Improving Lookahead search for grid-based pathfinding

Pathfinding is an essential part of navigation systems, often used in video games, route planning and robotic navigation. A* search has been one of the most well-known and frequently used algorithms for pathfinding. A* uses an open list and a closed list to keep track of all nodes generated and expanded. The size and performance of these data structures are major drawbacks of A*. Lookahead is used to investigate future outcomes and improve the quality of available choices. Lookaheads are done on a DFS manner from the frontier of A* search. This combination of A* and DFS lookahead has been shown to save space when working with puzzles. We leverage this concept with grid-based pathfinding in video games to save the amount of space consumed. However, because grids contain redundant paths, the DFS lookaheads end up being an overhead as they do not maintain a list of nodes visited or expanded. By using a domain-specific pruning technique, we significantly improve the time taken by the algorithm and further improve upon the space consumed. A combination of lookahead and A* search with this pruning technique is, therefore, able to achieve improvement in both space-consumed and time-taken over the standard A* search algorithm for grid-based pathfinding

Evaluation of domestic electrical demand and its effect on low voltage network performance

Electrical demand in a house depends on various factors mainly being the user’s behaviour and the rating of the appliances. Some researchers have used daily domestic electrical demand profile at half hour time resolution for the energy management. When data of half hour time interval is used for the analysis of on-site generation, it can lead to over/under -estimates of the proportion of generated energy used on site. As a consequence, this could lead to over/under-estimating in the import and export of power from and to the power grid. In this paper, domestic electricity use profile recorded at high time resolution of one minute is used to analyse the profile obtained at different time resolution and its effect on on-site generation. Daily load profile for summer and winter at time resolution of 30 minute is generated from a data set of 22 houses consisting data of a whole year which is then compared with the daily load curve obtained after diversity maximum demand from the literature. The generated daily load profile is then used to see effect on the low voltage network. For the analysis on the low voltage network, a typical UK low voltage network is developed in the Matlab/Simulink softwar

Sensor fusion of IMU and BLE using a well-condition triangle approach for BLE positioning

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesGPS has been a de-facto standard for outdoor positioning. For indoor positioning different systems exist. But there is no general solution to fit all situations. A popular choice among service provider is BLE-based IPS. BLE-has low cost, low power consumption, and tit is are compatible with newer smartphones. These factors make it suitable for mass market applications with an estimated market of 10 billion USD by 2020. Although, BLEbased IPS have advantages over its counterparts, it has not solved the position accuracy problem yet. More research is needed to meet the position accuracy required for indoor LBS. In this thesis, two ways for accuracy improvement were tested i) a new algorithm for BLE-based IPS was proposed and ii) fusion of BLE position estimates with IMU position estimates was implemented. The first way exploits a concept from control survey called well-conditioned triangle. Theoretically, a well-conditioned triangle is an equilateral triangle but for in practice, triangles whose angles are greater than 30° and less than 120° are considered well-conditioned. Triangles which do not satisfy well-condition are illconditioned. An estimated position has the least error if the geometry from which it is estimated satisfy well-condition. Ill-conditioned triangle should not be used for position estimation. The proposed algorithm checked for well-condition among the closest detected beacons and output estimates only when the beacons geometry satisfied well-condition. The proposed algorithm was compared with weighted centroid (WC) algorithm. Proposed algorithm did not improve on the accuracy but the variance in error was highly reduced. The second way tested was fusion of BLE and IMU using Kálmán filter. Fusion generally gives better results but a noteworthy result from fusion was that the position estimates during turns were accurate. When used separately, both BLE and IMU estimates showed errors in turns. Fusion with IMU improved the accuracy. More research is required to improve accuracy of BLE-based IPS. Reproducibility self-assessment (https://osf.io/j97zp/): 2, 2, 2, 1, 2 (input data, prepossessing, methods, computational environment, results)

Healing Faith

Given the limitations of medical and pharmaceutical treatments regarding the diverse range of pain individuals may experience, one must embrace the alternative paths of healing such as finding peace within ourselves. In this story, a man goes through a metamorphosis to find peace in the final moments of his life. An emotionally distressed, borderline delusional man struggles with his faith in God as he looks for peace in his last moments. He wants to be liberated from the overwhelming feelings of debilitating pain and regret. As he comes in and out of consciousness, he recalls his most beautiful memory. With his final breath, he accepts his fate and finds solace in the visage of the woman whom he had loved his entire life

