Deep learning-based meta-learner strategy for electricity theft detection

Electricity theft damages power grid infrastructure and is also responsible for huge revenue losses for electric utilities. Integrating smart meters in traditional power grids enables real-time monitoring and collection of consumers’ electricity consumption (EC) data. Based on the collected data, it is possible to identify the normal and malicious behavior of consumers by analyzing the data using machine learning (ML) and deep learning methods. This paper proposes a deep learning-based meta-learner model to distinguish between normal and malicious patterns in EC data. The proposed model consists of two stages. In Fold-0, the ML classifiers extract diverse knowledge and learns based on EC data. In Fold-1, a multilayer perceptron is used as a meta-learner, which takes the prediction results of Fold-0 classifiers as input, automatically learns non-linear relationships among them, and extracts hidden complicated features to classify normal and malicious behaviors. Therefore, the proposed model controls the overfitting problem and achieves high accuracy. Moreover, extensive experiments are conducted to compare its performance with boosting, bagging, standalone conventional ML classifiers, and baseline models published in top-tier outlets. The proposed model is evaluated using a real EC dataset, which is provided by the Energy Informatics Group in Pakistan. The model achieves 0.910 ROC-AUC and 0.988 PR-AUC values on the test dataset, which are higher than those of the compared models

Clinical Pattern and Post-Operative Complications of Post Tuberculous Meningitis Hydrocephalus in Patients Underwent Ventriculoperitoneal Shunt

Objective: To determine the clinical presentation of post tuberculous meningitis hydrocephalus and post-operative complications in patients underwent placement of a ventriculoperitoneal shunt.Study Design: This Quasi-experimental study was conducted at Department of Neurosurgery of Dow University of Health Sciences/ Civil Hospital, Karachi. Study duration was six months from October 2013 to March 2014.Methodology: Total 40 patients were studied who were diagnosed as cases of tuberculous meningitis and hydrocephalus on the basis of history, clinical examination, CSF findings, CT and MRI. Each patient underwent placement of a ventriculoperitoneal shunt. All the data regarding clinical presentation and postoperative complications was recorded in the proformaRESULTS: Total 40 patients having tuberculous meningitis hydrocephalus were selected; their mean age was 16.4+07.8 years. Male were found in the majority 62.50%, as compared to female 37.50%. According to the clinical presentation, most patients 70.0% were presented with a headache and 62.50% with fever, followed by nausea and vomiting was in 37.5% patients, Neck rigidity was in 27.50% cases, extra neural tuberculosis in 25.0% patients, papilledema in 22.50% cases, limb weakness in 10.0% patients, while fits were found only in 5.0% of the patients. Past history of tuberculosis was in 7.50% patients. According to postoperative complications infection was found in 10.0% of the cases, peritoneal pseudo-cyst without infection was in 7.5% cases, while 10.0% patients died. No significant difference was found in the postoperative complications according to gender p-value 0.94.Conclusion: It is concluded that a headache, fever and nausea/vomiting were the commonest clinical features and the Ventriculoperitoneal shunt is relatively simple and suitable for the patients of all age groups with hydrocephalus, its complications are relatively easy to manage

Line overload alleviations in wind energy integrated power systems using automatic generation control

Modern power systems are largely based on renewable energy sources, especially wind power. However, wind power, due to its intermittent nature and associated forecasting errors, requires an additional amount of balancing power provided through the automatic generation control (AGC) system. In normal operation, AGC dispatch is based on the fixed participation factor taking into account only the economic operation of generating units. However, large-scale injection of additional reserves results in large fluctuations of line power flows, which may overload the line and subsequently reduce the system security if AGC follows the fixed participation factor’s criteria. Therefore, to prevent the transmission line overloading, a dynamic dispatch strategy is required for the AGC system considering the capacities of the transmission lines along with the economic operation of generating units. This paper proposes a real-time dynamic AGC dispatch strategy, which protects the transmission line from overloading during the power dispatch process in an active power balancing operation. The proposed method optimizes the control of the AGC dispatch order to prevent power overflows in the transmission lines, which is achieved by considering how the output change of each generating unit affects the power flow in the associated bus system. Simulations are performed in Dig SILENT software by developing a 5 machine 8 bus Pakistan’s power system model integrating thermal power plant units, gas turbines, and wind power plant systems. Results show that the proposed AGC design efficiently avoids the transmission line congestions in highly wind-integrated power along with the economic operation of generating units

