Deep learning based solder joint defect detection on industrial printed circuit board X-ray images

With the improvement of electronic circuit production methods, such as reduction of component size and the increase of component density, the risk of defects is increasing in the production line. Many techniques have been incorporated to check for failed solder joints, such as X-ray imaging, optical imaging and thermal imaging, among which X-ray imaging can inspect external and internal defects. However, some advanced algorithms are not accurate enough to meet the requirements of quality control. A lot of manual inspection is required that increases the specialist workload. In addition, automatic X-ray inspection could produce incorrect region of interests that deteriorates the defect detection. The high-dimensionality of X-ray images and changes in image size also pose challenges to detection algorithms. Recently, the latest advances in deep learning provide inspiration for image-based tasks and are competitive with human level. In this work, deep learning is introduced in the inspection for quality control. Four joint defect detection models based on artificial intelligence are proposed and compared. The noisy ROI and the change of image dimension problems are addressed. The effectiveness of the proposed models is verified by experiments on real-world 3D X-ray dataset, which saves the specialist inspection workload greatly.

Prediction of Focal Image for Solar Parabolic Dish Concentrator With Square Facets – An Analytical Model

Solar parabolic dish concentrator is one of the high-temperature applications of more than 400 °C for thermal and electrical power generation. In the solar parabolic dish concentrator, the arrangement of reflectors over the surface area is the significant factor for effective concentration of solar radiation. Also, focal image is one of the most influencing parameters in the design of receiver. Among the various reflectors, the square shaped reflectors (facets) are comparatively effective in converging the incoming radiations to attain better focal image. In this regard, an attempt has been made to predict the focal image diameter of a solar parabolic dish concentrator with a square facet of different influencing parameters using a novel mathematical model. The influencing parameters considered for the study are aperture diameter, rim angle, and facet length of the dish concentrator. Based on the proposed model, the focal image dimension and aperture area of a solar parabolic dish concentrator with square facets can be predicted accurately for efficient design of a solar parabolic dish collector system. Finally, the proposed model is validated with the experimentally obtained focal image diameter and it is observed that the predicted result is in good agreement with the experimental one. Thus, the proposed model can be effectively used for the design of parabolic dish system for sustainable development.

Customer-Based Brand Equity for a Tourism Destination: The Case of Croatia

Tourism has been negatively impacted by the global COVID-19 pandemic, making it even more important for tourist destinations to focus on their brand equity from the perspective of their customers—visitors. The aim of this paper is therefore to verify and modify the model of customer-based brand equity for a tourism destination (CBBETD) and its attributes for the destination of Croatia from the perspective of Czech tourists, among whom primary research was conducted using the CAWI method (n = 451). The main CBBE dimensions were extracted using factor analysis and a model with four dimensions (awareness, image, quality and loyalty) was created. The identified attributes explain between 55% and 82% of the variability of a given dimension. Although the study’s results follow the published models of CBBETD, the attributes in each dimension and the subdimension in the image dimension reflect the specificities of the destination of Croatia. Thus, the results of this paper extend the economic theory with another model and are also applicable in the field of destination management.

Research on the Extraction of Image Edge Information in Convolutional Neural Networks

Convolutional neural network is an important neural network model in deep learning and a common algorithm in computer vision problems. From the perspective of practical application scenarios, this paper studies whether padding in convolutional neural network convolution layer weakens the image edge information. In order to eliminate the background factor, this paper select MNIST dataset as the research object, move the 0-9 digital image to the specified image edge by clearing the white area pixels in the specified direction, and use OpenCV to realize bilinear interpolation to scale the image to ensure that the image dimension is 28×28. The convolution neural network is built to train the original dataset and the processed dataset, and the accuracy rates are 0.9892 and 0.1082 respectively. In the comparative experiment, padding cannot solve the problem of weakening the image edge weight well. In the actual digital recognition scene, it is necessary to consider whether the core recognition area in the input image is at the edge of the image.

Stigma during COVID-19 pandemic among healthcare workers in greater Jakarta metropolitan area: a cross-sectional online study

