Advance Urban Flood Control System Using Fuzzy Logic and Internet of Things (IoT) for Smart City

City flood control is a significant concern everywhere due to the constantly changing environment. The modern world needs smart cities with smart infrastructure to manage or control floodwaters. The research objective of this study is to design real time urban flood control methodology, develop the working model and testing the model with result analysis in controlled environment. This research paper proposes a smart water control model based on fuzzy inference system. The research is advancement in the Water Sensitive Storm Water Management System by creating a prototype model and then evaluating it in real-world scenarios using input parameters as rainfall intensity, water flow rate, and water level. The method relies on water catchment flooding data that was collected in real-time using sensors and an autonomous smart controller. The system considers the real-time sensor data from all catchments to make collective decision, which also optimize the use of actuators by conserving the power used by the actuators. In terms of early floodwater control, the recommended approach optimizes the use of actuators with utilizing the existing drainage system. The average water reduction rate at the medium level is 34.8%. At high levels, the average water reduction rate is 61.43%, and at extremely high levels, it 73.63%. A significant reduction of water level achieved in the most inundated area by 73.9 % in high and extreme input parameter value

Revolutionizing Healthcare: The Role of AI-Based Medical Expert Systems in Building a Better Future

Modern society has an increasing need for better architecture and medical care. However, this difficulty is not sufficiently addressed by present medical architecture. The Medicinal Expert technique can be used to help persons in need in order to address this issue. A tremendous amount of medical data, including patient medical histories, records, and new medications, can be managed and maintained using this technology. It can help with decision-making and fill in for specialists when they are not present. The Medicinal Expert approach is a complex computer software system that generates forecasts using empirical data and expert knowledge. Based on the available training data and knowledge base, these systems function intelligently. Additionally, there are numerous Medical Expert System tools that support clinicians, help with diagnosis, and are crucial for instructing medical students. In this study, we introduce an AI-based Medical Expert System, its features, and its potential to help patients and medical students. We also go through some key findings from recent and prior research on expert systems, as well as how these systems can make the world a better place

PF-05280014 (a trastuzumab biosimilar) plus paclitaxel compared with reference trastuzumab plus paclitaxel for HER2-positive metastatic breast cancer: a randomised, double-blind study

BACKGROUND: This randomised, double-blind study compared PF-05280014 (a trastuzumab biosimilar) with reference trastuzumab (Herceptin®) sourced from the European Union (trastuzumab-EU), when each was given with paclitaxel as first-line treatment for HER2-positive metastatic breast cancer. METHODS: Between 4 April 2014 and 22 January 2016, 707 participants were randomised 1:1 to receive intravenous PF-05280014 plus paclitaxel (PF-05280014 group; n = 352) or trastuzumab-EU plus paclitaxel (trastuzumab-EU group; n = 355). PF-05280014 or trastuzumab-EU was administered weekly (first dose 4 mg/kg, subsequent doses 2 mg/kg), with the option to change to a 3-weekly regimen (6 mg/kg) from Week 33. Treatment with PF-05280014 or trastuzumab-EU could continue until disease progression. Paclitaxel (starting dose 80 mg/m2 ) was administered on Days 1, 8 and 15 of 28-day cycles for at least six cycles or until maximal benefit of response. The primary endpoint was objective response rate (ORR), evaluating responses achieved by Week 25 and confirmed by Week 33, based on blinded central radiology review. RESULTS: The risk ratio for ORR was 0.940 (95% CI: 0.842–1.049). The 95% CI fell within the pre-specified equivalence margin of 0.80–1.25. ORR was 62.5% (95% CI: 57.2–67.6%) in the PF-05280014 group and 66.5% (95% CI: 61.3–71.4%) in the trastuzumab-EU group. As of data cut-off on 11 January 2017 (using data up to 378 days post-randomisation), there were no notable differences between groups in progression-free survival (median: 12.16 months in the PF-05280014 group vs. 12.06 months in the trastuzumab-EU group; 1-year rate: 54% vs. 51%) or overall survival (median: not reached in either group; 1-year rate: 89.31% vs. 87.36%). Safety outcomes and immunogenicity were similar between the treatment groups. CONCLUSION: When given as first-line treatment for HER2-positive metastatic breast cancer, PF-05280014 plus paclitaxel demonstrated equivalence to trastuzumab-EU plus paclitaxel in terms of ORR. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov, NCT0198967

