Design and Development of Product Sorting Robot

The EV3 Product Sorting Machine is designed and implemented to provide a better machine for the industry that will act on behalf of the workers in an industry by helping to sort the products according to the type without the usage of manpower. This machine will detect the stock to arrive from the factory, sort it and arrange it for their categories. At the same time, it will also record the total number of stock available in the store and also can withdraw stock from storage by their categories. The main idea why we propose this project is because there are certain problems in the industry like the industry of manufacturing that needs a lot of manpower to complete their work, workers always have mistaken or errors in sorting products to the right place and there is difficulty to calculate stock available. Our objective is to create a sustainable robot to sort products according to the code, to classify products according to the category and to identify the number of products available from each category of product. Here, the image processing method is implemented to determine and read the code on the label of the product, once the image of the code is processed it will instruct the next execution. This project is more significant in developing this robot as this invention could help the industry to get more systematic work with fewer man errors. Besides that, this project will also enable the industry to save a lot of money as less manpower needed to work.  Keywords—EV3 Robot; Product Sorting; Image Processing;

Designing and Developing Smart Plant Information System

Pandemic COVID-19 have impacted the way of life of all people in the world. The effect continues worsened when our government-imposed lockdowns and every people need to stay home. Due to too long of staying at home, boredom become  one of the most reported negative psychological effects of the quarantine. It is undeniable that people of all ages enjoy gardening and planting. Hence, this pandemic time can be a golden opportunity for people to get outside of their compound and grow their interest in gardening. Thus, this project is designed to introduce the basic knowledge of plantations in easier and effective way. The system is applicable for multiple users who tend to learn more about plants and its plantation methods. Both men and women can start their own garden with proper planting methods. This system has been developed using several modules such as the leaf recognition using convolutional neural network (CNN), plant disease advice using knowledge based expert system and plant information using chatbot. The leaf recognition using CNN module will help the user to recognize a plant by providing the plant’s leaf image. The plant disease advice will diagnose the certain disease a plant might have by calculating the confidence level of provided symptoms of the disease. Finally, the plant information using chatbot module will provide information about plants by answering the user’s questions. It is hoped that this system could serve as the best smart plant information system to the user

Automatic Road Crack Segmentation Using Thresholding Methods

Maintenance of good condition of roads are very essential to the economy and everyday life of people in a every country. Road cracks are one of the important indicators that show degradations of road surfaces. Inspection of roads that have been done manually took a very long time and tedious. Hence, an automatic road crack segmentation using thresholding methods have been proposed in this study. In this study, ten road crack images have been pre-processed as an initial step. Then, normalization techniques, L1-Sqrt norm have been applied onto images to reduce the variation of intensities that skewed to the right. Then, thresholding methods, Otsu and Sauvola methods have been used to binarize the images.  From the experiment of ten road crack images that have been done, normalization technique, L1-Sqrt norm can help to increase performance of road crack segmentation for Otsu and Sauvola methods. The results also show that Sauvola method outperform Otsu method in detecting road cracks

Proximal Gastrojejunal Reconstruction after Pancreaticoduodenal Resection

Introduction. Reconstruction by proximal gastrojejunostomy, and distal biliary and pancreatic anastomoses is infrequently used after resection of the head of the pancreas because of fear of fistulas and cholangitis. Pancreaticoduodenectomy is being performed more frequently for cystic malignant and premalignant lesions. Because of this there is a need for endoscopic visualization and biopsy of the residual pancreatic duct, since multi-centricity is characteristic of some of these malignancies. Since endoscopic access of the bile duct and pancreatic duct is difficult and unsuccessful in 50–70% after B II or Roux Y reconstruction, we prospectively studied the merit and complications (early and late) of proximal gastrojejunal (PGJ) reconstruction after pancreaticoduodenal resection. Material and Methods. Thirty nine consecutive, non-radomized patients underwent pancreaticoduodenectomy and PGJ reconstruction over 14 mos. There were 21 males and 18 females. Results. 7 patients with IPMN have undergone repeat CT scanning for surveillance, with 3 requiring repeat EUS and ERCP. There were no technical difficulties accessing the pancreas or the pancreatic duct, supporting the PGJ reconstruction. Conclusion. Proximal gastrojejunal reconstruction following pancreaticoduodenal resection may be safely done with similar morbidity to traditional pancreaticojejunal reconstructions. PGJ reconstruction may be of greater value when direct visual access to the bile duct or pancreatic duct is necessary, and should be considered when doing resection for mucinous cysts or IPMN of the head of the pancreas

Comparison on Cloud Image Classification for Thrash Collecting LEGO Mindstorms EV3 Robot