Background: COVID-19, which started in Wuhan, has become a global pandemic leading to a new global risk to human health. Lack of information or misinformation about COVID-19 can lead to stigmatization, including for health workers. This study aims to determine the stigmatization among health workers during the COVID-19 pandemic within the Greater Jakarta Metropolitan Area. Methods: This study was a cross-sectional study conducted online using Google Forms in the Jabodetabek area. The questionnaire’s link was distributed through social media, including Whatsapp, Facebook, Twitter, and Instagram. The study sample is health workers who live in Jabodetabek and carry out health practices. Stigma is measured using four dimensions: personalized stigma, disclosure concerns, public attitudes, and negative self-image. Result: The negative self-image dimension is the dimension most felt by health workers. More than half of health workers agreed that during the COVID-19 pandemic, they put their families at risk because of their status as health workers. The stigma of health workers who work in hospitals is higher than that of non-hospital health workers, such as health centers, clinics, and laboratories. Conclusion: There was any stigmatization among healthcare workers in Greater Jakarta Metropolitan Area. Stigmatization was higher among healthcare workers who work in hospitals compared to those who work in non-hospitals. Some efforts should be made to reduce stigmatization among health workers, such as provide correct information to the public, equip health personnel with adequate personal protective equipment, and give incentives periodically to the health workers. Keywords: Stigma, COVID-19, healthcare workers, Greater Jakarta Metropolitan Area Abstrak Latar belakang: COVID-19 yang bermula dari Wuhan telah menjadi pandemi global yang mengancam kesehatan umat manusia. Kurangnya informasi atau informasi yang salah mengenai COVID-19 dapat menyebabkan adanya stigmatisasi termasuk terhadap tenaga kesehatan. Penelitian ini menilai adanya stigmatisasi terhadap tenaga kesehatan selama pandemi COVID-19 di wilayah Jabodetabek. Metode: Penelitian ini merupakan penelitian potong lintang dan dilakukan secara daring menggunakan Google Form di wilayah Jabodetabek. Tautan pengisian kuesioner disebarkan melalui media sosial seperti Whatsapp, Facebook, Twitter dan Instagram. Sampel studi adalah tenaga kesehatan yang tinggal di Jabodetabek dan melakukan praktik kesehatan. Stigma diukur menggunakan empat dimensi yaitu personized stigma, disclosure concerns, concerns about public attitudes dan negative self-image. Hasil: Dimensi negative self-image merupakan dimensi yang paling dirasakan oleh tenaga kesehatan. Lebih dari separuh tenaga kesehatan setuju bahwa selama pandemi COVID-19 mereka membahayakan keluarga mereka karena status mereka sebagai tenaga kesehatan. Stigma pada tenaga kesehatan yang bekerja di rumah sakit lebih tinggi disbanding tenaga kesehatan yang bekerja bukan di rumah sakit seperti puskesmas, klinik dan laboratorium. Kesimpulan: Terdapat stigmatisasi pada petugas kesehatan di jabodetabek. Stigmatisasi lebih tinggi di antara petugas kesehatan yang bekerja di rumah sakit dibandingkan dengan mereka yang bekerja tidak di rumah sakit. Beberapa upaya yang perlu dilakukan untuk mengurangi stigmatisasi di kalangan petugas kesehatan, seperti memberikan informasi yang benar kepada masyarakat, melengkapi tenaga kesehatan dengan alat pelindung diri yang memadai, dan memberikan insentif kepada mereka secara berkala. Kata Kunci: Stigma, COVID-19, tenaga kesehatan, jabodetabek

Perceived Destination Image and Post-Visit Behaviour: An International MICE Visitors’ Perspective

Africa including Kenya has continued to suffer negative images due to stereotypes, prejudice, and negative reporting by international media. This has continued to negatively affect the continents' share of the global leisure tourism market despite the rich and unique natural touristic resources. The continents’ MICE tourism, however, has been on the growth path before COVID 19 pandemic. This study, therefore, investigated the influence of perceived destination image by international MICE visitors on their post-visit behaviour. The study was carried out in the Kenyan capital city, Nairobi. The study followed a convenience sampling method with a total sample of 335 respondents. A model on destination image and post-visit behaviour was developed and tested. A blindfolding procedure in PLS showed the model had predictive relevance. Findings indicated that the cognitive image dimension had a positive and significant influence on affective image, overall image, and post-visit behaviour. Affective image positively influences overall image but not post-visit behaviour. Overall destination image had the greatest effect on post-visit behaviour. Destination Marketers in Kenya should pay particular attention to the destination’s cognitive image. The study provides valuable information for policymakers and destination marketers in developing actionable positioning strategies to enhance the destination’s image and competitiveness.

Evaluasi kualitas pelayanan dengan metode airqual, importance-performance analysis dan competitive zone of tolerance-based importance-performance analysis

This study aims to identify and provide priority proposals for improving the quality of airline services in Indonesia, case studies of X Airline and Y Airline using the AIRQUAL method and the Competitive Zone of Tolerance Based Importance-Performance Analysis (CZIPA).This research is classified as descriptive research. The population in this study are all X Air and Y passengers residing in West Sumatra. The sampling technique in this study is using purposive sampling technique with the criteria of respondents who have been on X or Y Airline at least 3 times and boarded the aircraft in the last 3 years. The total sample is 530 samples. The data used are primary data obtained from online questionnaires. Data analysis method used is the Competitive Zone of Tolerance Based Importance-Performance Analysis.The results of this study concluded that the AIRQUAL indicator that became the priority order of improvement for the X airline is the cleanliness of the well-maintained aircraft toilets (Airline Tangible dimension), airline officials were willing to provide their assistance to everyone on the plane (personal service dimension), airline officers dressed well (empathy dimension) and ticket prices that are the same value as the service received (image dimension). Whereas Y Airline gets a positive CZSQ and d value. This indicates that Y Airline still outperforms X Airline in the attributes included in quadrant A in the CZIPA matrix. The AIRQUAL indicators that enter into the A quadrant are the availability of seats and the provision of promotions that are very attractive to passengers (image dimension) and clean and comfortable seats (Airline Tangible dimension). Keywords: Service Quality, airqual, importance-performance analysys (ipa) and competitive zone of tolerance based importance-performance analysys (czipa)