Academic literature on the topic 'TNI (TRAINING NEED IDENTIFICATION)'
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Journal articles on the topic "TNI (TRAINING NEED IDENTIFICATION)"
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Ramli, Mastura Binti, Noradilah Binti Sukor, and Sharifah Nurulhuda Binti Tuan Mohd Yasin. "E-TNA identification." Journal of Educational and Learning Studies 1, no. 1 (December 30, 2018): 1. http://dx.doi.org/10.32698/0162.
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Electronic Training Need Analysis Identification (e-TNAi) is an application of responsive web systems developed to provide accurate and relevant data on the predictions of training needs of an organization. This system application can be accessed through a variety of devices where each staff can fill out the training requirements information everywhere. This effective method allows information to be collected centrally. The training offers are based on the field of training and staff’s choice. The staff's interest and knowledge and additional values will be linked directly to this app in ensuring the right training offers. The novelty and uniqueness of this system is from the aspect of smart identification; the system will identify the priority of which training the management needs to organize. Additionally, this method also has a good impact in which it is time-saving in the aspect of effective decision making at the organization level. In short, this application gives you the edge in the accuracy of information as well as smart, portable, flexible and cost-effective. The e-TNAi system is a system applied at Sultan Mizan Zainal Abidin Polytechnic (PSMZA). It is also very suitable to be applied and has the potential to be marketed as it can be used by all polytechnics in Malaysia. This system can also be applied to all other institutions to assist management in decision making of training priorities in future.
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Jungjohann, Jana, and Markus Gebhardt. "Dimensions of Classroom-Based Assessments in Inclusive Education." International Journal of Special Education (IJSE) 38, no. 1 (March 15, 2023): 131–44. http://dx.doi.org/10.52291/ijse.2023.38.12.
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Inclusive education aims to provide learning progress for all. It requires assessments to identify learning levels and progress and to adapt and evaluate instruction. We extend the classroom-based assessment (CBA) approach and argue that CBA in inclusive schools consists of the four dimensions of Instructional Decision-Making, Educational Assessment, Identification of Students with Special Educational Needs, and Progress Monitoring. For this paper, we developed both a framework of CBA for research interests and individual scales for each dimension (6 to 9 items per scale) in order to identify the four dimensions in which teachers need further training. To create a more manageable instrument for education and training practice, we tested a combined model as a questionnaire. In a survey of 110 teachers and 152 pre-service special education teachers (N = 252), the individual scales had good internal consistency (α = .92, .82, .92, .93). Using Confirmatory Factor Analysis, an initial combined model, consisting of the revised individual scales, showed acceptable fit values (CFI = 0.94, TLI = 0.89, RMSEA = 0.07, SRMR = 0.06) almost everywhere. The further development of the questionnaire and its significance and relevance for inclusive educational practice will be discussed.
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Sihotang, Boston Raymond, Edi Susilo, and Jumino Jumino. "Optimalisasi Sinergitas TNI-Polri Dalam Penanggulangan Terorisme di Indonesia." Jurnal Ilmu Administrasi Negara ASIAN (Asosiasi Ilmuwan Administrasi Negara) 9, no. 2 (September 28, 2021): 261–78. http://dx.doi.org/10.47828/jianaasian.v9i2.63.
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This study aims to describe the synergy between TNI and Polri in countering terrorism. This research uses a mixed method with a SWOT analysis (Strength, Weakness, Opportunity, and Threat) to find the best strategies in increasing the synergy between TNI and Polri in countering terrorism. This research concludes that there is a need for a Presidential Decree which contains technical operational regulations so that the TNI's involvement mechanism is clearer in countering terrorism, command and control in countering acts of terrorism is one of the main factors that determine the success of operations. The ability of the TNI and Polri to cope with actions terrorism is still not optimal because of the lack of intensity of joint training in counterterrorism, as well as a narrow, negative and overblown understanding of "esprit de corps" will have negative implications for application in everyday life and in assignment situations, especially in counterterrorism involving the TNI and Polri.d short conclusion. The abstract should only be typed in one paragraph and one-column format.
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Denslow, Paula, Jean Doster, Kristin King, and Jennifer Rayman. "Project BRAIN: Working Together to Improve Educational Outcomes for Students With Traumatic Brain Injury." Perspectives on Neurophysiology and Neurogenic Speech and Language Disorders 22, no. 3 (October 2012): 106–18. http://dx.doi.org/10.1044/nnsld22.3.106.
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Children and youth who sustain traumatic brain injury (TBI) are at risk for being unidentified or misidentified and, even if appropriately identified, are at risk of encountering professionals who are ill-equipped to address their unique needs. A comparison of the number of people in Tennessee ages 3–21 years incurring brain injury compared to the number of students ages 3–21 years being categorized and served as TBI by the Department of Education (DOE) motivated us to create this program. Identified needs addressed by the program include the following: (a) accurate identification of students with TBI; (b) training of school personnel; (c) development of linkages and training of hospital personnel; and (d) hospital-school transition intervention. Funded by Health Services and Resources Administration (HRSA) grants with support from the Tennessee DOE, Project BRAIN focuses on improving educational outcomes for students with TBI through the provision of specialized group training and ongoing education for educators, families, and health professionals who support students with TBI. The program seeks to link families, hospitals, and community health providers with school professionals such as speech-language pathologists (SLPs) to identify and address the needs of students with brain injury.
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O.SARADA*, G.V. SUNEEL KUMAR and G. SIVANARAYANA. "SERVICES OFFERED BY THE RBKS AND TRAINING NEEDS OF VILLAGE AGRICULTURAL ASSISTANTS IN GUNTUR DISTRICT." Journal of Research ANGRAU 51, no. 1 (March 31, 2023): 152–62. http://dx.doi.org/10.58537/jorangrau.2023.51.1.17.
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The attempt was made to analyse the awareness and utility of RBK services by the farmers and training needs of Village Agricultural Assistants (VAAs) in Guntur district. Hundred farmers from 10 subdivisions and 165 VAAs from 55 mandals were selected asthe respondents. Majority of the farmers were aware of distribution of quality fertilizers (88.00%), e-crop booking (86.00%), soil & water testing facility (78.00%), free crop insurance/ animal insurance (75.00%), provision of quality seed (green manure/ crop seed/fodder seed/concentrate feed) (73.00%), distribution of quality pesticides (60.00%) and provision of need based information to farmers on crop healthmanagement (57.00%). With respect to utility, only few services are utilised by the farmers’ viz., e crop booking (82.00%), free crop insurance / animal insurance (59.00%) and distribution of quality fertilizers (58.00%). Majority of the Village Agricultural Assistants expressed that Integrated Disease Management (87.27 TNI & Rank I), Integrated Pest management (83.64TNI &Rank II), new varieties (81.41TNI & Rank III),Micro nutrient management (80.80TNI & Rank IV), Integrated weed management (80.20 TNI & Rank V) are the major areas of training needed by them. Major constraints expressed by VAAs are inability to meet the demands of farmers with respect to providing all of them with subsidies, inability to maintain sufficient fertilizers, pesticides and otherstocks as required by farmers and Heavy work load.
