New Approaches in Engineering Research Vol. 14

In this study, a new efficient control system for a unified power quality conditioner is developed, which can reduce voltage variations such as sag and swell conditions, as well as current and voltage harmonic isolation in distribution systems.  The suggested control approach is utilised to model and simulate the UPQC that can be used at the PCC to improve power quality, and the results are compared by applying it to a distribution system that has and does not have UPQC. UPQC can be installed to protect the sensitive load inside the plant as well as to restrict entry of any distortion on the load side. The UPQC's performance was assessed using a typical industrial load and realistic characteristics supplied by a polluted distribution network. In the MATLAB/SIMULINK environment, a dynamic model of the UPQC is created, and simulation results proving system power quality improvement are provided for various supply and load circumstances.

Study Objective: The important issue in Evolutionary Algorithms (EAs), is time-complexity analysis.

Here, 1. To consider the concept of take-overtime to obtain the mean hitting time of EA. i.e.  the concept of the takeover time is generalized rather than a selection of operator alone.

1. This generalization is applied to benchmark problems like N-Bit parity. For various input sizes N, the time complexity in terms of number of generations is estimated.
2. To develop an empirical model is also generated for proposed EA using statistical tool.
3. To apply the proper selection method to find the take-overtime.

In 2018, as contribution to the area of calibrations in Industry 4.0, the novel concept of Touchless Calibration (TCal) was introduced. In this paper, a study, accompanied by explanations, results, uncertainty and cost-benefit analysis, followed by practical experiment for the validation of TCal in the area of DC voltage calibrations are presented. Touchless Calibration (TCal) is introduced as a future development in calibration metrology on the XXII IMEKO Congress in Belfast in 2018. TCal is dealing mostly with decreasing the steps necessary to provide calibration traceability. Missing steps actually contribute to considerable decreasing of time and costs of calibration keeping the calibration traceability on high level. In the scope of Metrology for Industry 4.0, it could be one of the important improvements bringing increased effectiveness and efficiency for manufacturing industry.

It is shown by this study, implementing the worst-case scenarios, that TCal can be used in manufacturing companies for the calibration of any measurement system used to measure DC voltages in the range from 0 V to 10 V with tolerances (USL – LSL) bigger than 0.44825 V (± 0.22413 V).

Variations in capacitive fed suspended RMSA systems are proposed in this research. Initially, the reference antenna consists of a rectangle patch measuring 35.5 X 45.6 mm² and a small rectangular feed patch measuring (1.4 X 4) mm² both of which are suspended above the ground plane on the same substrate. Probe feed or coaxial feed is popular and widely used in MSA as it can feed the patch at any arbitrary position without much difficulty. The small patch is fed with a coaxial probe, which electromagnetically excites the radiator patch, resulting in a large impedance bandwidth (BW) of 39 percent, strong gain and a broadside radiation pattern. The prototype antenna was created by meandering the ground plane of the reference antenna with three rectangular slots, and measurements were taken to validate the outcome for compact broadband response. The prototype antenna was then created by loading a pair of rectangular slots in the radiating patch of the reference antenna in addition to the rectangular slots in the ground plane, and measurements were taken to validate the result for compact dual band response.

Solar cars have been the up-and-rising trend. This technology represents the ideal solution for different challenges which have been a concern for different industries, leads to the contrast between contemporary mobility substitutes and the constant seek of sustainability. Given the multilayered nature grasped by this innovation, the fulfillment of an effective structure requests the improvement of each part of the vehicle, including its mechanics, which is the essence of this project. With their exceptional ability to play a critical role in the vehicle’s stability, the suspension system of the solar car, in particular the control arms, is comprehensively scrutinized throughout this project. The objective of this study is o design upper and lower control arms for a solar car using Quality Function Deployment and SolidWorks. Control arms are considered an essential part of a suspension system since it is the link between the chassis and the wheel hub. It also keeps the wheel in contact with the surface at all times and provides the vehicle with the mobility to adapt to uneven surfaces. Therefore, using engineering problem-solving methods, control arms were designed, analyzed, and optimized. However, throughout this report, the process undertaken to achieve those results will be the main point of focus and will be explained thoroughly. The factor of safety (FOS) for the optimum design was 3.4, showing the feasibility of the selected tools such as Quality Function Deployment (QFD) for the chosen engineering problem to determine the optimum solution.

In this study, we use Multiple Linear Regression to forecast short-term load. This study obtains a day-ahead load forecasting. The regression coefficients were calculated using the Least Squares estimation method. Load forecasting has an effective role in economic operation of power utilities.  In an electrical power system, load is affected by temperature, due point, and seasons, as well as previous load consumption (historical data) [1].Temperature, Due point, prior day's load, hours, and prior week's load are the input variables.  The mean absolute percentage error is used to validate the model or assess its accuracy, and R squared is checked [2-5], which is shown in the results section. A weekly prediction is also obtained using day-ahead projected data.

