Search

The ongoing COVID-19 pandemic has created an unprecedented predicament for global supply chains (SCs). Shipments of essential and life-saving products, ranging from pharmaceuticals, agriculture, and healthcare, to manufacturing, have been significantly impacted or delayed, making the global SCs vulnerable. A better understanding of the shipment risks can substantially reduce that nervousness. Thenceforth, this paper proposes a few Deep Learning (DL) approaches to mitigate shipment risks by predicting "if a shipment can be exported from one source to another", despite the restrictions imposed by the COVID-19 pandemic. The proposed DL methodologies have four main stages: data capturing, de-noising or pre-processing, feature extraction, and classification. The feature extraction stage depends on two main variants of DL models. The first variant involves three recurrent neural networks (RNN) structures (i.e., long short-term memory (LSTM), Bidirectional long short-term memory (BiLSTM), and gated recurrent unit (GRU)), and the second variant is the temporal convolutional network (TCN). In terms of the classification stage, six different classifiers are applied to test the entire methodology. These classifiers are SoftMax, random trees (RT), random forest (RF), k-nearest neighbor (KNN), artificial neural network (ANN), and support vector machine (SVM). The performance of the proposed DL models is evaluated based on an online dataset (taken as a case study). The numerical results show that one of the proposed models (i.e., TCN) is about 100% accurate in predicting the risk of shipment to a particular destination under COVID-19 restrictions. Unarguably, the aftermath of this work will help the decision-makers to predict supply chain risks proactively to increase the resiliency of the SCs.

لايزال المث السائد بان " العنف يبدأ من الرأسس قبل أن ينفذ من الأطراف " ، بتج العنف من خلال بيئة اجتماعية و بدنية ، ويلعب الاعلام و البيئة المحيطة دورا رئيسا في تعريف العنف . يولد العنف من عدة مصادر منها العائلة ، الاصدقاء ، المدرسة وكذلك الاعلام . العديد من العوامل الجديدة تؤثر في حدوث العنف ومنها البطالة ، المخدرات ، وتعاطي الحكول . هذه العوامل عندما تجتمع او تتاح لها الفرصة فانها تولد العنف وقد تقوم بأداء هذه الادوار على شكل انتقام . هنالك عدة تاثيرات للدماغ على ظهور ظاهرة العنف ، ويعتبر ملعب كرة القدم هو احد البيئات الخصبة لحدوث هذه الظاهرة . تحاول هذه الدراسة التعرف على التأثيرات الحاصلة على الدماغ بشكل سلبي وحدوث العنف وكذلك العوامل العاطفية ، ظروف تعاطي الخدرات .

Invasion of the skin of the neck by laryngeal carcinoma is relatively uncommon. Twelve cases of cancer of the larynx fungating through the cervical skin are presented. They mostly followed initial treatment by deep X-ray therapy or partial laryngectomy. A high tracheostomy was also considered to be a contributing cause for the occurrence of such a mishap. The management and follow-up of these patients is described.