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Amir, Muhammad, Sabir Hussain, and Shamsheer Muhammad. "Identification of the Need for Teacher Training at The Primary School Level." International Research Journal of Education and Innovation 3, no. 1 (March 31, 2022): 165–76. http://dx.doi.org/10.53575/irjei.v3.01.16(22)165-176.
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The study's main objective was to determine the need for primary school teacher training. The study's major goals were to (a) investigate the importance of teacher training programs at the primary school level for the effectiveness of the teaching-learning process; (b) determine the need for teacher training at the primary school level; (c) determine the need for professional training at the primary school level, and (c) recommend specific measures to improve primary school teacher training. A survey technique was utilized to conduct the study. Through random sampling, one hundred thirty-eight (138) male-female public primary and Punjab Education Foundation (PEF) affiliated school teachers were selected from the five Tehsils of District Bahawalpur with an equal proportion of urban and rural schools. The data were collected through a questionnaire and interpreted through SPSS V23. The results showed that no one teacher had excellent knowledge of to use learning tools in the classroom, Knowledge of National Profession Standards for teachers, concepts of math, practical application of content knowledge skills and English Language skills. So, there is a need of training for teachers to use the learning tools in the classroom effectively, to know about National professional Standards for teachers, teaching skills of math, science, and English.
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Arif, Samsul. "DEVELOPMENT OF 1 ST ENGINEER BATTALION OF MARINE CORPS PERSONNEL IN ORDER TO FOLLOW THE UNITED NATIONS MISSIONS PEACEKEEPING OPERATIONS." Jurnal Strategi Pertahanan Laut 8, no. 1 (June 14, 2022): 46. http://dx.doi.org/10.33172/spl.v8i1.1041.
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Indonesia consistently sends TNI troops to the UN Peacekeeping Mission as a Garuda Contingent. The 1st Engineer Battalion of the Marine Corps needs to increase its unit's readiness to support the TNI's tasks in every world peacekeeping operation. Each unit personnel is expected to have readiness in following each assignment mission so that they are able to meet the specified requirements. However, unit personnel still did not pass the assignment selection at the recruitment stage. This study will analyze the formation of 1 st Engineer Battalion of Marine Corps personnel to follow the assignment, especially at the recruitment stage using qualitative methods. From the results of the study, it can be seen that the personnel training carried out by the unit is still unable to increase its personnel's readiness in following assignments optimally. Therefore we need an effort to foster personnel comprehensively.
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Juanda, Juanda, and Ogiandhafiz Juanda. "Pengangkatan Penjabat Kepala Daerah Menghadapi Pilkada Serentak 2024 Dalam Perspektif Hukum Tata Negara." Jurnal Keamanan Nasional 8, no. 1 (August 11, 2022): 192–219. http://dx.doi.org/10.31599/jkn.v8i1.534.
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This research is entitled "appointment of acting regional heads to face the 2024 simultaneous regional-head elections in the perspective of constitutional law". This research is considered urgent because there are numerous important aspects of the appointment of the Acting Regional Heads that need to be studied and analyzed, including the pros and cons of the absence of Government Regulations, the lack of transparency, openness, and accountability, as well as the pros and cos regarding the appointment of active members of the TNI and POLRI as acting regional heads. The problem is stated as follows: 1. How is the appointment of the acting Regional Heads to face the 2024 simultaneous regional head elections in the perspective of constitutional law? 2. How is the appointment of middle high leaders and Pratama high leaders who are members of the TNI and POLRI as acting Regional Heads according to statutory regulations? This research is a normative juridical research that employs primary, secondary, and tertiary legal materials. The method of collecting legal materials is carried out by literature study, while the method of processing legal materials is inventory, identification, categorization, and systematization of existing legal materials, and the analytical method used is a qualitative juridical method. The conclusions of the research are 1. the appointment of acting Regional Heads that has been carried out by the Government to face the 2024 regional head elections in a formal or textual juridical manner is in accordance with the provisions of Article 201 paragraph (10) and (11) of Law No. 10 of 2016 concerning the Election of Governors, Regents, and Mayors. However, in essence and substance, the appointment of the acting regional heads has violated the principles of constitutionalism contained in the 1945 Constitution of the Republic of Indonesia, namely the principle of the rule of law and the principle of a democratic state, the principle of legality, and regional autonomy. It also Failed to fulfill the principle of transparency, openness and accountability as contained in the principles of state administration and good governance. 2. The appointment of of middle high leaders and Pratama high leaders who come from active members of the TNI and POLRI as acting Regional Heads is a violation of Law Number 34 of 2004 concerning the TNI, Law Number 2 of 2002 concerning the Indonesian Police, Law Number 5 of 2014 concerning ASN and the decision of the Constitutional Court Number 15/PUU-XX/2022.
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Sunyoto, Sunyoto, Robinson Situmorang, and Etin Solihatin. "The Importance of Training Need Assessment on Competency-Based Training of Technical Guidance of Energy Auditor in Cement Industry." JETL (Journal of Education, Teaching and Learning) 5, no. 1 (March 31, 2020): 127. http://dx.doi.org/10.26737/jetl.v5i1.1097.
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Training needs assessment or training needs analysis is a move made prior to training and a part in the design of integrated training in order to obtain a comprehensive picture of the material, the allocation of time, and learning strategies that should be applied in conducting Technical Guidance Training of Energy Auditor. In this case, identifying training needs (Training Needs Analysis) is the second step after identify desired result (SKKNI Comply) in the development of a training model Technical Guidance of energy Auditor. Identification of training needs carried out by the training institutions in the cement industry is micro case, namely the identification process to find out the "gap" the competence that is owned by the labor force with the requirements of the position. Program Technical Guidance Training of Energy Auditor prepared based on Standard of Competence Workplace of Indonesia (SKKNI) in the field audits of energy audit as desired field workforce performance which is refer to Human Performace Technology (HPT) model.
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Zhivaeva, Vera V., Vadim A. Nikovaev, Svetlana N. Parfenova, and Elena P. Tuponosova. "Identification of quality problems staff vocational training." Vestnik of Samara State Technical University Psychological and Pedagogical Sciences, no. 3 (October 2020): 55–76. http://dx.doi.org/10.17673/vsgtu-pps.2020.3.4.