Three-Pond Model with Fuzzy Inference System-Based Water Level Regulation Scheme for Run-of-River Hydropower Plant

Power generation from river hydropower plants depends mainly on river flow. Water fluctuations in the river make the yield process unpredictable. To reduce these fluctuations, building a small reservoir at the river flow of the hydropower plant is recommended. Conventionally, classic single-pond models are commonly used to design run-of-river hydropower plants. However, such models are associated with fluctuations, sagging, and irregular power fluctuations that lead to irregular water fluctuations. This research proposes a novel idea to replace the single-pond model with a three-pond model to increase the plant’s overall efficiency. The three-pond model is developed as a three-tank nonlinear hydraulic system that contains the same amount of water as a conventional single pond. It also has the advantage of minimizing the run-of-river power plant’s dependence on river flow and increasing efficiency by trapping swell and turbulence in the water. To further increase the efficiency, the developed model was tested for smooth and effective level control using fuzzy control.publishedVersionPeer reviewe

A novel missense mutation in TNNI3K causes recessively inherited cardiac conduction disease in a consanguineous Pakistani family

Cardiac conduction disease (CCD), which causes altered electrical impulse propagation in the heart, is a life-threatening condition with high morbidity and mortality. It exhibits genetic and clinical heterogeneity with diverse pathomechanisms, but in most cases, it disrupts the synchronous activity of impulse-generating nodes and impulse-conduction underlying the normal heartbeat. In this study, we investigated a consanguineous Pakistani family comprised of four patients with CCD. We applied whole exome sequencing (WES) and co-segregation analysis, which identified a novel homozygous missense mutation (c.1531T\u3eC;(p.Ser511Pro)) in the highly conserved kinase domain of the cardiac troponin I-interacting kinase (TNNI3K) encoding gene. The behaviors of mutant and native TNNI3K were compared by performing all-atom long-term molecular dynamics simulations, which revealed changes at the protein surface and in the hydrogen bond network. Furthermore, intra and intermolecular interaction analyses revealed that p.Ser511Pro causes structural variation in the ATP-binding pocket and the homodimer interface. These findings suggest p.Ser511Pro to be a pathogenic variant. Our study provides insights into how the variant perturbs the TNNI3K structure-function relationship, leading to a disease state. This is the first report of a recessive mutation in TNNI3K and the first mutation in this gene identified in the Pakistani population

Wind energy potential in Pakistan : A feasibility study in sindh province

The environment and the economy are negatively impacted by conventional energy sources, such as coal, gasoline, and other fossil fuels. Pakistan’s reliance on these resources has resulted in a catastrophic energy crisis. This has driven the government to make critical decisions such as early retail closures, power outages for the industrial sector, and an increase to two days a week vacations. Wind energy, accessible and affordable, will become a viable option for meeting Pakistan’s present and future energy demands. Approximately 3% of Pakistan’s land can produce nearly 132 GW of power with an installed capacity of 5 MW per km2. In this study, four zones (Karachi, Thatta, Badin, and Jamshoro) in Sindh province are assessed for the feasibility of wind energy generation. The installed capacity, generator types, and detailed specifications are provided for each zone. Moreover, the wind mapping of Pakistan is presented considering the four potential zones. The zones are analyzed using annual wind speed and power output considering wind data measured at 50 m height over one year. The higher mean speed is recorded at Jamshoro compared to other zones. The analysis indicates that all four sites are suitable for large-scale wind power generation due to their energy potential

Eco-friendly incorporation of crumb rubber and waste bagasse ash in bituminous concrete mix

