• Current Optics and Photonics
• /
• v.6 no.4
• /
• pp.392-399
• /
• 2022

Light-measuring devices (LMDs) are frequently used to measure luminance and color coordinates of displays. However, it is very difficult to use a conventional LMD for measuring the optical properties of virtual-reality (VR) devices with a wide field of view (FOV), because of their confined spaces where the entrance pupil of a LMD is located. In this paper, a new LMD that can measure the optical properties of wide-FOV VR devices, without physical conflict with the goggles of the VR device, is proposed. The LMD is designed to fully satisfy the requirements of IEC 63145-20-10, and a pivot-point correction method for the LMD is applied to improve its accuracy. To show the feasibility of the developed LMD and the correction method, seven VR devices with wide FOV are measured with it. From the results, all of them are successfully measured without any physical conflict, and a comparison to their nominal values shows that the FOVs have been properly measured.

• Journal of Information Technology Applications and Management
• /
• v.31 no.3
• /
• pp.149-163
• /
• 2024

As conversational AI systems such as ChatGPT have become more advanced, researchers are exploring ways to use them in education. However, we need effective ways to evaluate these systems before allowing them to help teach students. This study proposes a detailed framework for testing conversational AI across three important criteria as follow. First, specialized benchmarks that measure skills include giving clear explanations, adapting to context during long dialogues, and maintaining a consistent teaching personality. Second, adaptive standards check whether the systems meet the ethical requirements of privacy, fairness, and transparency. These standards are regularly updated to match societal expectations. Lastly, evaluations were conducted from three perspectives: technical accuracy on test datasets, performance during simulations with groups of virtual students, and feedback from real students and teachers using the system. This framework provides a robust methodology for identifying strengths and weaknesses of conversational AI before its deployment in schools. It emphasizes assessments tailored to the critical qualities of dialogic intelligence, user-centric metrics capturing real-world impact, and ethical alignment through participatory design. Responsible innovation by AI assistants requires evidence that they can enhance accessible, engaging, and personalized education without disrupting teaching effectiveness or student agency.

• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.686_687
• /
• 2009

The traceability maintenance system for the AC voltage and current has been developed at the frequency range of 20 Hz to 100 Hz without using any compensation technique which is used at thermal converter (TC) ac-dc transfer system at low frequencies. The system uses a digital voltmeter (DVM) as a data acquisition system of the input waveform and stored data in memory. The developed algorithm acquires and processes the sampling data to calculate the root mean square (rms) value of the input voltage of DVM which operates at DC 10 V range for better accuracy. The best uncertainty of the AC voltage measurements is $3 {\mu}V/V$ within the frequency range. The best uncertainty of the AC current measurements is better than the $5 {\mu}A/A$ and mainly depend on the current to voltage converter, ac-dc current shunt or Current Transformer (CT), used for the measurement

• School Mathematics
• /
• v.3 no.2
• /
• pp.325-354
• /
• 2001

The study aims to develop balanced performance assessment tasks for primary school mathematics which can be implemented in the primary school easily. In order to these purposes, I suggest the types of performance assessment tasks and the framework of assessment standards for the balanced performance assessment with describing the procedures of developing tasks and rubrics. The types of task are journal writing, problem posing, constructed task, and descriptive task. In the framework of assessment standards, I suggest holistic scoring which are classified as four levels according to the degree of excellence which students perform totally concerning about the criterion of implication, reasoning, accuracy, and communication. Also I analyse the responses of children to the task “make a beautiful pattern” and suggest its assessment rubric and anchor papers for each level for illustrating the process of developing a rubric in holistic scoring. In order to reflect the viewpoints of children and their Parents concerning about the tasks, the responses in self assessment and parent assessment are analysed. Finally, methods of implementing the assessment tasks and considerations are discussed.

• Bulletin of the Korean Chemical Society
• /
• v.14 no.6
• /
• pp.696-700
• /
• 1993

Gold bonding wire of 0.076 mm in diameter used in semiconductor industry, is dissoved in aqua regia. The solution is then evaporated to near dryness several times with a few drops of HCl added to prepare the final sample solution in 5% HCl. The gold matrix is separated from trace impurities by controlled potential deposition. The whole electrolysis has been carried out inside a clean bench. An optimum potential is found to be +0.25 V to give more than 99.9% Au matrix removal with better than 90 analytes remaining in the electrolyte solution. Isotope dilution calibration is employed to get the best accuracy and precision. Analytical results are presented with determination limits of the analytical method.