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Vocational training (VET) is a very complex and understudiedsystem-object, the functioning of which is the subject to a continuous action of a large number of random (uncertain) factors. The coactions of these factors leads to significant inconsistencies in the development of the training program, reducing its effectiveness in relation to the achievement of learning objectives. The lack of commensurability of the real increase in efficiency with the target settings should be considered, first of all, as a problem of software quality. In connection with the insufficiency of the existing theoretical ideas about the internal properties of the educational process (OP), the problem of control synthesis can be solved by observing its inputs and outputs. Observation of the reaction of output quantities to changes in input influences allows us to construct a posteriori model of the process, i.e. to identify the quality problem in the early stages of its inception. The purpose of this work is to investigate the possibility of ensuring the quality of personnel software by the identification method based on the results of evaluating the input and output signals of the OP as a control object. The methodology of work is based on the concept of integrated quality management (TQM) and the process approach. The main categories of problems of the quality of education are considered and clustered to support the adoption of managerial decisions. The most important features of closed and open problems that need to be considered when making decisions are described. Recommendations were developed on the application of methods of direct and indirect approaches to the identification of quality problems. It has been shown that discussions in cross-functional groups provide, as a rule, the best results in identifying and resolving problems. The value of the study for the theory and practice of software consists in constructing an identification procedure to support the adoption of informed decisions when choosing actions to prevent the development of quality problems. The developed identification procedure can be applied in the software system, providing an acceptable level of satisfaction of the enterprise personnel with the quality of training.
Dissertations / Theses on the topic "TNI (TRAINING NEED IDENTIFICATION)"
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SINGH, GAYATRI. "EFFECTIVENESS AND ASSESSMENT OF TRAINING AND DEVELOPMENT AT HIGH BEAN GLOBAL." Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18499.
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As and environment is changing day to day, it is important for all the organization to progress
in the same direction with its manpower to sustain and succeed.” “An organization’s role in
improving an employee’s performance and” their carrier is fulfilled through proper training
programs.” “For apt trainings, which are to be provided to employees, proper training needs
must be identified so that” training proves to be fruitful and purposeful.”
TNI (Training need identification) system of the organization takes care of such aspects.”
In my research project I have discussed about the TNI system as carried out at Smart Utility
System.” “This report evaluates the effectiveness of TNI system of the Organization carried
out for the employees.”
First section of the project deals with the detailed organization’s profile including the
information about the company- mission, Vision, Corporate philosophy, competitors.
Objectives and the scope of the study is also covered in this section.”
Second section gives an overview of the TNI system and analysis of the effectiveness.” This
section contains the brief conceptional explanation to the system. It contains the definition,
process, TNI process followed by the organization.”
Final section includes the conclusion drawn from the research and recommendations make to
improve upon the system.
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Morin, Elisabeth. "Identification des besoins de formation continue des travailleurs sociaux pouvant intervenir auprès des endeuillés." Thesis, 2020. http://hdl.handle.net/1866/25634.
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Ce mémoire vise à explorer les besoins de formation continue des travailleurs sociaux pouvant intervenir auprès des endeuillés. Il s’agit de mieux comprendre les besoins de formation continue concernant les pertes, le deuil et l’accompagnement des endeuillés. Se situant dans une perspective qualitative exploratoire, six travailleurs sociaux et agents de relations humaines du Centre intégré de la santé et des services sociaux (CISSS) de Lanaudière ont participé à des entrevues semi-dirigées. De plus, une analyse documentaire des formations continues offertes sur le deuil et inscrites au catalogue de l’Ordre des travailleurs sociaux, thérapeutes conjugaux et familiaux du Québec (OTSTCFQ) a été réalisée. Nous avons utilisé un cadre d’analyse intégrateur s’inspirant de plusieurs concepts clés (la formation continue, la motivation, le développement professionnel, le contexte organisationnel, les savoirs) et du modèle d’analyse des besoins de formation ressentis de Labesse (2008) afin d’analyser nos résultats de recherche. Avec une analyse de contenu thématique, ce modèle a permis de mieux comprendre les besoins de formation continue des travailleurs sociaux pouvant intervenir auprès des endeuillés. Cette recherche a aussi permis d’examiner les formations continues actuellement offertes et de déterminer la concordance entre ces dernières et les besoins identifiés par les participants.This thesis aims to explore the continuing training needs of social workers who may intervene with bereaved persons. Its goal is to better understand the continuing education needs regarding loss, mourning and bereavement support. From a qualitative exploratory perspective, six social workers and human relations agents within the Integrated Health and Social Services Centres (IHSSC) of Lanaudière participated in semi-structured interviews. In addition, an in-depth textual analysis of bereavement-related continuing education courses listed within the Order of Social Workers, Marriage and Family Therapists of Quebec (OTSTCFQ) catalogue was carried out. An integrative analytical framework was used, inspired by several key concepts (continuing education, motivation, professional development, organizational context, knowledge) and an analytical model related to perceived training needs (Labesse, 2008) was used to analyze collected data. Through thematic content analysis, this model made it possible to better understand the ongoing training needs of social workers who may provide services for bereaved persons. The research results also allowed us to review the current continuing education training offered and helped determine the degree to which these trainings met the needs identified by participants.
Book chapters on the topic "TNI (TRAINING NEED IDENTIFICATION)"
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Dhal, Sharanika, and Snigdha Mohapatra. "Training Need Identification of Nursing Professional’s Competencies During Pandemic and Scale Development." In Managing Disruptions in Business, 365–90. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-79709-6_19.
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Kenny, Maureen C. "Training in Reporting of Child Maltreatment: Where We Are and Where We Need to Go." In Mandatory Reporting Laws and the Identification of Severe Child Abuse and Neglect, 327–46. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9685-9_16.
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Mkomwa, Saidi, Simon Lugandu, Ngari Macharia, Alexandra Bot, and Weldone Mutai. "Centres of excellence in conservation agriculture: developing African institutions for sustainable agricultural development." In Conservation agriculture in Africa: climate smart agricultural development, 402–15. Wallingford: CABI, 2022. http://dx.doi.org/10.1079/9781789245745.0025.
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Abstract Conservation Agriculture (CA) is an important component in addressing food insecurity, biodiversity degradation and water scarcity challenges. Its adoption in Africa has lagged behind other continents. One major area of need to enable the acceleration of the adoption of CA in Africa relates to building the necessary cross-sectoral institutional and human capacity across the education-research-extension-enterprise axis along the value chain. This study was conducted in order to contribute to the discussions about the need to create sustainable institutions: specifically, Conservation Agriculture Centres of Excellence (CA-CoEs) in Africa. The CA-CoEs model includes a stakeholder team, a shared facility or an entity that provides leadership, best practices, research, support and/or training in CA, with linkages to service providers along the value chain. This literature-based research involved systematic identification, collection, analysis and documentation of data to identify and address the unique roles these CA-CoEs play in the promotion and adoption of CA and their level of performance. It employed a CA quality assurance self-assessment tool to measure the performance of the CA-CoEs against predetermined performance descriptors. Although the CA-CoEs are facilitating and catalysing adoption of CA, their capacity in providing the CA-related programmes, training and research is not optimal. CA-CoE quality assurance of services can be helpful in identification and design of measures for addressing the challenges faced. To be impactful, CA-CoEs need well-coordinated, participatory and demand-driven CA-based agricultural practices, information services and knowledge for farmers and other stakeholders such as non-governmental organizations (NGOs), CA service providers and CA equipment manufacturers.
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Shan, Yao. "Sources Identification of Water Inrush in Coal Mines Using Technique of Multiple Non-Linear Machine Learning Modelling." In Groundwater [Working Title]. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94288.