The world today faces the biggestwaste management crisis due to rapid economicgrowth, congestion, urban planning issues,devastating negative symptoms and politicalaffairs. In addressing this waste managementproblem, many methods of solving wastemanagement have proven not to be as planned.In this high technology era, the innovation ofhumanoid robots is found to be helpful to supportthe everyday human life. The industry is gearingtowards automation to increase productivity at thesame time will improved quality of life to localcommunities. Therefore, in this paper ThrashCollecting Robot (TCR) is proposed to helpprovide automatic control in thrash collection. TheTCR, built on the LEGO Mindstorm EV3 robot, candistinguish between static and dynamic barriers,and can move according to the programming thathas been created. TCRs are basically composedof sensors designed according to differentrequirements in order to detect dynamic barriers.TCR is one type of Cloud Robot that implementsimage processing techniques to identify the typeof waste that has been collected. The concept ofimage processing built in TCR by using CloudRepresentational State Transfer (REST API).This concept has been applied by Google CloudAPI and Sighthound. This cloud services usedmachine vision techniques to identify and classifythe type of thrash images; whether it is plastic,metal or paper. Experiment results show thatSightHound gives accurate result compared toGoogle Cloud in classifying thrash types

Students’ experiences, learning outcomes and satisfaction in e-learning

This study was aimed to examine whether students’ experiences in e-learning are related to learning outcomes and satisfaction. Three learning experiences, which are course design, interaction with the instructor and interaction with peer students were identified as the predictors of learning outcomes and satisfaction. Self-administered questionnaire was adopted. The paper questionnaires were distributed to students at a university in Malaysia. In total, 670 valid responses were obtained. Exploratory factor analysis was performed to confirm the underlying factor structure for the observed variables. Regression analyses indicated that course design, interaction with the instructor and interaction with peer students are positively related to the learning outcomes and satisfaction. Among all learning experiences, interaction with peer students make the strongest contributions to learning outcomes and satisfaction. This study demonstrates the importance for University administrators and instructors to design e-learning course to optimal students’ experiences to enhance their learning outcomes and satisfaction

Renal cell cancer without a renal primary

Renal cell carcinoma has been increasing in incidence over the past two decades. Men are affected more than women and metastatic disease at presentation occurs in up to one third of patients. Metastasis can occur to virtually any organ, and involvement of multiple organs is not uncommon. To date, no reports have been found of metastatic disease without a renal primary. We present a case of renal cell cancer initially presenting as a subcutaneous mass with subsequent pancreatic and parotid gland metastases in absence of a primary renal source

Conference of Soviet and American Jurists on the Law of the Sea and the Protection of the Marine Environment

Included in the papers for the Conference of Soviet and American Jurists on the Law of the Sea and the Protection of the Marine Environment: Introduction by Milton Katz and Richard R. Baxter, p. 1 Freedom of Scientific Research in the World Ocean by A.F. Vysotsky, p. 7 The International Law of Scientific Research in the Oceans by Richard R. Baxter, p. 27 Responsibility and Liability for Harm to the Marine Environment by Robert E. Stein, p. 41 Liability for Marine Environment Pollution Damage in Contemporary International Sea Law by A. L. Makovsky, p. 59 Protection of the Marine Environment from Pollution by Richard A. Frank, p. 73 The Freedom of Navigation and the Problem of Pollution of the Marine Environment by V. A. Kiselev, p. 93 The Freedom of Navigation Under International Law by William E. Butler, p. 107 International Fisheries Management Without Global Agreement: United States Policies and Their Impact on the Soviet Union by H. Gary Knight, p. 119 Some Biological Background for International Legal Acts on Rational Utilization of the Living Resources of the World Ocean by P. A. Moiseev, p. 143 An International Regime for the Seabed Beyond National Jurisdiction by Thomas M. Franck, p. 151 Settlement of Disputes Under the Law of Ocean Use, with Particular Reference to Environmental Protection by John Lawrence Hargrove, p. 18

Beyond climate-smart agriculture: toward safe operating spaces for global food systems

Agriculture is considered to be “climate-smart” when it contributes to increasing food security, adaptation and mitigation in a sustainable way. This new concept now dominates current discussions in agricultural development because of its capacity to unite the agendas of the agriculture, development and climate change communities under one brand. In this opinion piece authored by scientists from a variety of international agricultural and climate research communities, we argue that the concept needs to be evaluated critically because the relationship between the three dimensions is poorly understood, such that practically any improved agricultural practice can be considered climate-smart. This lack of clarity may have contributed to the broad appeal of the concept. From the understanding that we must hold ourselves accountable to demonstrably better meet human needs in the short and long term within foreseeable local and planetary limits, we develop a conceptualization of climate-smart agriculture as agriculture that can be shown to bring us closer to safe operating spaces for agricultural and food systems across spatial and temporal scales. Improvements in the management of agricultural systems that bring us significantly closer to safe operating spaces will require transformations in governance and use of our natural resources, underpinned by enabling political, social and economic conditions beyond incremental changes. Establishing scientifically credible indicators and metrics of long-term safe operating spaces in the context of a changing climate and growing social-ecological challenges is critical to creating the societal demand and political will required to motivate deep transformations. Answering questions on how the needed transformational change can be achieved will require actively setting and testing hypotheses to refine and characterize our concepts of safer spaces for social-ecological systems across scales. This effort will demand prioritizing key areas of innovation, such as (1) improved adaptive management and governance of social-ecological systems; (2) development of meaningful and relevant integrated indicators of social-ecological systems; (3) gathering of quality integrated data, information, knowledge and analytical tools for improved models and scenarios in time frames and at scales relevant for decision-making; and (4) establishment of legitimate and empowered science policy dialogues on local to international scales to facilitate decision making informed by metrics and indicators of safe operating spaces