The consumption of waste materials in the construction sector is a sustainable approach that helps in reducing the environmental pollution and decreases the construction cost. The present research work emphasizes the mechanical properties of bituminous concrete mix prepared with crumb rubber (CR) and waste sugarcane bagasse ash (SCBA). For the preparation of bituminous concrete mix specimens with CR and SCBA, the effective bitumen content was determined using the Marshall Mix design method. A total of 15 bituminous concrete mix specimens with 4%, 4.5%, 5%, 5.5% and 6% of bitumen content were prepared, and the effective bitumen content turned out to be 4.7%. The effect of five different CR samples of 2%, 4%, 6%, 8% and 10% by weight of total mix and SCBA samples of 25%, 50%, 75% and 100% by weight of filler were investigated on the performance of bituminous concrete. A total of 180 samples with different percentages of CR and SCBA were tested for indirect tensile strength (ITS) and Marshall Stability, and the results were compared with conventional bituminous concrete mix. It was observed that the stability values rose with an increase in CR percentage up to 6%, while the flow values rose as the percentage of SCBA increased in the mix. Maximum ITS results were observed at 4% CR and 25% SCBA replacement levels. However, a decrease in stability and ITS result was observed as the percentages of CR and SCBA increased beyond 4% and 25%, respectively. We concluded that the optimum CR and SCBA content of 4% and 25%, respectively, can be effectively used as a sustainable alternative in bituminous concrete mix

Effects of a high-dose 24-h infusion of tranexamic acid on death and thromboembolic events in patients with acute gastrointestinal bleeding (HALT-IT): an international randomised, double-blind, placebo-controlled trial

Background: Tranexamic acid reduces surgical bleeding and reduces death due to bleeding in patients with trauma. Meta-analyses of small trials show that tranexamic acid might decrease deaths from gastrointestinal bleeding. We aimed to assess the effects of tranexamic acid in patients with gastrointestinal bleeding. Methods: We did an international, multicentre, randomised, placebo-controlled trial in 164 hospitals in 15 countries. Patients were enrolled if the responsible clinician was uncertain whether to use tranexamic acid, were aged above the minimum age considered an adult in their country (either aged 16 years and older or aged 18 years and older), and had significant (defined as at risk of bleeding to death) upper or lower gastrointestinal bleeding. Patients were randomly assigned by selection of a numbered treatment pack from a box containing eight packs that were identical apart from the pack number. Patients received either a loading dose of 1 g tranexamic acid, which was added to 100 mL infusion bag of 0·9% sodium chloride and infused by slow intravenous injection over 10 min, followed by a maintenance dose of 3 g tranexamic acid added to 1 L of any isotonic intravenous solution and infused at 125 mg/h for 24 h, or placebo (sodium chloride 0·9%). Patients, caregivers, and those assessing outcomes were masked to allocation. The primary outcome was death due to bleeding within 5 days of randomisation; analysis excluded patients who received neither dose of the allocated treatment and those for whom outcome data on death were unavailable. This trial was registered with Current Controlled Trials, ISRCTN11225767, and ClinicalTrials.gov, NCT01658124. Findings: Between July 4, 2013, and June 21, 2019, we randomly allocated 12 009 patients to receive tranexamic acid (5994, 49·9%) or matching placebo (6015, 50·1%), of whom 11 952 (99·5%) received the first dose of the allocated treatment. Death due to bleeding within 5 days of randomisation occurred in 222 (4%) of 5956 patients in the tranexamic acid group and in 226 (4%) of 5981 patients in the placebo group (risk ratio [RR] 0·99, 95% CI 0·82–1·18). Arterial thromboembolic events (myocardial infarction or stroke) were similar in the tranexamic acid group and placebo group (42 [0·7%] of 5952 vs 46 [0·8%] of 5977; 0·92; 0·60 to 1·39). Venous thromboembolic events (deep vein thrombosis or pulmonary embolism) were higher in tranexamic acid group than in the placebo group (48 [0·8%] of 5952 vs 26 [0·4%] of 5977; RR 1·85; 95% CI 1·15 to 2·98). Interpretation: We found that tranexamic acid did not reduce death from gastrointestinal bleeding. On the basis of our results, tranexamic acid should not be used for the treatment of gastrointestinal bleeding outside the context of a randomised trial