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Water inrush is a major threat to the working safety for coal mines in the Northern China coal district. The inrush pattern, threaten level, and also the geochemical characteristics varies according to the different of water sources. Therefore, identifying the water source correctly is an important task to predict and control the water inrush accidents. In this chapter, the algorithms and attempts to identify the water inrush sources, especially in the Northern China coal mine district, are reviewed. The geochemical and machine learning algorithms are two main methods to identify the water inrush sources. Four main steps need to apply, namely data processing, feature selection, model training, and evaluation, in the process of machine learning (ML) modelling. According to a calculation instance, most of the major ions, and some trace elements, such as Ti, Sr, and Zn, were identified to be important in light of geochemical analysis and machine learning modelling. The ML algorithms, such as random forest (RF), support vector machine (SVM), Logistica regression (LR) perform well in the source identification of coal mine water inrush.
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Hawrylak, Peter J., and Chris Hart. "Using Radio Frequency Identification Technology to Store Patients' Medical Information." In Healthcare Ethics and Training, 641–61. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2237-9.ch029.
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Radio Frequency Identification (RFID) technology enables wireless communication between a RFID reader and a RFID tag. One type, passive RFID tags, need no battery, being powered from the RFID reader's radio frequency signal. Passive RFID tags can support memories that can be used to store portions of the patient's medical history. One form factor for passive RFID tags is an employee ID (used for wireless access) or credit card form factor. This form factor allows the patient to carry their medical information with them. RFID benefits include providing information to Emergency Medical Technicians (EMTs), maintaining a patient's vaccination history and providing emergency contact information, all in a clear and unmistakable format. This simplifies information exchange during patient transfers, a cause of many preventable medical mistakes and errors. Cheap and simple systems, such as the one presented in this chapter, can reduce stress and prevent possible errors. Such systems with an intuitive human-machine interface can reduce the duration of a patient visit throughput. This system can prevent simple errors such as the administration of the wrong drug, dose, or drug omission, which is a major issue in hospitals. This requires that information be stored in a standardised manner, with limited healthcare provider access and use to protect patient privacy. This chapter explores the use of passive RFID tags to store medical information about a patient, with specific focus on storage of a child's vaccination history and safety.
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González Martínez, Rocío, Martha Ríos-Manríquez, and Ana Laura Arteaga Cervantes. "The Entrepreneurial Intention in University Level Students." In Global Considerations in Entrepreneurship Education and Training, 128–50. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7675-4.ch008.
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Universities impact in the entrepreneurship ecosystem, they emanate a large number of talents, using their resources to support entrepreneurship. From this situation, arrives the importance of generating and validating measurement instruments to contribute to the identification of level of entrepreneurial intention with which students, of higher education level, have. The Exploratory Factor Analysis technique, uses the Varimax Orthogonal Rotation method, with principal component extraction factors, with a sample of 235 students in public universities of the state of Guanajuato in Mexico, considering 6 dimensions as variables. The results of this research consider as relevant only 3 dimensions from the 6 studied, considering that the entrepreneurial intention in the higher education student is a product of creativity, innovation and need for achievement. While the three dimensions: self-esteem, assumption of risk and problem solving, does not reach a relevant importance; showing a robust instrument for the Mexican context.
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Pearson, Stephen Robert, and Mahmoud Shafik. "Research into Early Stage Identification of Entrepreneurs: Educational Tools Using Virtual and Augmented Reality." In Advances in Transdisciplinary Engineering. IOS Press, 2022. http://dx.doi.org/10.3233/atde220606.
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One of the big challenges facing youth over all the world is unemployment. There are many reasons that unemployment exists specially within this community. It is mainly due to lack of jobs, knowledge, professional skills, and inability of the youth to recognise their potential as entrepreneurs. This is off course impact on national economy and there is a need to help this community to identify their individual potential at early stage and develop the necessary educational and training tools that can help them to overcome such unemployment challenge. This ongoing research programme is mainly focused on researching into early-stage identification of young entrepreneurs and aiming to develop the tools that can support them in short and long development. This paper presents the initial outcomes of whether virtual reality and augmented reality tools can offer advanced educational and training tools, better suited to entrepreneurs than conventional classroom-based training. It is important to mention that key part of this research programme is also focused on integrating Artificial Intelligences tools. This is to enhance the tools learning experience and meet individual needs. The outcomes of this studies are reported in the other paper published in this conference.
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Syed, Mahanazuddin, Shaymaa Al-Shukri, Shorabuddin Syed, Kevin Sexton, Melody L. Greer, Meredith Zozus, Sudeepa Bhattacharyya, and Fred Prior. "DeIDNER Corpus: Annotation of Clinical Discharge Summary Notes for Named Entity Recognition Using BRAT Tool." In Studies in Health Technology and Informatics. IOS Press, 2021. http://dx.doi.org/10.3233/shti210195.
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Named Entity Recognition (NER) aims to identify and classify entities into predefined categories is a critical pre-processing task in Natural Language Processing (NLP) pipeline. Readily available off-the-shelf NER algorithms or programs are trained on a general corpus and often need to be retrained when applied on a different domain. The end model’s performance depends on the quality of named entities generated by these NER models used in the NLP task. To improve NER model accuracy, researchers build domain-specific corpora for both model training and evaluation. However, in the clinical domain, there is a dearth of training data because of privacy reasons, forcing many studies to use NER models that are trained in the non-clinical domain to generate NER feature-set. Thus, influencing the performance of the downstream NLP tasks like information extraction and de-identification. In this paper, our objective is to create a high quality annotated clinical corpus for training NER models that can be easily generalizable and can be used in a downstream de-identification task to generate named entities feature-set.
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Xu, Jia-Heng, Lian-Song Yu, Wei-Wei Yang, Xiao Rong, Wei Luo, Na Song, and Hua-Feng Hu. "Intelligent Judgment Method of Superimposed Label Recognition Technology Based on a Deep Learning Target Detection Algorithm for Detecting Wiring Errors in Current Transformer Tests." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2022. http://dx.doi.org/10.3233/faia220561.
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This paper presents a novel method of intelligent detection of transformer wiring tests. It combines a new deep learning-based object detection algorithm with a tag code identification technique. Complex wiring in the current transformer error test scenarios implies a need for frequent human testing and judgment by digitizing the equipment terminals and the connected wires in the test. The automatic identification of the test connection lines is realized, relying on learning from the standard wiring and logically binding the standard wiring relationship. The proposed method is instrumental in greatly saving labor costs, reducing the possibility of human error, improving work efficiency, and developing a new concept of current transformer error test training for new employees.
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Iino, Atsushi, and Brian Wistner. "Effects of repeating after stimuli sounds during computer assisted HVPT on Japanese learners’ perception and production of English fricatives." In CALL and professionalisation: short papers from EUROCALL 2021, 149–54. Research-publishing.net, 2021. http://dx.doi.org/10.14705/rpnet.2021.54.1324.
