Comparison of the Packet Wavelet Transform Method for Medical Image Compression

Medical images are often used for educational, analytical, and medical diagnostic purposes. Medical image data requires large amounts of storage on computers. Three types of codecs, namely Haar, Daubechies, and Biorthogonal, were used in this study. This study aims to find the best wavelet method of the three tested wavelet methods (Haar, Daubechies, and Biorthogonal). This study uses medical images representing USG and CT-scan images as testing data. The first test is carried out by comparing the threshold ratio. Three threshold values are used, namely 30, 40, and 50. The second test looks for PSNR values with different thresholds. The third test looks for a comparison of the rate (image size) to the PSSR value. The final test is to find each medical image's compression and decompression times. The first compression ratio test results on both medical images showed that CT scan images on Haar and Biorthogonal wavelets were the best, with an average compression ratio of 40.76% and a PSNR of 33.77. The PSNR obtained is also getting more significant for testing with a larger image size. The average compression time is 0.52 seconds, and the decompression time is 2.27 seconds. Based on the test results, this study recommends that the Daubechies wavelet method is very good for compression, which is 0.51 seconds, and the Biorthogonal wavelet method is very good for medical image decompression, which is 1.69 seconds

PENGEMBANGAN JARINGAN INTERNET WIRELESS DENGAN WIFI OVERVIEW PADA OBYEK WISATA BLANGSINGA WATERFALL

Blangsinga Waterfall is one tourist attraction with very extreme geographical conditions, where the area has not covered GSM signals as a result tourists can not access the Internet network. The purpose of this research is to determine the spot of Wireless and Hotspot network infrastructure and then to measure signal strength for tourism area coverage. Based on field analysis determined 3 (three) points for network construction and placement of Access Point as Hotspot. Implementation begins with building a LAN network. Then for scanning channel and signal access point testing used Wifi Overview tool. Signal strength testing is performed around the area of ​​the resort by taking a distance of 5m, 10m, and 15m in all directions from the Access point is placed. The result is the establishment of internetworking for Blangsinga Waterfall tourism area. The next result is the internet access where all the tourist areas are covered wifi signal. With the development of internet infrastructure, tourists get easier communication access and management of tourist attractions can develop other facilities based on internet network that has been built.Blangsinga Waterfall merupakan salah satu objek wisata dengan kondisi geografis yang sangat ekstrim, Dimana area tersebut belum tercover sinyal GSM akibatnya wisatawan tidak bisa mengakses jaringan internet. Tujuan penelitian ini adalah menentukan spot infrastruktur jaringan Wireless serta Hotspot dan kemudian melakukan pengukuran kekuatan sinyal untuk coverage areal wisata. Berdasarkan analisa lapangan ditentukan 3 (tiga) titik untuk pembangunan jaringan dan penempatan Access Point sebagai Hotspot. Implementasi diawali dengan membangun jaringan LAN. Kemudian untuk scanning channel dan pengujian sinyal access point digunakan tools Wifi Overview. Pengujian kekuatan sinyal dilakukan di sekitar areal tempat wisata dengan mengambil jarak 5m, 10m, dan 15m  ke segala arah dari Access point ditempatkan. Hasil yang dicapai adalah terbangunnya internetworking untuk areal wisata Blangsinga Waterfall. Hasil berikutnya adalah adanya akses internet dimana semua areal wisata ter-cover sinyal wifi. Dengan terbangunnya infrastruktur internet, wisatawan mendapatkan akses komunikasi lebih mudah serta pengelola tempat wisata dapat mengembangkan fasilitas lain dengan berdasar jaringan internet yang sudah dibangun

Facemask detection using the YOLO-v5 algorithm: assessing dataset variation and resolutions