The quality of buildings, especially those executed by indigenous construction firms and professionals in Nigeria cannot be measurable with those of developed countries, or even those of other countries in the West African sub-region such as Benin Republic, Togo and Ghana. This ugly situation has been attributed to many factors, ranging from the dearth of skilled tradesmen, non-existence of national quality standards and code of practice and ineffective government regularity policies to mention a few. It is against this background that this study was undertaken to ascertain the level of compliance with existing quality management standards in public building projects in the South-Eastern States of Nigeria in accordance with NIOB/NBC quality checklist. The construction methodology, project quality management plan, and project health and safety plan are all factors that influence the quality of a structure. A checklist document that guides on workmanship, construction materials, inspection, material sampling, and testing is crucial to the success of the quality management strategy. The checklist document contains 62 variables that were regarded important factors.Subsurface, timber, formwork, concrete work, steel reinforcement, block work, rendering, and roofing were the eight sub-headings for the 62 variables. The evaluation was done on a 5-point Likert scale, and the results were analysed using the weighted average mean index (Iimp), which ranged from -2 to 2. With a mean score of 1.5752, the subsurface sub-sector came in first, followed by the roofing sub-sector.With a mean score of 1.3297, blockwork comes in last, followed by the rendering sub-sector with a mean score of 1.3492. 730 people answered to the 900 structured questionnaires that were distributed, representing an 81.1 percent response rate. Quality control checklists and approved systems for construction project monitoring should be provided by building professional groups and all levels of government regulatory agencies.

Creativity in the field of fashion is known to draw inspiration from many unusual sources. One such source happens to be architectural styles of buildings that strive to preserve the cultural heritage of an entire civilization. The styles might not only inspire simple motifs and silhouette types, but also weave a story that will eventually find its way into more intricate forms of human clothing. Therefore, this paper will lead us to first understand the inner anatomy of a piece of architecture. Later, the paper will help us identify the finer elemental artifacts that can be retrieved and assembled into an exotic fashion creation. The final objective is to establish the hidden relationships, influences, similarities, and differences between the fields of architecture and fashion design. Within India, the great monuments whose architectures are waiting to be exploited for fashion ideas include the Golden Temple, Charminar, Meenakshi, Temple, and Hampi. This study reveals that many fashion designers have been inspired by intricate elements of architecture.

Every year, the number of people dying from lung cancer rises around the world. It is second most cancer affecting among population worldwide. The ability to forecast the onset of cancer in patients can aid clinicians in making decisions about their drugs and therapies.This study suggests a new technique for detecting and predicting the existence of malignant nodules in the lungs of patients. To conduct the classification, the suggested system uses a machine learning technique called support vector machine (SVM) and a deep learning algorithm called convolutional neural network (CNN) and a large lung cancer repository database called the UCI repository. Images are pre-processed and then post-processed in the initial step of cleaning. The RGB to greyscale conversion is included in the pre-processing step, and the noise is removed using the Non-Local Means (NLM) filter in the post-processing step. Image segmentation was achieved using Otsu's method in the second stage of development, and feature extraction was achieved using Grey Level Co-occurrence Matrix (GLCM). Finally, the two classifiers are used to classify lung malignant images, and the accuracy of their classifications is compared and recorded.

In compact Kaehlerian manifolds, Izumi and Kazanan [1] computed and defined infinitesimal holomorphically projective transformations. Transformations holomophic ammeters projective equivalentes have also been researched by Malave Guzman [2]. Following that, Negi [3] investigated and explored certain issues related to pseudo-analytic vectors on pseudo-Kaehlerian Manifolds. In nearly Kaehlerian spaces, Negi et al. [4] have defined and established an analytic HP-transformation. We measured and estimated a Kahlerian manifolds associated in  -projective recument Curvature killing vector fields with vectorial fields and their holomophic properties Einsteinian and the constant curvature manifolds are established. The geometrical qualities of the harmonic and scalar curvatures calculated over killing vectorial fields are used to construct Kaehlerian holomorphically projective recurrent curvature manifolds with almost complex structures.

A unidirectional dry rubbing in a low vacuum, regularly separating \(\alpha\)-iron slider from \(\alpha\)-iron specimen generated a layer of piled-up adhered wear debris whose thickness was more than 100 \(\mu\)m. TEM diffraction patterns taken from this layer consist of large spots and halo rings. This seems to demonstrate the state just before the perfect amorphization. All the rings and spots correspond to the structure formed due to the occupancy of iron atoms in O and T sites of \(\varepsilon\)-iron. Neither this way of amorphization nor the occupied structure mentioned above has been reported. Both the amorphous state and the occupied structure remain at ambient conditions. The mechanism of high-pressure generation that transformed \(\alpha\)-iron to \(\varepsilon\)-iron is presented.