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This study investigated the effects of using an online High Variability Phonetic Training (HVPT) program for university students whose first language is Japanese and who studied English as a foreign language. The target sounds were English fricatives, which many of the participants felt were challenging to distinguish and articulate. The training was conducted for five weeks; each week consisted of three HVPT sessions. The training process consisted of an initial explanation of how to articulate the sounds followed by a video that showed the physical articulative movements. The participants listened to stimuli sounds, produced the sounds after each stimulus, and completed an identification task. Based on pre and posttests, the perception performance of the participants improved significantly through the HVPT training. Regarding production, a positive effect was found for one phoneme, while no difference was found for the other. Questionnaire results were generally positive but indicated the need for explicit instruction for some of the fricatives that exhibited relatively lower successful production and perception rates.
Conference papers on the topic "TNI (TRAINING NEED IDENTIFICATION)"
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Lakshmi, Pulla, G. Mythili, and Santosh Panda. "A Comparative Study on Training/Professional Development Needs of University Teachers on ODL Pre-Covid and Ongoing Pandemic in India." In Tenth Pan-Commonwealth Forum on Open Learning. Commonwealth of Learning, 2022. http://dx.doi.org/10.56059/pcf10.8780.
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Education is of utmost importance for social development and political change, regardless of whether it is dispensed through conventional, non-conventional or ODL mode. The Indian ODL system, geared toward this philosophy, is the second largest ODL system in the world, comprising 17 open universities and 110+ dual-mode distance education institutions. The Staff Training and Research Institute of Distance Education (STRIDE) of the Indira Gandhi National Open University (IGNOU) undertakes training needs assessment (TNA) studies from time to time for addressing the training needs of the ODL faculty in the country, (besides offering a PG Diploma and a Masters in DE as long-term professional development programmes, which at one point of time was offered in about 22 countries, largely supported by the Commonwealth of Learning). Recently, the Covid-19 pandemic forced the education sector to adopt changes in teaching-learning. Even though the adaptation of technologies started in the field of education prior to the pandemic, the educational institutions including ODL institutions had to go through compulsory remote online teaching during this period. It was thought prudent to undertake a TNA of ODL teachers during this pandemic and compare the variations in their training needs, which was conducted in pre-pandemic times. This paper reports the findings of a research focusing on the identification of training needs of teachers/ academics from IGNOU; their preferences on mode of training; and any difference in additional required competency during pre- and ongoing-pandemic. The data collected in January-February 2022 has been compared with the data collected in the pre-pandemic period of 2019, and implications for policy and practice on continuing professional development in ODL are drawn accordingly.
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Cojocariu, Venera-Mihaela. "Comparative Study On The Identification Of Teachers' Need For Inclusive Education Training." In Edu World 7th International Conference. Cognitive-crcs, 2017. http://dx.doi.org/10.15405/epsbs.2017.05.02.80.
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Jain, A., R. P. P. Rane, Y. Sweedan, and S. Z. Ayaz. "Bedside Echocardiographic Identification of Pericardial Tamponade: A Case Highlighting the Need For Enhanced Pocus Training For Residents in Intensive Care Units." In American Thoracic Society 2023 International Conference, May 19-24, 2023 - Washington, DC. American Thoracic Society, 2023. http://dx.doi.org/10.1164/ajrccm-conference.2023.207.1_meetingabstracts.a6694.
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Frasineanu, Ecaterina sarah. "IDENTIFICATION OF THE SPECIFIC OF LEARNING WITHIN A DOMAIN - AS A SOLUTION TO IMPROVE ACADEMIC TRAINING." In eLSE 2014. Editura Universitatii Nationale de Aparare "Carol I", 2014. http://dx.doi.org/10.12753/2066-026x-14-170.
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Article includes both, summaries of our experiences in the learning guidance to students who prepare themselves to be teachers and survey results, of the stimulation of self-reflexive analysis of the students, we currently work with. In the academic training is important to be noticed, but, especially, to resolve the situation in which students find themselves sometimes, that not to meet the demands of learning, to feel overwhelmed, because what is required is new, too much too difficult. In this case, to identify the specific of the approach of the study field is a solution that includes the application of a methodology of intellectual work, self-management, meta-cognition, learning motivation, adapting the style to requirements. From the perspective of a teacher who guides the students learning in psycho-pedagogical domain, we consider to be absolutely necessary building of the implementing and knowledge transfer capacities. Learning Pedagogy follows its specificity as a science focused on building diverse correlations between knowledge and skills made in psycho-pedagogy domain and the items of general or specialized culture. From the perspective of students, it is interesting that they are proposing a productive approach, not one reproductive of the area and the fact that they understand the need to learn in a generative manner, with continued restructuring experience. In fact, in any new area it is useful to identify not only different contents, but rather, the goals and methodologies of that science. The psycho-pedagogical training of students learning goals correlate with professional achievement, and the elements needed to achieve competencies in this category involve perseverance in learning.
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Zhao, Zihan, Wenzhe tang, Linlin Li, and ChengQi Xue. "Effects of Users’ Familiarity in Icons on the Cognitive Performance of Icon Identification." In Intelligent Human Systems Integration (IHSI 2023) Integrating People and Intelligent Systems. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1002920.
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This study investigated the effects of icon familiarity on visual search task and semantic information recall. First, participants need to search for target icons among 10 unfamiliar icons. The familiarity of the ten target icons is different, which is determined by the number of occurrences in the training stage. In the training stage, subjects are familiar with the ten icons and their semantics, and the number of occurrences of each icon is random. After the visual search task, participants first memorize the semantic information of the icon, and then recall the semantic information of the corresponding icon. The results showed that in the visual search task, the participants' response time was faster when the icons were more familiar.
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BUD, MIHAI ADRIAN, MIHAI NEDELCU, IONUT MOLDOVAN, and ELOI FIGUEIREDO. "HYBRID SUPERVISED MACHINE LEARNING APPROACH FOR DAMAGE IDENTIFICATION IN BRIDGES." In Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36294.
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Structural health monitoring (SHM) of bridges often involves machine learning algorithms, trained based on two independent learning strategies, namely unsupervised and supervised learning, depending on the type of training data available. When unsupervised learning strategy is employed, the algorithms are normally trained with data gathered from monitoring systems, corresponding to normal operational and environmental conditions. The lack of information regarding the dynamic response of the structure under extreme environmental and operational conditions, as well as under damage scenarios, may lead to flaws in the damage detection process, namely the rise of false indications of damage. In order to overcome this drawback, finite element models can be used as structural proxies to generate data that correspond to scenarios unlikely to be recorded by the monitoring systems, such as extreme temperatures or structural damage. The use of both monitoring and numerical data in the framework of a hybrid approach greatly improves the quality of the training process, as recently shown by the authors. The hybrid approach also enables the use of the supervised learning strategy if numerical data corresponding to damage scenarios are available. Therefore, this paper assesses the reliability of a hybrid approach for the supervised training of machine learning algorithms using numerical data corresponding to extreme temperatures and several damage scenarios. The damage scenarios comprise various degrees of settlement of a bridge pier and a landslide near the same pier. Monitoring data are used for the testing of the algorithms and for the initial calibration of the finite element model, which does not need to be exceedingly detailed, as the probabilistic variation of the uncertain parameters is taken into account. The procedure was applied to the Z-24 Bridge, a well-known benchmark consisting of one year of continuous monitoring and including progressive damage readings.