The Covid-19 pandemic has made it imperative to prioritize health standards in companies and public areas with a large number of people. Typically, officers oversee the usage of masks in public spaces; however, computer vision can be employed to facilitate this process. This study focuses on the detection of facemask usage utilizing the YOLO-v5 algorithm across various datasets and resolutions. Three datasets were employed: the face with mask dataset (M dataset), the synthetic dataset (S dataset), and the combined dataset (G dataset), with image resolutions of 320 pixels and 640 pixels, respectively. The objective of this study is to assess the accuracy of the YOLO-v5 algorithm in detecting whether an individual is wearing a mask or not. In addition, the algorithm was tested on a dataset comprising individuals wearing masks and a synthetic dataset. The training results indicate that higher resolutions lead to longer training times, but yield excellent prediction outcomes. The system test results demonstrate that face image detection using the YOLO-v5 method performs exceptionally well at a resolution of 640 pixels, achieving a detection rate of 99.2 percent for the G dataset, 98.5 percent for the S dataset, and 98.9 percent for the M dataset. These test results provide evidence that the YOLO-v5 algorithm is highly recommended for accurate detection of facemask usage

KOMPRESI CITRA MEDIS MENGGUNAKAN PACKET WAVELET TRANSFORM DAN RUN LENGTH ENCODING

Citra medis memegang peranan yang sangat penting dalam dunia medis saat ini. Biasanya citra medis membutuhkan penyimpanan yang cukup besar pada komputer. Penelitian ini bertujuan untuk melakukan kompresi pada citra medis menggunakan wavelet packet transform (PWT) dan run length encoding (RLE). Tiga jenis codec yaitu Haar, Daubechies dan Biorthogonal digunakan dalam penelitian ini. Penelitian ini membandingkan rasio kompresi, waktu kompresi dan dekompresi untuk setiap citra. Penelitian ini menggunakan tiga nilai threshold yaitu 30, 40 dan 50. Percobaan yang dilakukan menggunakan lima citra medis yang mewakili jenis citra hasil X-ray, USG dan CT-Scan sebagai data testing. Penelitian ini menunjukkan bahwa codec Haar dan Biorthogonal memberikan hasil yang lebih baik dibandingkan codec Daubechies dalam hal kualitas citra (PSNR) dan rasio. Akan tetapi untuk waktu kompresi, codec Daubechies lebih cepat meskipun tidak secara signifikan

Developing Organizational Agility in SMEs: An Investigation of Innovation’s Roles and Strategic Flexibility

Although social capital and collaborative knowledge creation were considered essential drivers in maintaining competitive advantage, empirical evidence on the impact of collaborative knowledge creation on organizational agility remained limited. Therefore, this study examined the relationship between social capital and collaborative knowledge creation in building innovation and agility and testing strategic flexibility as a moderating variable. It employed a quantitative design by distributing questionnaires to 414 managers and assistant managers of SMEs analyzed by SmartPLS-SEM. The results showed that social capital significantly affected collaborative knowledge creation, innovation, and organizational agility. Meanwhile, collaborative knowledge creation has no significant impact on organizational agility. Furthermore, strategic flexibility was not a moderating variable of the relationship between innovation and organizational agility. Based on these findings, this study produced recommendations for managers to strengthen organizational agility

Roboswab: A Covid-19 Thermal Imaging Detector Based on Oral and Facial Temperatures

The SARS-CoV-2 virus has been the precursor of the coronavirus disease (COVID-19). The symptoms of COVID-19 begin with the common cold and then become very severe, such as those of Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). Currently, polymerase chain reaction (PCR) is used to detect COVID-19 accurately, but it causes some side effects to the patient when the test is performed. Therefore, the proposed "Roboswab" was developed that uses thermal imaging to measure non-contact facial and oral temperature. This study focuses on the performance of the proposed equipment in measuring facial and oral temperature from various distances. Face detection also involves checking whether the subject is wearing a mask or not. Image processing methods with thermal imaging and robotic manipulators are integrated into a contact-free detector that is inexpensive, accurate, and painless. This research has successfully detected masked or non-masked faces and accurately detected facial temperature. The results showed that the accurate measurement of facial temperature with a mask is 90% with an error of +/- 0.05%, while it was 100% without a mask. On the other hand, the oral temperature was measured with 97% accuracy and an error of less than 5%. The optimal distance of the Roboswab to the face for measuring temperature is an average of 60 cm. The Roboswab tool equipped with masked or non-masked face detection can be used for early detection of COVID-19 without direct contact with patients