Types Of Cars Research Articles

HIGH RESOLUTION CAMERA DESIGN PLANNING THEORETICAL FOUNDATIONS FOR DRIVING SYSTEMS

Background. Analysis of statistical data showed that in most cases the cause of the accident is driver error and, as a consequence, violation of traffic rules. In this regard, over the past 10 years, active developments in the field of recognition of road signs and other obstacles in the path of a car have been actively developing. Car manufacturers offer ready-made built-in systems, mounted behind the interior rearview mirror and connected to the car’s on-board computer, which carries out further control of the car in a critical situation. The main disadvantage of these systems of this class is the low range of recognition of road signs, the dependence of optical parameters on temperature and low light sensitivity. Objective. The purpose of the paper is to model an athermal objective for a high-resolution camera, investigate the characteristics of lenses depending on the ambient temperature. Methods. Analysis and modeling of objectives, lenses, optical glass from different materials. Results. A high-resolution camera objective for all types of cars is proposed. An athermal objective was developed for a high-resolution camera. Conclusions. The optimized athermal design of the visible spectrum objective for long-range car cameras is considered. Car cameras typically have a fixed focus, and forward-facing cameras typically require relatively long focal lengths to provide information about distant objects. The optical system for these cameras should provide high resolution, as well as operate in a wide range of ambient temperatures. The camera design parameters are derived from the functional requirements of road sign recognition at a distance of 200 m. The objective design has five lenses with spherical surfaces. The objective has a relative aperture of f/2 and a modulation transfer function (MTF) of more than 0.5 at 111 l/mm over the entire temperature range.

Empirical Models for the Viscoelastic Complex Modulus with an Application to Rubber Friction

Up-to-date predictive rubber friction models require viscoelastic modulus information; thus, the accurate representation of storage and loss modulus components is fundamental. This study presents two separate empirical formulations for the complex moduli of viscoelastic materials such as rubber. The majority of complex modulus models found in the literature are based on tabulated dynamic testing data. A wide range of experimentally obtained rubber moduli are used in this study, such as SBR (styrene-butadiene rubber), reinforced SBR with filler particles and typical passenger car tyre rubber. The proposed formulations offer significantly faster computation times compared to tabulated/interpolated data and an accurate reconstruction of the viscoelastic frequency response. They also link the model coefficients with critical sections of the data, such as the gradient of the slope in the storage modulus, or the peak values in loss tangent and loss modulus. One of the models is based on piecewise polynomial fitting and offers versatility by increasing the number of polynomial functions used to achieve better fitting, but with additional pre-processing time. The other model uses a pair of logistic-bell functions and provides a robust fitting capability and the fastest identification, as it requires a reduced number of parameters. Both models offer good correlations with measured data, and their computational efficiency was demonstrated via implementation in Persson’s friction model.

Sistem Pendukung Keputusan Pemilihan Mobil Rental dengan Menggunakan Metode Topsis (Studi Kasus : CV. Bita Jaya Mandiri)

Along with the development of the era of demand, to always be fast in doing everything, I can't be avoided from the name of transportation. Transportation is a necessity for everyone alive. The car is one of the negotiated land transportation that is chosen by the people. People who work in the service sector own various types of cars to meet the needs of society. To get a car that meets expectations, of course, the rental tenant / car rental owner must have information about the car. Of the many car choices we can make decisions based on feelings. However, we had difficulty making a decision. Therefore we need a decision support system to help consumers decide which car to rent based on the criteria they want. TOPSIS is a method that can be used in the decision making process. And the products used are Toyota Cars 2000-2014. This method can be used to determine whether the car will be rented according to the qualifications required or not. This is because the method is a step-by-step assessment, both qualitative and quantitative. And TOPSIS is a method of taking into account the tolerance limits for the validity of various criteria chosen by the decision maker.

Vehicle Dimensions Based Passenger Car Classification using Fuzzy and Non-Fuzzy Clustering Methods

There has been globally continuous growth in passenger car sizes and types over the past few decades. To assess the development of vehicular specifications in this context and to evaluate changes in powertrain technologies depending on surrounding frame conditions, such as charging stations and vehicle taxation policy, we need a detailed understanding of the vehicle fleet composition. This paper aims therefore to introduce a novel mathematical approach to segment passenger vehicles based on dimensions features using a means fuzzy clustering algorithm, Fuzzy C-means (FCM), and a non-fuzzy clustering algorithm, K-means (KM). We analyze the performance of the proposed algorithms and compare them with Swiss expert segmentation. Experiments on the real data sets demonstrate that the FCM classifier has better correlation with the expert segmentation than KM. Furthermore, the outputs from FCM with five clusters show that the proposed algorithm has a superior performance for accurate vehicle categorization because of its capacity to recognize and consolidate dimension attributes from the unsupervised data set. Its performance in categorizing vehicles was promising with an average accuracy rate of 79% and an average positive predictive value of 75%.