• Bulletin of the Korean Chemical Society
• /
• v.19 no.8
• /
• pp.868-874
• /
• 1998

An equivalent retention has been experimentally observed in thermal field-flow fractionation (ThFFF) for different polymer-solvent systems. It is shown that iso-retention between two sets of polymer-solvent systems can be obtained by adjusting the temperature difference (ΔT) according to the difference in the ratio of ordinary diffusion coefficient to thermal diffusion coefficient. This method uses a compensation of field strength (ΔT) in ThFFF at a fixed condition of cold wall temperature. It is applied for the calculation of molecular weight of polymers based on a calibration run of different standards obtained at an adjusted AT. The polymer standards used in this study are polystyrene (PS), polymethylmethacrylate (PMMA), and polytetrahydrofuran (PTHF). Three carrier solvents, tetrahydrofuran (THF), methylethylketone (MEK) and ethylacetate (ETAc) were employed. Though the accuracy in the calculation of molecular weight is dependent on the difference in the slope of log λ vs. log M which is related to Mark-Houwink constant a, it shows reasonable agreement within about 6% of relative error in molecular weight calculation for the polymer-solvent systems having similar a value.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.253-260
• /
• 2022

Existing web-based cost databases have proved invaluable for construction cost estimating. These databases have been utilized to compute approximate cost estimates using assembly rates, unit rates, and etc. These web-based databases can be used independently with traditional cost estimation methods (manual methods) or used to support BIM-based cost estimating platforms. However, these databases are rigid, costly, and require a lot of manual inputs to reflect recent trends in prices or prices relative to a construction project's location. To address this gap, this study integrated deep learning techniques with web-based price analysis to develop a database that incorporates a project's location cost estimating standards and current cost trends in generating a cost estimate. The proposed method was tested in a case study project in Lagos, Nigeria. A cost estimate was successfully generated. Comparison of the experimental results with results using current industry standards showed that the proposed method achieved a 98.16% accuracy. The results showed that the proposed method was successful in generating approximate cost estimates irrespective of project's location.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.17 no.5
• /
• pp.117-127
• /
• 2018

The author tried to propose the orthographic and DTM (digital terrain model) creation and evaluate the accuracy for an university campus using UAV (unmanned aerial vehicle) system. Most previous studies used GPS-based data, but in this paper, the observations of triangulation level measurements was used for comparison of accuracy. Accuracy analysis results showed that the operational requirements for aerial photographic standards are satisfied in all scenaries. The author confirmed availability in aviation photo measurements and applications using UAV (Drone). In order to create a sophisticated DTM and contour, we need to eliminate interference from building, trees, and artificial objects. The results of this study are expected to be used as the basis for future studies in the creation of DTM and the accuracy assessments using Drone.

• Archives of Plastic Surgery
• /
• v.41 no.5
• /
• pp.500-504
• /
• 2014

Background Skin cancer is the most prevalent cancer by organ type and referral accuracy is vital for diagnosis and management. The British Association of Dermatologists (BAD) and literature highlight the importance of accurate skin lesion examination, diagnosis and educationally-relevant studies. Methods We undertook a review of the relevant literature, a national audit of skin lesion description standards and a study of speciality training influences on these descriptions. Questionnaires (n=200), with pictures of a circular and an oval lesion, were distributed to UK dermatology/plastic surgery consultants and speciality trainees (ST), general practitioners (GP), and medical students (MS). The following variables were analysed against a pre-defined 95% inclusion accuracy standard: site, shape, size, skin/colour, and presence of associated scars. Results There were 250 lesion descriptions provided by 125 consultants, STs, GPs, and MSs. Inclusion accuracy was greatest for consultants over STs (80% vs. 68%; P<0.001), GPs (57%) and MSs (46%) (P<0.0001), for STs over GPs (P<0.010) and MSs (P<0.0001) and for GPs over MSs (P<0.010), all falling below audit standard. Size description accuracy sub-analysis according to circular/oval dimensions was as follows: consultants (94%), GPs (80%), STs (73%), MSs (37%), with the most common error implying a quadrilateral shape (66%). Addressing BAD guidelines and published requirements for more empirical performance data to improve teaching methods, we performed a national audit and studied skin lesion descriptions. To improve diagnostic and referral accuracy for patients, healthcare professionals must strive towards accuracy (a circle is not a square). Conclusions We provide supportive evidence that increased speciality training improves this process and propose that greater focus is placed on such training early on during medical training, and maintained throughout clinical practice.

• Journal of Periodontal and Implant Science
• /
• v.54 no.1
• /
• pp.3-12
• /
• 2024

Deep learning (DL) offers promising performance in computer vision tasks and is highly suitable for dental image recognition and analysis. We evaluated the accuracy of DL algorithms in identifying and classifying dental implant systems (DISs) using dental imaging. In this systematic review and meta-analysis, we explored the MEDLINE/PubMed, Scopus, Embase, and Google Scholar databases and identified studies published between January 2011 and March 2022. Studies conducted on DL approaches for DIS identification or classification were included, and the accuracy of the DL models was evaluated using panoramic and periapical radiographic images. The quality of the selected studies was assessed using QUADAS-2. This review was registered with PROSPERO (CRDCRD42022309624). From 1,293 identified records, 9 studies were included in this systematic review and meta-analysis. The DL-based implant classification accuracy was no less than 70.75% (95% confidence interval [CI], 65.6%-75.9%) and no higher than 98.19 (95% CI, 97.8%-98.5%). The weighted accuracy was calculated, and the pooled sample size was 46,645, with an overall accuracy of 92.16% (95% CI, 90.8%-93.5%). The risk of bias and applicability concerns were judged as high for most studies, mainly regarding data selection and reference standards. DL models showed high accuracy in identifying and classifying DISs using panoramic and periapical radiographic images. Therefore, DL models are promising prospects for use as decision aids and decision-making tools; however, there are limitations with respect to their application in actual clinical practice.