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Ziakkas, Dimitrios, Debra Henneberry, and Abner Del Cid Flores. "Competency-Based Training and Assessment (CBTA) Framework in Global Aviation Training." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003728.
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One of the most important components of workforce planning in Human Resources Management (HRM) is ensuring that employees have the right skills and competences to do their jobs. The expansion of low-cost and traditional carriers has enhanced the reach, breadth, and frequency of traditional passenger-carrying services. Due to the growing need for highly trained professionals in Intelligence Human Systems, airline recruiters are under pressure to find new ways to attract and communicate with potential candidates. This study intends to include CBTA into aviation personnel planning, training, and management of the Intelligence Human Systems Integration - transformation. Research objectives include a theoretical study of the CBTA framework, an examination of human resources planning, training, and operations, identification of aviation Subject Matter Experts performance gaps, and a recommendation for adopting the CBTA framework in aviation human resources framework and Intelligence Human Systems Integration. When building the worldwide CBTA framework for the aviation industry, the authors studied the governing variables and trends in the industry, suggesting a global strategy to managing HSI-change.The pandemic's effects were addressed when implementing CBTA. According to a recent research, aviation programs should stimulate learning beyond the ab initio basic knowledge requirements, give chances for ongoing education, and stress quality over quantity (e.g., developing pilot hours, integrating new technology) (AI). Organizational culture, opposition to technological progress, and employment laws affect demand. In the following study, a synthesis of the Lean Six Sigma (L6) strategy and CBTA framework is offered as an alternative to the prevailing method in many countries, which inhibits change management and increases organizational pressure. Implementing verified CBTA – EBT / psychological applications during installation and change management can help airlines become an employer of choice in the sector and speed up intelligence human systems integration."Competency" is a human performance attribute used in aviation to predict job success. When a person engages in behaviors that draw on the proper knowledge, abilities, and attitudes to complete activities or tasks within set parameters, they demonstrate and demonstrate a competency. Research follows ICAO's description of knowledge, abilities, and attitude (ICAO, 2022):• "Knowledge is particular information needed to acquire and apply skills and attitudes needed to recall facts, recognize concepts, apply rules or principles, solve issues, and think creatively at work,"• "Knowledge is particular information needed to acquire and apply skills and attitudes to recall facts, recognize concepts, and apply rules or principles (ICAO, 2022)." Attitude is a learned mental state or disposition that determines a person's conduct toward any item, person, or event. Positive or negative attitudes can evolve. Attitudes are affective, cognitive, and behavioral. Aviation SME must "know how to be" in each circumstance to have the "right" attitude.Purdue's professional flying program acknowledged both technical and nontechnical competencies based on IATA requirements. Furthermore, Purdue research employed qualitative and quantitative methods to confirm the idea that combining Competency-Based Training Assessment with a structured recruitment and selection plan increases organizational performance.The chosen inductive research method focuses on reducing delays in pilot hiring and training by incorporating personnel capabilities that reduce performance differences. The study also examines how Lean Six Sigma personnel planning and training effect airline operating expenses. Removing superfluous processes from the recruitment process can help airlines save money and time on recruitment and employee training. Purdue Research roadmap focuses on AI certification (FAA, EASA), AI training following a change management approach, and AI standards in the worldwide AI aviation ecosystem. In conclusion, the outcomes of this study project indicate that the firm must rethink its organizational culture, adopt an integrated CBTA approach, and use the proposed Lean Six Sigma Recruitment process.
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Moldoveanu, Alin, Oana Balan, and Florica Moldoveanu. "TRAINING SYSTEM FOR IMPROVING SPATIAL SOUND LOCALIZATION." In eLSE 2014. Editura Universitatii Nationale de Aparare "Carol I", 2014. http://dx.doi.org/10.12753/2066-026x-14-011.
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This paper presents a new training system for 3D audio space localization, part of a more complex project, Sound of Vision, which is intended to be an object recognition and navigation aid system for visually-impaired people. As a large number of people are suffering from a visual handicap which impedes them from normally accomplishing their daily chores, there is need for an assistive device that replaces sight with another sense, for instance, hearing. The most important aspect in the sound localization techniques is the human capacity to discriminate between different sounds playing at various locations in space. The aim of the presented audio system is to train and test the subjects' space localization ability, hence to develop and improve their 3D recognition skills. The solution uses binaural sounds conveyed through headphones as basic blocks, applying HRTFs to various sounds (Head Related Transfer Function - a physical propagation characteristic that describes how the ear perceives the sound coming from a particular point in space). The acoustic signals represent short (e.g. 20ms long) white and pink noise sounds, externalized with non-individualized HRTFs recorded in dedicated lab environments. Thus, from a monaural noise sound, through the process of mathematical convolution with the corresponding angular HRTF impulse for both the left and right channels, we obtained a 3D binaural sound which is perceived as coming from the particular direction specified by the angular value of the convoluted HRTF. The program is composed of a training module, where the user moves the mouse cursor inside a circle and hears a continuous binaural sound that corresponds to the azimuth angle indicated on the circle- ranging from 0 to 355 degrees, and a test module- where the subject is presented 10 different sounds that correspond to 10 different locations, being required to point out on the circle the presumed emitting location of the sound, as he perceives it. Through learning and training, the users (both normal-sighted and visually impaired subjects) performed various auditory tasks- identification, recognition, discrimination- and improved their sound localization capacity. This paper gives on overview of 3 aspects: the technical realization of the system, the experimental results with a set of training subjects and the advanced observations about sound localization that we made.
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Wiyoga, Sonny Ari, Jhonny Xu, Aulia Desiani Carolina, and Ratna Dewanda. "Application of Class-Based Machine Learning for Potential Hydrocarbon Zones Identification: A Case Study." In SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205617-ms.
