Halalnet: A Deep Neural Network That Classifies the Halalness of Slaughtered Chicken from Their Images

Halal requirement in food is important for millions of Muslims worldwide especially for meat and chicken products, insuring that slaughter houses adhere to this requirement is a challenging task to do manually. In this paper a method is proposed that uses a camera that takes images of slaughtered chicken on the conveyor in a slaughter house, the images are then analyzed by a deep neural network to classify if the image is of a halal slaughtered chicken or not. However, traditional deep learning models require large amounts of data to train on, which in this case these amounts of data were challenging to collect especially the images of non-halal slaughtered chicken, hence this paper shows how the use of one shot learning (Lake, Brenden, Salakhutdinov, Ruslan, Gross & Jas, 2011) and transfer learning (Yosinski, Clune, Bengio & Lipson, 2014) can reach high accuracy on the few amounts of data that were available. The architecture used is based on the Siamese neural networks architecture which ranks the similarity between two inputs (Koch, Zemel & Salakhutdinov, 2015) while using the Xception network (Chollet, 2017) as the twin networks. We call it HalalNet. This work was done as part of SYCUT (syriah compliant slaughtering system) which is a monitoring system that monitors the halalness of the slaughtered chicken in a slaughter house. The data used to train and validate HalalNet was collected from the Azain slaughtering site (Semenyih, Selangor, Malaysia) containing images of both halal and non-halal slaughtered chicken

Esophagus Detection for Halal Classification in SYCUT

According to the Islamic Law, one of the procedures in halal slaughtering of chicken is the step of severing the trachea, esophagus and both the carotid arteries and jugular veins to accelerate the chicken’s bleeding and death. Syariah Compliance Automated Chicken Processing System (SYCUT) uses the Vision Inspection Technology to detect and classify whether a chicken is halal or not. The lack of quality and halal assurance in chicken processing industry made it a need to produce such technology. The system implements image processing techniques and artificial intelligence approach, particularly the Viola and Jones object detection framework for esophagus detection. The results of the experiment from two different sites (Az-Zain and 3P) are 81.8% and 55% respectively. The detection module of those two sites show results of 95.6% and 93.5% which are the accuracy as good as human personnel

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Pakatan Still at Odds over PM choice

PAKATAN Harapan remains at odds over its choice for prime minister although it has yet to step into the battleground

PEGARUH NILAI-NILAI DASAR PERJUANGAN (NDP) TERHADAP PEMBINAAN KADER HMI DI AMBON

A B S T R A KNama: M. Asrul PattimahuNomor Induk Mahasiswa: 645.03.20.2007Judul Tesis: Pengaruh Nilai-Nilai Dasar Perjuangan Terhadap Pembinaan Kader HMI di AmbonKomisi Pembimbing: Prof. Dr. H. Abd. Rahim Yunus, MA Dr. H. M. Arfah Siddiq, MAKata-kata Kunci: Pengaruh, Nilai-Nilai Dasar Perjuangan, Pembinaan Kader HMIFokus pembahasan dalam tesis ini adalah mengkaji pengaruh Nilai-Nilai Dasar Perjuangan terhadap pembinaan kader HMI di Ambon. pokok pembahasannya dibagi dalam tiga sub pembahasan yaitu, bagaimanakah konsep Nilai-Nilai Dasar Perjuangan HMI. Bagaimanakah pemahaman kader HMI cabang Ambon terhadap Nilai-Nilai Dasar Perjuangan HMI. Bagaimanakah pengaruh Nilai-Nilai Dasar Perjuangan terhadap pembinaan kader HMI. Tujuan penelitian in adalah untuk mengetahui dan menganalisis ketiga permasalahan tersebut.Prinsip dasar dalam penelitian ini bersifat kualitatif dengan pendekatan sosiologis. Data primer diperoleh melalui observasi, wawancara terstruktur, fokus grup diskusi, dan dokumentasi, sedangkan data sekunder diperoleh melalui telaah kepustakaan. Analisis analisis data penelitian dilakukan dengan cara reduksi data, displai data, dan membuat kesimpulan.Berdasarkan hasil penelitian menunjukan bahwa NDP menjadi motivasi utama dan memiliki pengaruh kuat membentuk karakter dan kepribadian kader HMI di Ambon dalam seluruh aktivitas pembinaan, baik itu dalam proses rekruitmen kader, pengembangan kapasitas dan intelektal kader maupun sampai menjadi alumni, dimana kader HMI akan menentukan medan perjuangan dalam pengabdiannya kepada masyarakat, sebagai upaya menjalankan misi untuk mencapai tujuan organisasi HMI