Fault Location in Grid Connected Ungrounded PV Systems Using Wavelets

Solar photovoltaic (PV) power has become one of the major sources of renewable energy worldwide. This thesis develops a wavelet-based fault location method for ungrounded PV farms based on pattern recognition of the high frequency transients due to switching frequencies in the system and which does not need any separate devices for fault location. The solar PV farm used for the simulation studies consists of a large number of PV modules connected to grid-connected inverters through ungrounded DC cables. Manufacturers report that about 1% of installed PV panels fail annually. Detecting phase to ground faults in ungrounded underground DC cables is also difficult and time consuming. Therefore, identifying ground faults is a significant problem in ungrounded PV systems because such earth faults do not provide sufficient fault currents for their detection and location during system operation. If such ground faults are not cleared quickly, a subsequent ground fault on the healthy phase will create a complete short-circuit in the system, which will cause a fire hazard and arc-flashing. Locating such faults with commonly used fault locators requires costly external high frequency signal generators, transducers, relays, and communication devices as well as generally longer lead times to find the fault. This thesis work proposes a novel fault location scheme that overcomes the shortcomings of the currently available methods. In this research, high frequency noise patterns are used to identify the fault location in an ungrounded PV farm. This high frequency noise is generated due to the switching transients of converters combined with parasitic capacitance of PV panels and cables. The pattern recognition approach, using discrete wavelet transform (DWT) multi-resolution analysis (MRA) and artificial neural networks (ANN), is utilized to investigate the proposed method for ungrounded grid integrated PV systems. Detailed time domain electromagnetic simulations of PV systems are done in a real-time environment and the results are analyzed to verify the performance of the fault locator. The fault locator uses a wavelet transform-based digital signal processing technique, which uses the high frequency patterns of the mid-point voltage signal of the converters to analyze the ground fault location. The Daubechies 10 (db10) wavelet and scale 11 are chosen as the appropriate mother wavelet function and decomposition level according to the characteristics of the noise waveform to give the proposed method better performance. In this study, norm values of the measured waveform at different frequency bands give unique features at different fault locations and are used as the feature vectors for pattern recognition. Then, the three-layer feed-forward ANN classifier, which can automatically classify the fault locations according to the extracted features, is investigated. The neural network is trained with the Levenberg-Marquardt back-propagation learning algorithm. The proposed fault locating scheme is tested and verified for different types of faults, such as ground and line-line faults at PV modules and cables of the ungrounded PV system. These faults are simulated in a real-time environment with a digital simulator and the data is then analyzed with wavelets in MATLAB. The test results show that the proposed method achieves 99.177% and 97.851% of fault location accuracy for different faults in DC cables and PV modules, respectively. Finally, the effectiveness and feasibility of the designed fault locator in real field applications is tested under varying fault impedance, power outputs, temperature, PV parasitic elements, and switching frequencies of the converters. The results demonstrate the proposed approach has very accurate and robust performance even with noisy measurements and changes in operating conditions

Nodule in mesosalphinx: a rare microscopic finding

Ectopic adrenal cortical rests are uncommon in adults, particularly in females. Their occurrence in fallopian tubes or mesosalphinx is extremely rare. Herein, we report a rare occurance of ectopic adrenal cortical rests in mesosalphinx which was diagnosed on histopathological examination. To the best of our knowledge, there are less than five previously published cases at this rare location and the present report is the second case from India. A 46-year-old female who underwent hysterectomy for fibroids was incidentally detected with ectopic adrenal cortical rests in the mesosalphinx on histopathology. The present case is reported to increase the awareness of this unique finding at this rare location, its implications and histopathological diagnosis.

Toward Non-Corrosion and Highly Sustainable Structural Members by Using Ultra-High-Performance Materials for Transportation Infrastructure

This research focused on investigating a highly sustainable and efficient reinforced concrete structural member for future infrastructure by utilizing emerging high-performance materials. These materials include ultra-high-performance fiber-reinforced concrete (UHP-FRC) and corrosion-resistant high-strength fiber-reinforced polymer (FRP) bars. Four reduced scale UHP-FRC specimens were tested under large displacement reversals to prove the proposed new ductile-concrete strong-reinforcement (DCSR) design concept by fully utilizing these ultra-high-performance materials. Micro steel fibers were incorporated into three specimens and ultra-high molecular weight polyethylene fibers were blended into the fourth specimen. One specimen with ASTM A1035 MMFX high-strength steel rebars, one with high-strength glass fiber reinforced polymer (GFRP) rebars, and two with high-strength basalt fiber reinforced plastic (BFRP) rebars were tested. The beams had a reinforcement ratio of 14% to 15%. The test results concluded that the beams could sustain very large cyclic drift ratios without major damage in the UHP-FRC material, which provided ample shear strength and confinement to the reinforcement throughout the testing. Even with the high amount of reinforcement, UHP-FRC’s superior ductility provided a very stable cyclic behavior up to some very large drift ratios. Because of the DCSR design, all specimens also exhibited a self-centering ability, which considerably reduces the residual displacement after being subjected to large displacement reversals. The test results also show that the high damage-resistance and self-centering characteristics of the proposed UHP-FRC flexural members can provide excellent resilience for building structures

Nutritional assessment of school children and adolescents: Pokhara city in Western Nepal

Introduction: Nutritional assessment of school children and adolescent is one of the most cost-effective ways of keeping track of overall wellbeing of children in the society. The objective of this study was to find out the nutritional status of school children and adolescent of Pokhara city using anthropometric indicators.  Method: A total of 1160 students from the schools across the Pokhara city, Nepal, were enrolled in this study. Anthropometric measurements, height and weight, mean height and weight for age, and BMI for age were estimated. Undernutrition and obesity were defined as per the 2007 WHO growth reference data. Association among the variables were determined by applying statistical tests: t-test and Anova.  Result: Growth curve of weight and BMI for age were above 15th percentile and height for age were between 3rd and 15th percentile, in both, boys and girls. The proportion of stunted and underweight students were 26.29% (boys 51% and girls 41%) and 24.65% (boys 53% and girls 47%) respectively. The proportion of thin, severely thin, overweight and obese were 3.53%, 5.03%, 12.49% and 8.96% respectively. Father’s occupation and education, mother’s occupation, school type, number of siblings were statistically associated with mean BMI and height.  Conclusion: Stunted and underweight were seen in a quarter of students, as well overweight and obesity in less than 10% of school children surveyed