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Abstract At times, petrophysicists are expected to evaluate potential of the well in time-constraint situations while maintaining consistency of the parameters and interpretation. Other than that, some challenges may also occur when working with older wells where the dataset are not as complete as current wells and processing parameters are not transferable. In this case study, class-based machine learning (CBML) approach is used to perform petrophysical evaluation to identify potential hydrocarbon zones in the target wells. The objective is to find solution to improve efficiency and consistency in those challenging situations. A class-based machine learning (CBML) workflow uses cross-entropy clustering (CEC)-Gaussian mixture model (GMM)- hidden Markov model (HMM) workflow that identifies locally stationary zones sharing similar statistical properties in logs, and then propagates zonation information from training wells to other wells (Jain, et al., 2019). The workflow is divided into two (2) main steps: training and prediction. Key wells which best represent the formation in the field are used to train the model. This approach automatically generates the number of cluster (class) using unsupervised or supervised depending on the input data. The model from key wells data is then used to reconstruct inputs and outputs along with uncertainty and outlier flags. This allows expert to QC and validate the generated class which is the most crucial part of the workflow. Once the model from the key wells has been built, it is applied to predict the same set of zones in the new wells that require interpretation and predict output curves. The result matched well over the good data interval with the petrophysical interpretation result from conventional approach. While in the bad interval, some discrepancies can be observed. The discrepancy was identified easily from the uncertainty and outlier flags which helps petrophysicists to identify which interval to fix or re-evaluate. Some requirements to condition the input were observed (no missing value over the input and outlier) to get the best result. A number of inputs used in the model need to be consistent over the set of wells used in the training and prediction target. This machine learning workflow speeds-up the petrophysical analysis process, reduce analyst bias and improve consistency result between one well to another within the same field. This machine learning application can also generate auto log QC, zonation class for rock typing also reconstructed logs which enrich the petrophysical interpretation even for wells with limited logs availability. This paper offers practical examples and lessons learned of CBML approach application to perform petrophysical evaluation and identify potential zones while being in time-constrained and limited resource situations.
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Constantin, Nica, and Tiberiu Tanase. "USING ARTIFICIAL INTELLIGENCE IN AUGMENTED ENVIRONMENTS FOR COMPLEX TRAINING SCENARIOS IN THE DEFENCE INDUSTRY." In eLSE 2018. Carol I National Defence University Publishing House, 2018. http://dx.doi.org/10.12753/2066-026x-18-079.
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Classical training scenarios in exercises and practices in the defense industry, focus on realism, where complex scenarios are simulated to achieve maximum impact on unit training. Thousands of hours are being spent to train units and provide real-life scenarios, to improve on survivability and efficiency of units, if and when the time comes, for proven organizational and practical efficiency. Using Augmented Reality and Artificial Intelligence to create real-life simulated environments would create a totally new learning platform, which provides a new learning experience and approach, for specialized situations in the defense industry. Many other solutions have tried to provide for interactive content, without achieving the much needed interaction between subjects participating in training courses, where complex environmental relations need to be analyzed. Artificial Intelligence algorithms may help identify patterns and may be trained to provide for specific input on human interaction. The Augmented Reality environment may provide for the much needed interaction and practices that are normally required for real-life situations. Combining both elements into a single eLearning platform, may provide for a totally new paradigm in the training of military and intelligence units, by reducing costs on an already expansive military budget, providing a safer training environment and ultimately improving the available methods of training for a special domain. The present work makes an analysis of available technology, software and hardware, to provide for such a scenario where Artificial Intelligence and Augmented Reality is united to create a new e-learning concept. A functional architecture will be presented, with the identification of the most probable already existing technologies that could be used to reach a proof-of-concept solution.
Reports on the topic "TNI (TRAINING NEED IDENTIFICATION)"
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Gurung, M. B., Uma Pratap, N. C. T. D. Shrestha, H. K. Sharma, N. Islam, and N. B. Tamang. Beekeeping Training for Farmers in Afghanistan: Resource Manual for Trainers [in Urdu]. International Centre for Integrated Mountain Development (ICIMOD), 2012. http://dx.doi.org/10.53055/icimod.564.
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Beekeeping contributes to rural development by supporting agricultural production through pollination and by providing honey, wax, and other products for home use and sale. It offers a good way for resource-poor farmers in the Hindu Kush Himalayas to obtain income, as it requires only a small start-up investment, can be carried out in a small space close to the home, and generally yields profits within a year of operation. A modern approach to bee management, using frame hives and focusing on high quality, will help farmers benefit most fully from beekeeping. This manual is designed to help provide beekeepers with the up-to-date training they need. It presents an inclusive curriculum developed through ICIMOD’s work with partner organizations in Bangladesh, Bhutan, India, and Nepal, supported by the Austrian Development Agency. A wide range of stakeholders – trainers, trainees, government and non-governmental organizations (NGOs), associations and federations, and private entrepreneurs – were engaged in the identification of curriculum needs and in development and testing of the curriculum. The manual covers the full range of beekeeping-related topics, including the use of bees for crop pollination; production of honey, wax and other hive products; honey quality standards; and using value chain and market management to increase beekeepers’ benefits. It also includes emerging issues and innovations regarding such subjects as indigenous honeybees, gender and equity, integrated pest management, and bee-related policy. The focus is on participatory hands-on training, with clear explanations in simple language and many illustrations. The manual provides a basic resource for trainers and field extension workers in government and NGOs, universities, vocational training institutes, and private sector organizations, and for local trainers in beekeeping groups, beekeeping resource centres, cooperatives, and associations, for use in training Himalayan farmers. Individual ICIMOD regional member countries are planning local language editions adapted for their countries’ specific conditions.
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Hlushak, Oksana M., Svetlana O. Semenyaka, Volodymyr V. Proshkin, Stanislav V. Sapozhnykov, and Oksana S. Lytvyn. The usage of digital technologies in the university training of future bachelors (having been based on the data of mathematical subjects). [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3860.
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This article demonstrates that mathematics in the system of higher education has outgrown the status of the general education subject and should become an integral part of the professional training of future bachelors, including economists, on the basis of intersubject connection with special subjects. Such aspects as the importance of improving the scientific and methodological support of mathematical training of students by means of digital technologies are revealed. It is specified that in order to implement the task of qualified training of students learning econometrics and economic and mathematical modeling, it is necessary to use digital technologies in two directions: for the organization of electronic educational space and in the process of solving applied problems at the junction of the branches of economics and mathematics. The advantages of using e-learning courses in the educational process are presented (such as providing individualization of the educational process in accordance with the needs, characteristics and capabilities of students; improving the quality and efficiency of the educational process; ensuring systematic monitoring of the educational quality). The unified structures of “Econometrics”, “Economic and mathematical modeling” based on the Moodle platform are the following ones. The article presents the results of the pedagogical experiment on the attitude of students to the use of e-learning course (ELC) in the educational process of Borys Grinchenko Kyiv University and Alfred Nobel University (Dnipro city). We found that the following metrics need improvement: availability of time-appropriate mathematical materials; individual approach in training; students’ self-expression and the development of their creativity in the e-learning process. The following opportunities are brought to light the possibilities of digital technologies for the construction and research of econometric models (based on the problem of dependence of the level of the Ukrainian population employment). Various stages of building and testing of the econometric model are characterized: identification of variables, specification of the model, parameterization and verification of the statistical significance of the obtained results.
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, July 1996. http://dx.doi.org/10.32747/1996.7613033.bard.