Computational intelligence approaches for optimizing operations in smart ports

Over the last couple of decades, demand for seaborne containerized trade has increased significantly and it is expected to continue growing over the coming years. As an important node in the maritime industry, a marine container terminal (MCT) should be able to tackle the growing demand for international sea trade. The increasing number of ships and containers creates several challenges to MCTs, such as congestion, long waiting times before ships dock, delayed departures, and high service costs. The berth allocation problem (BAP) and the quay crane assignment problem (QCAP) are two of the most important optimization problems in container terminals at ports worldwide. A BAP concerns allocating berthing positions to arriving ships to reduce total service cost, waiting times, and delays in vessels’ departures. The latter concerns assigning optimal number of quay cranes to docked vessels. From both the port operator’s and the shipping lines’ point of view, minimizing the time a vessel spends at berth and minimizing the total cost of berth operations are considered fundamental objectives with respect to terminal operations. This dissertation initially focuses on the BAP, with the objective of reducing the total service cost, which includes waiting cost, handling cost, and several penalties, such as a penalty for late departure and a penalty for non-optimal berth allocation. First, the BAP is formulated as a mixed-integer linear programming (MILP) model. Since BAP is an NP-hard problem and cannot be solved by exact optimization methods in a reasonable time, a metaheuristic approach, namely, a cuckoo search algorithm (CSA), is proposed to solve the BAP. To validate the performance of the proposed CSA-based method, we use two benchmark approaches, namely, the genetic algorithm (GA) and the optimal MILP solution. Next, we conduct several experiments using a benchmark data set as well as a randomly-generated larger data set. Simulation results show that the proposed CSA algorithm has higher efficiency in allocating berths within a reasonable computation time than its counterparts. Furthermore, we extend the study of BAP, which considers a single quay (straight line) for berthing ships, to multiple quays, as found in many ports around the globe. Multi-quay BAP (MQ-BAP) adds the additional dimension of assigning a preferred quay to each arriving ship, rather than just specifying the berthing position and time. Here, we address MQ-BAP with the objective of minimizing the total service cost, which includes minimizvii ing the waiting times and delays in the departure of ships. MQ-BAP is first formulated as a MILP and then solved using three computational intelligence (CI)-based approaches, namely, CSA, GA, and particle swarm optimization (PSO). In addition, the exact MILP method is also implemented for comparison purposes. Several experiments are conducted using real data from the Port of Limassol, Cyprus, which has five quays serving commercial vessel traffic. The comparative analysis and experimental results show that the CSAbased method outperforms the other CI-based methods, while achieving near-optimal results in affordable time for all considered scenarios. Eventually, this dissertation investigates, for the first time, multi-quay combined BAP and QCAP, and solves it using CI approaches. First, a mathematical model has been developed based on a real port scenario and real constraints. Then, based on the developed model, we solve multi quay combined BAP and QCAP using exact method and CI approaches, i.e., CSA, GA, and PSO. Validation and performance evaluation of the developed modeling framework and the proposed methods are performed through extensive experiments with real data. The real dataset is collected from the Port of Limassol, Cyprus. In addition, the dataset contains data for multiple quays (five), two of which are container terminals and the other three are passenger or general cargo terminals. The experimental results reveal that the exact method can solve the problem only when one week dataset is used; however, our newly adopted CI-based methods for MQ combined (BAP and QCAP) problem are able to solve large instances (i.e., one month) with small computation time. To summarize, this dissertation develops several CI based methodologies for several BAP formulations (stand-alone BAP, MQ-BAP, and MQ combined BAP and QCAP) in real world environments with several practical constraints. The proposed methods have been tested and evaluated extensively using real data against benchmark approaches. Numerical findings from experiments confirm the effectiveness of the proposed solutions. Therefore, the proposed CI-based methods can serve as promising decision support tools and assist terminal operators while developing berth allocation plans. The latter (MQ combined BAP and QCAP) will also assist port operators with the development of a fully-specified berth schedule, for container ships as well as for other general cargo or passengers ships, to ensure that the ships will be moored and departed in a timely manner.Member of the committee: Mikael Lind, Professor Member of the committee: Andreas Andreou, ProfessorComplete