Optimization of aftermarket logistics with dual supply chains for Sandvik AB

Background: Aftermarket logistics is important for a manufacturing company to maintain customer satisfaction in the long run. However, the supply chain set for aftermarket parts is equally crucial as the original equipment. Modification or optimization of the logistics systems for slow-moving aftermarket items is inevitable. Sandvik, an engineering company in the mining industry is now interested in optimizing its aftermarket logistics. The analysis will be for the stone crusher models for which original equipment is assembled in China, however the aftermarket items are still supplied from the production site in Sweden. Sandvik is considering even sourcing the aftermarket parts from the suppliers based in China. The company expects the optimization decision will help reduce the complexity of the supply chain and the overall total costs. Before making the decision, it is important to study the logistics and administrative related factors and its impact on the optimized supply chain. Purpose: The purpose will be to analyze the decision of phasing out selected aftermarket items from the production unit (PU) Svedala alongside developing a generic decision model which will support a similar decision-making process in the future. Methodology: Case-based research to analyze the change in different costs, lead times and other qualitative aspects if the aftermarket items are moved to the sister site in China and comparing it with the current values. Design science is applied to develop a decision model which will be generic to all crusher models. All related data were collected from the case company. The master thesis follows an abductive research approach. Conclusion: Sandvik should implement a single SC for stone crusher models AG120 & GA230 by sourcing the equipment and aftermarket items from the suppliers based in China. This will ensure these slow-moving items have a linear supply chain with same efficiency at lower total costs. A generic decision model is present which will help the company take similar optimization decisions in the future. Major factors like annual demand, total costs, lead times, after-effects on manufacturing as well as trade compliances are incorporated in the decision model. Sandvik should search for alternate back-up suppliers to reduce the risk of high supplier dependency due to single sourcing. Better information sharing between the DC and production sites can reduce the bullwhip effect. Longer lead-times can be compensated by having higher safety stocks and efficient inventory control Keywords: Supply chain optimization, Aftermarket logistics, Single and Dual supply chains, Decision ModelOptimization of aftermarket logistics with dual supply chains for Sandvik In recent years an exponential trend has been observed in which manufacturing companies are increasingly buying and manufacturing at a global level in order to improve cost efficiency, multiple procurement options and geographically broaden their operational bases. As a result, the challenges of supply chain management are becoming more complex. Companies are now focusing on integrating their supply chain design, planning and management to gain the benefits of operational efficiency, lower costs and increased customer efficiency. A well-defined and efficient supply chain can give businesses a competitive advantage with reduced costs, increased revenue and greater customer value leading to higher profit margins and long-term relationships with customers. Sandvik, a global engineering company in the mining industry has now recognized the importance of optimizing its aftermarket supply to achieve similar benefits. This master thesis will focus on analyzing the decision of optimizing the aftermarket supply for products in order to have a near-optimal logistics setup. The second purpose is also to build a decision model that will act as a framework for the company to follow while making similar optimization decisions in the future. The analysis will be for the products for which original equipment is assembled in China, however, the aftermarket items are supplied from the production site in Sweden. Sandvik is considering even sourcing the aftermarket parts from the suppliers based in China. Before making the decision, it is important to study the logistics and administrative related factors and its impact on the optimized supply chain. Logistics aspects like annual demand, total costs, lead times, manufacturing times were analyzed and compared for both the alternatives. Similarly, administrative aspects like trade compliances and related costs like import duties were taken into consideration. The company’s decision to optimize the aftermarket supply chain is considered as a strategic decision which will have long term effects on the cost and administration. The total cost is observed to decrease considerably in the optimized supply chain. Apart from the cost benefits, the optimization of the aftermarket contributes to simplifying the supply chain. Since both original equipment and aftermarket parts will be sourced from China, it will generate high-quality data in the company’s information systems. It was observed that the lead times will be increased in the alternate supply chain. However higher lead times should not be the only deciding factor about the optimization decision and this shortcoming does not overshadow other advantages of having a single supply chain for slow-moving items. The problem of higher lead time can be overcome by having in place efficient supply chain planning strategies for better customer demand fulfillment. Effective inventory control measures like opting for high order quantity values will help maintain the required service levels which are the backbone of spare parts logistics. Sandvik can use economies of scale to negotiate for better standard costs and induce healthy supplier competition. Based on the steps followed in the analysis, a generic decision model was developed which acts as a framework for the case company to follow while analyzing the decision on optimizing the aftermarket supply chain. It provides a step-by-step procedure to analyze and compare the supply chain before and after optimization. It also provides the user with the type of data that will be required to execute the action mentioned at each step. It also mentions the people who can be contacted to help with the analysis at each stage. We believe the decision model will help the company in all future decision making about the optimization process

DESIGNING PASSIVE FILTER USING NON-TRADITIONAL TECHNIQUE

Harmonics and its mitigation technique are headache for most of the power engineers for the obvious reasons; its adverse effects on power system. In power system, various techniques exist for mitigation, but most of them are based on the study of harmonic pattern at the site. Beside this, there is no passive filter design for ASDs (Automatic Speed Drives). This paper focuses on filter design technique based on Butterworth filter. It does not need any prior study of harmonics at the site. It is applicable for both VFDs (Variable Frequency Drives) and PCCs (Point of Common Coupling)

Not Available

Not AvailableBackground Moringa pods are known for their nutritional and health benefits. The cultivation of this crop receives frequent pesticide applications. In the absence of risk assessment data, maximum residue limits of pesticides in this crop are considered at the default level (0.01 mg/kg). However, there exists scarcely any validated method for pesticide residue analysis in this matrix. Objective This study was undertaken to develop and validate a multiresidue method for the simultaneous analysis of multi-class pesticides in moringa pods by gas chromatography-tandem mass spectrometry (GC-MS/MS), and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Method The homogenized sample (10 g) was extracted with acetonitrile (10 mL). The extract was cleaned by dispersive solid-phase extraction using a combination of 50 mg primary secondary amine, 5 mg graphitized carbon black, and 25 mg C18 sorbents, and was directly analyzed by LC-MS/MS. Another portion of the extract was reconstituted in ethyl acetate before GC-MS/MS analysis. The method was validated as per the SANTE/12682/2019 guidelines using GC-MS/MS (180 pesticides) and LC-MS/MS instruments (203 pesticides). Results The method provided a satisfactory analysis of the targeted pesticides with good calibration linearity (r2>0.99), high precision (RSD < 20%), and accuracy (recoveries, 70 to 120%). The reconstitution of the acetonitrile extract in ethyl acetate significantly reduced the matrix effects on GC-MS/MS analysis. The use of matrix-matched standards could correct all recoveries. Conclusions The method offered a large-scale analysis of multi-class pesticides with high accuracy, and precision at 10 ng/g, and higher levels. The method performance complied with the regulatory requirements, and thus, can be implemented in routine testing purposes. Highlights The study reports a validated method for large-scale multiresidue analysis of pesticides in moringa matrix for the first time. The method provided a high throughput analysis of multi-class pesticides with satisfactory selectivity, sensitivity, accuracy, and precision.Not Availabl