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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detection, refractometer and a scale (mass). Data were analyzed and provided input for five classification models. Chlorophyll from fluorescence was found to give the best estimation for ripeness stage while the combination of machine vision and firmness from impact performed best for quality sorting. A new algorithm was developed to estimate and minimize training size for supervised classification. A new criteria was established to choose a training set such that a recurrent auto-associative memory neural network is stabilized. Moreover, this method provides for rapid and accurate updating of the classifier over growing seasons, production environments and cultivars. Different classification approaches (parametric and non-parametric) for grading were examined. Statistical methods were found to be as accurate as neural networks in grading. Classification models by voting did not enhance the classification significantly. A hybrid model that incorporated heuristic rules and either a numerical classifier or neural network was found to be superior in classification accuracy with half the required processing of solely the numerical classifier or neural network. In Israel: A multi-sensing approach utilizing non-destructive sensors was developed. Shape, color, stem identification, surface defects and bruises were measured using a color image processing system. Flavor parameters (sugar, acidity, volatiles) and ripeness were measured using a near-infrared system and an electronic sniffer. Mechanical properties were measured using three sensors: drop impact, resonance frequency and cyclic deformation. Classification algorithms for quality sorting of fruit based on multi-sensory data were developed and implemented. The algorithms included a dynamic artificial neural network, a back propagation neural network and multiple linear regression. Results indicated that classification based on multiple sensors may be applied in real-time sorting and can improve overall classification. Advanced image processing algorithms were developed for shape determination, bruise and stem identification and general color and color homogeneity. An unsupervised method was developed to extract necessary vision features. The primary advantage of the algorithms developed is their ability to learn to determine the visual quality of almost any fruit or vegetable with no need for specific modification and no a-priori knowledge. Moreover, since there is no assumption as to the type of blemish to be characterized, the algorithm is capable of distinguishing between stems and bruises. This enables sorting of fruit without knowing the fruits' orientation. A new algorithm for on-line clustering of data was developed. The algorithm's adaptability is designed to overcome some of the difficulties encountered when incrementally clustering sparse data and preserves information even with memory constraints. Large quantities of data (many images) of high dimensionality (due to multiple sensors) and new information arriving incrementally (a function of the temporal dynamics of any natural process) can now be processed. Furhermore, since the learning is done on-line, it can be implemented in real-time. The methodology developed was tested to determine external quality of tomatoes based on visual information. An improved model for color sorting which is stable and does not require recalibration for each season was developed for color determination. Excellent classification results were obtained for both color and firmness classification. Results indicted that maturity classification can be obtained using a drop-impact and a vision sensor in order to predict the storability and marketing of harvested fruits. In conclusion: We have been able to define quantitatively the critical parameters in the quality sorting and grading of both fresh market cantaloupes and tomatoes. We have been able to accomplish this using nondestructive measurements and in a manner consistent with expert human grading and in accordance with market acceptance. This research constructed and used large databases of both commodities, for comparative evaluation and optimization of expert system, statistical and/or neural network models. The models developed in this research were successfully tested, and should be applicable to a wide range of other fruits and vegetables. These findings are valuable for the development of on-line grading and sorting of agricultural produce through the incorporation of multiple measurement inputs that rapidly define quality in an automated manner, and in a manner consistent with the human graders and inspectors.
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Yusrina, Asri, Emilie Berkhout, Daniel Suryadarma, and Luhur Bima. Can the Teacher Professional Education Admission Criteria in Indonesia Predict Teacher Performance? Research on Improving Systems of Education (RISE), March 2023. http://dx.doi.org/10.35489/bsg-rise-ri_2023/055.
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Studies find that effective teachers raise student test achievement and lead to higher future earnings for the students (Chetty et.al, 2014; Hanushek, 2011). Teacher selection and the criteria used in making the selection are important because they aim to identify such effective teachers. Identifying teachers with such potential is relatively more cost-effective than other policies applied after the teachers have teaching jobs (Klassen and Kim, 2019; Hobson et al., 2010). Many studies focus on selecting teachers based on the information collected at the time of hire to predict student outcomes (Jacob et al., 2018; Hill et al., 2012; Staiger and Rockoff, 2010). Other studies identify potentially effective teachers even before they become teachers. Those studies use information from teacher education programme admission criteria to predict teacher candidates’ success in the programme (Heinz, 2013; Casey and Child, 2011; Caskey et al., 2001). Among teacher selection criteria, studies identified predictors of subsequent performance including undergraduate grades, written tests, interviews, and teaching practice. In developing countries, studies on teacher selection are virtually non-existent. We found two studies that focus on the selection of teachers during hiring. Both use candidates’ screening tests results to predict student learning outcomes (Araujo et al., 2020; Cruz-Aguayo et al., 2017). However, we did not find studies in developing country contexts that focus on selection of teachers into education programmes or how the admission criteria relate to student learning outcomes. Whether focusing on selecting teachers during their education programme or as they go through the recruitment process, studies on teacher selection across countries have the same underlying question: Will the criteria be able to identify effective teachers? The idea of teacher selection to improve the quality of the teaching force is appealing. For instance, in high performing countries in PISA, like Japan and Korea, where there are many teacher colleges (Ingersoll, 2007) and the most prevalent teacher employment is civil-service, great attention is paid to the quality of selection into teacher education programmes (OECD, 2018). Teacher selection is arguably more critical in developing countries. In most developing countries, the entry into teacher education programmes lacks selectivity and teacher qualifications tend to be set lower compared to other professional jobs (Béteille and Evans, 2019). Across all developing countries, a larger number of teachers are employed and account for most of the education spending, but their effect on student outcomes is small (ADB, 2021; Crawfurd and Pugatch, 2021). This suggests the need for more attention to policies such as the selection of teachers and criteria used to identify those best suited to teach in the classroom. In Indonesia, where the teacher recruitment system lacks a strong mechanism to ensure quality (Huang et al., 2020) and the teacher in-service training has not been effective (Revina et al., 2020), a potential way to improve the pool of teachers is through enhanced selection of individuals who will become teachers. We specifically question whether we can predict a teacher’s performance using information available when they were a teacher candidate. Admission criteria for teacher education are presumably intended to identify candidates who have the greatest likelihood of being able to do well in the academic programme and ultimately in the classroom as a professional. The identification of criteria that predict teacher subsequent performance would give policy makers a stronger understanding of where programme improvement may be needed.
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Theory of change: Bet You Can Help. Addiction Recovery Agency, Beacon Counselling Trust, June 2021. http://dx.doi.org/10.33684/2021.004.
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Gambling-related harms are a significant public health issue in Great Britain. These harms are often underrecognized and most people who experience harms go without support. Under the leadership of Addiction recovery Agency (Ara) and Beacon Counselling Trust (BCT), the Bet You Can Help (BYCH) programme is filling the need for place-based education and training to identify and address gambling related harms. The BYCH programme is a community first aid model for safer gambling that promotes the early identification of people who are at risk of gambling related harms. Offered as a Level 2 Qualification through the Royal Society of Public Health, this programme aims to reduce harms and prevent lives being lost from gambling related harms in Great Britain. This theory of change considers the inputs, activities, outputs, and outcomes necessary to achieve these goals. It can be used by organizations, groups, and individuals in any sector impacted by gambling related harms in Great Britain.