemia Laboratory: Employment. Walter:MLL Munich Leukemia Laboratory: Employment. Hutter:MLL Munich Leukemia Laboratory: Employment. Sallman:Celgene: Research Funding, Speakers Bureau. Roboz:Otsuka: Consultancy; Orsenix: Consultancy; Celgene Corporation: Consultancy; Daiichi Sankyo: Consultancy; Pfizer: Consultancy; Cellectis: Research Funding; Argenx: Consultancy; Roche/Genentech: Consultancy; Celltrion: Consultancy; Sandoz: Consultancy; Aphivena Therapeutics: Consultancy; Bayer: Consultancy; Pfizer: Consultancy; Aphivena Therapeutics: Consultancy; Eisai: Consultancy; Sandoz: Consultancy; Eisai: Consultancy; Roche/Genentech: Consultancy; AbbVie: Consultancy; Novartis: Consultancy; Janssen Pharmaceuticals: Consultancy; Bayer: Consultancy; Celltrion: Consultancy; Novartis: Consultancy; Janssen Pharmaceuticals: Consultancy; Astex Pharmaceuticals: Consultancy; Daiichi Sankyo: Consultancy; Celgene Corporation: Consultancy; Jazz Pharmaceuticals: Consultancy; Jazz Pharmaceuticals: Consultancy; Cellectis: Research Funding; Otsuka: Consultancy; Orsenix: Consultancy; Argenx: Consultancy; Astex Pharmaceuticals: Consultancy; AbbVie: Consultancy. List:Celgene: Research Funding. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Maciejewski:Apellis Pharmaceuticals: Consultancy; Ra Pharmaceuticals, Inc: Consultancy; Alexion Pharmaceuticals, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Ra Pharmaceuticals, Inc: Consultancy; Alexion Pharmaceuticals, Inc.: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Apellis Pharmaceuticals: Consultancy. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Sekeres:Opsona: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Opsona: Membership on an entity's Board of Directors or advisory committees.
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Lebert, Florence, and Erika Antal. "Reducing Employment Insecurity." SAGE Open 6, no. 4 (October 2016): 215824401667176. http://dx.doi.org/10.1177/2158244016671769.
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The perception of job insecurity is known to be a stressful condition for employees. Less is known about employment insecurity and the ways employees and their families deal with it. This study investigates whether participation in further training is a strategy that employees adopt to reduce perceived employment insecurity. As participation in further training is often costly and time-consuming, we assume that the family context is of importance for the decision to take part in further training. To take account of possible self-selection, we apply a propensity score matching procedure on longitudinal data from the Swiss Household Panel (2004-2013). Three main findings can be emphasized: first, participation in further training is not a strategy adopted particularly by employees who perceive high employment insecurity as they are less likely to train than their secure counterparts. Second, even though further training is not a strategy that is actively adopted, employees who train subsequently report lower levels of perceived employment insecurity. Third, the family context indeed influences the likelihood to train: partnered employees are more likely to train and preschool-aged children act as a constraint on women’s but enhance men’s participation in further training. Yet, in the context of high perceived employment insecurity, children generally reduce their parents’ likelihood to train as the parents may turn to other strategies that reduce perceived employment insecurity.
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Zweimuller, Josef, and Rudolf Winter-Ebmer. "Manpower Training Programmes and Employment Stability." Economica 63, no. 249 (February 1996): 113. http://dx.doi.org/10.2307/2554637.
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Blanco-García, Montserrat, Pablo Sánchez-Antolín, and Francisco Javier Ramos-Pardo. "Women’s Perceptions of Training and Employment." Mediterranean Journal of Social Sciences 8, no. 3 (May 24, 2017): 155–62. http://dx.doi.org/10.5901/mjss.2017.v8n3p155.
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Abstract Despite institutional declarations, women still rank second in key areas of society related to employment. The goal of this study was to analyse the perceptions of Spanish women taking occupational training courses and of gender equality experts with respect to the relationship between initial formal education, occupational training, continuing education and employment, as well as the role played by the family in this relationship, in order to elucidate conceptions of women’s social reality in the fields of education and employment. A qualitative methodology was employed, consisting of semi-structured, in-depth individual and group interviews with women taking occupational training courses. Interviews were also conducted with experts in gender equality. Working women’s conception of the relationship between training and employment is heavily influenced by the effect of gender socialisation, which leads them to assume the role of carer in the family. Women’s choice of training presents a clear gender bias that directly influences the jobs they hold. In many cases, these comprise subsistence activities that coincide with traditional female roles. However, women with a higher education present less dependence on gender roles. Socialisation in gender stereotypes is evident in working women’s discourse, and generates frustration at the impossibility of reconciling all the areas of responsibility assigned to them, leading them to relinquish any expectations of professional or personal development.
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Davoudi, Simin. "Women and part-time employment training." Local Economy: The Journal of the Local Economy Policy Unit 8, no. 1 (May 1993): 33–42. http://dx.doi.org/10.1080/02690949308726171.
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Murphy, Garrett. "Employment & Training: Making the Connection." Adult Learning 7, no. 5 (May 1996): 22–31. http://dx.doi.org/10.1177/104515959600700516.
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Bulgarelli, Aviana, and Antonio Ranieri. "Vocational Training, Employment and Labour Participation." Evaluation 3, no. 3 (July 1997): 280–99. http://dx.doi.org/10.1177/135638909700300303.
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