The junction of sections on rigid and non- rigid road pavement is a source of severe load. In course of time residual strain causes the formation of subsidence in road surface. This is not significant defect of road pavement but it has a negative impact on driving comfort. This effect reveals itself not only for road pavement damaged by overloading. The unavailability of verification and quality control during work is not considered to be a reason of the problem. It is based on the internal physical processes that occur in the junction of sections on rigid and non- rigid road pavement under wheel loading. The issue under discussion in this article is related to the problem of the formation of non-rigid road pavement subsidence in the junction of sections of rigid and non-rigid road pavement. Subsidence at the junction of the pavement most often occurs in the area of bridge approach. The subsidence of the non-rigid road pavement can later lead to the formation of pits on the road. The reason for the formation at non-rigid road pavement subsidence is irregularities in the procedure, suffusion. It is necessary to consider the degree of impact not only of the amount of load from the wheel, but also its direction.

The research subject is in the sphere of road construction and maintenance. The article analyzes the causes of the subsidence formation at approach section from non-rigid to hard road pavement. The reasons for the phenomenon of this drawdown have not been studied. There is no clear idea of the nature of appearance of mould and its structure at the boundary between the rigid and non-rigid pavement.

In the reviewed articles, a large amount of attention is paid to the comprehensive study of the transition from fracture to tension to fracture associated with soil stability problems [1,2], the creation of composite materials based on them [3,4]. When calculating pavement, the formation of subsidence is determined based on the application of loads on the surface of the coating [5,6]. The subjects of preventing the occurrence of subsidence are given a lot of attention when strengthening both base soils and coating materials so as to increase the bearing capacity [7]. Different types of impact on structures under the influence of external environmental factors, such as water-thermal [8], aggressive media [9] are also widely studied. The work of the material under various hydraulic regimes of free water in soils has been the subject of many articles [10-13], and the calculation is carried out using half-space methods [14,15,16], without taking into account the indispensable component as a load motion vector. The loads used in the calculations are static. The study of this issue is increasingly moving away from the consideration of the root causes of formation. It delves into the process of improving existing materials [17-20]. This circumstance prompted an in-depth study of the question on the causes of the appearance of mould at the pavement of rigid and non-rigid pavement.  

The problem of azimuth-only calculation of target course angle with a single station is studied independent of time parameter. On a two-dimensional plane, for a uniform moving target in a straight line, if a stationary single station is assumed to be able to obtain the azimuth information of the target three times in a row with equal spacing in the moving path of the target, then the analytic expression of the course angle of the target can be obtained in a simple mathematical form by directly using trigonometric functions. The error analysis shows that the measuring accuracy of target course angle based on trigonometric function method is suitable for engineering application.

Recently, Deep Learning [1] models are used primarily in Object Detection algorithms because of their specific capability for Image Recognition. These models identify items present in input images and videos [2] by extracting features from them. These models have a variety of applications, which include Image Processing, Video analysis, Speech Recognition, Biomedical Image Analysis, Biometric Recognition, Iris Recognition, National Security applications, Cyber Security, Natural Language Processing [3], Weather Forecasting applications, Renewable Energy Generation Scheduling etc. The Convolution Neural Network (CNN) [3], which comprises many artificial neuron layers, is employed for these models. The accuracy of Deep Learning models is determined by a number of factors, including the learning rate, the training batch size, the validation batch size, the activation function, and the drop-out rate. Hyper-Parameters are the name for these parameters. The accuracy of Object Detection depends on the choice of Hyper-Parameters. It is therefore a difficult task to find the best values for these parameters. Fine-Tuning is a method for selecting an effective Hyper-Parameter for improving Object Detection precision.

Selecting an inaccurate Hyper-Parameter value, leads to Over-Fitting or Under-Fitting of data. Over-Fitting is a problem, when training data is greater than the necessary, leading to learning noise and inaccurate Object Detection [4]. Under-Fitting occurs when a model is unable to capture the data's trend, resulting in more erroneous testing or training outcomes.

By changing the ‘Learning rate' of various Deep Learning Models, a balance between Over-Fitting and Under-Fitting is reached in this article. For experimentation purpose, this paper considers four Deep Learning Models such as VGG-16, VGG-19, InceptionV3 and Xception. In terms of maximal Object Detection accuracy, the best zone of Learning-rate for each model is analyzed.  The prediction accuracy of a dataset of 70 object classes is investigated in this study by adjusting the ‘Learning-Rate' while keeping the rest of the Hyper-Parameters fixed.This article focuses on the impact of ‘Learning-Rate' on accuracy in Object Detection and identifies an ideal accuracy zone.  This analysis helps in reduction of computational effort in calculation of Objection Detection Accuracy.