Can modified components make cars greener? A life cycle assessment

The goal of this study is to evaluate which improvements to car components can most reduce its environmental impacts, narrowing the field to only those currently available on the market. The strategy of the material substitution is the more investigated together with mass reduction, even if the study does not ignore marginally shape optimization, controls, and production processes. Another goal is to discriminate the environmental benefits according to the size of the car and power supply, i.e., gasoline, hybrid and electric.To ensure the reliability and the reproducibility of the results, the study was conducted using the Life Cycle Assessment (LCA) methodology, following the international standards ISO 14040/44, limited to the determination of CO2 eq. Each considered datum was extracted from scientific papers and used within a rigorous structured methodology to calculate the environmental impacts for all the types of car. The functional unit was defined to refer the environmental benefits arising from each improvement of the components to the impacts of the car life cycle normalized for a distance travelled of 100 km in a typical European route.Overall, a reduction in overall car impacts between 7% and 14% was determined by combining all the best alternatives for each analysed component. The major advantage was guaranteed to internal combustion cars and minor to electric cars, while in terms of size, small car benefitted the most. Frame improvement alone provided 51% of the total impact reduction, followed at a distance by that on the bodywork.In conclusion, the study showed how the followed approach can be useful to combine a large amount of different and heterogeneous data while extracting general considerations for automotive eco-design. The structural lightning achieved through material substitution has been fundamental to reduce fuel and energy consumption, and therefore the impacts of the use phase. However, the moderate lightning ensured by aluminium is better than the larger one of carbon fiber and magnesium, whose greater impacts in material extraction, manufacturing, and end-of-life compromise their most sustainable use phase. A further investigation should be deserved to increase control over vehicle condition and driving patterns which resulted valuable options.

Bone Marrow Mesenchymal Stromal Cells Can Render Multiple Myeloma Cells Resistant to Cytotoxic Machinery of CAR T Cells through Inhibition of Apoptosis.

The microenvironment of multiple myeloma (MM) can critically impair therapy outcome, including immunotherapies. In this context, we have earlier demonstrated that bone marrow mesenchymal stromal cells (BMMSC) protect MM cells against the lytic machinery of MM-reactive cytotoxic T cells (CTL) and daratumumab-redirected natural killer (NK) cells through the upregulation of antiapoptotic proteins Survivin and Mcl-1 in MM cells. Here, we investigated the significance of this mode of immune escape on T cells engineered to express chimeric antigen receptors (CAR T cells). We tested the cytolytic ability of a panel of 10 BCMA-, CD38-, and CD138-specific CAR T cells with different affinities against a model MM cell line and against patient-derived MM cells in the presence versus absence of BMMSCs. Although BMMSCs hardly protected MM cells from lysis by high-affinity, strongly lytic BCMA- and CD38-CAR T cells, they significantly protected against lower affinity, moderately lytic BCMA-, CD38-, and CD138-specific CAR T cells in a cell-cell contact-dependent manner. Overall, there was a remarkable inverse correlation between the protective ability of BMMSCs and the lytic activity of all CAR T cells, which was dependent on CAR affinity and type of costimulation. Furthermore, BMMSC-mediated resistance against CAR T cells was effectively modulated by FL118, an inhibitor of antiapoptotic proteins Survivin, Mcl-1, and XIAP. These results extend our findings on the negative impact of the microenvironment against immunotherapies and suggest that outcome of CAR T cell or conventional CTL therapies could benefit from inhibition of antiapoptotic proteins upregulated in MM cells through BMMSC interactions.

3D car shape reconstruction from a contour sketch using GAN and lazy learning

3D car models are heavily used in computer games, visual effects, and even automotive designs. As a result, producing such models with minimal labour costs is increasingly more important. To tackle the challenge, we propose a novel system to reconstruct a 3D car using a single sketch image. The system learns from a synthetic database of 3D car models and their corresponding 2D contour sketches and segmentation masks, allowing effective training with minimal data collection cost. The core of the system is a machine learning pipeline that combines the use of a generative adversarial network (GAN) and lazy learning. GAN, being a deep learning method, is capable of modelling complicated data distributions, enabling the effective modelling of a large variety of cars. Its major weakness is that as a global method, modelling the fine details in the local region is challenging. Lazy learning works well to preserve local features by generating a local subspace with relevant data samples. We demonstrate that the combined use of GAN and lazy learning produces is able to produce high-quality results, in which different types of cars with complicated local features can be generated effectively with a single sketch. Our method outperforms existing ones using other machine learning structures such as the variational autoencoder.

High-Throughput Raman Flow Cytometry and Beyond.

Flow cytometry is a powerful tool with applications in diverse fields such as microbiology, immunology, virology, cancer biology, stem cell biology, and metabolic engineering. It rapidly counts and characterizes large heterogeneous populations of cells in suspension (e.g., blood cells, stem cells, cancer cells, and microorganisms) and dissociated solid tissues (e.g., lymph nodes, spleen, and solid tumors) with typical throughputs of 1,000-100,000 events per second (eps). By measuring cell size, cell granularity, and the expression of cell surface and intracellular molecules, it provides systematic insights into biological processes. Flow cytometers may also include cell sorting capabilities to enable subsequent additional analysis of the sorted sample (e.g., electron microscopy and DNA/RNA sequencing), cloning, and directed evolution. Unfortunately, traditional flow cytometry has several critical limitations as it mainly relies on fluorescent labeling for cellular phenotyping, which is an indirect measure of intracellular molecules and surface antigens. Furthermore, it often requires time-consuming preparation protocols and is incompatible with cell therapy. To overcome these difficulties, a different type of flow cytometry based on direct measurements of intracellular molecules by Raman spectroscopy, or "Raman flow cytometry" for short, has emerged. Raman flow cytometry obtains a chemical fingerprint of the cell in a nondestructive manner, allowing for single-cell metabolic phenotyping. However, its slow signal acquisition due to the weak light-molecule interaction of spontaneous Raman scattering prevents the throughput necessary to interrogate large cell populations in reasonable time frames, resulting in throughputs of about 1 eps. The remedy to this throughput limit lies in coherent Raman scattering methods such as stimulated Raman scattering (SRS) and coherent anti-Stokes Raman scattering (CARS), which offer a significantly enhanced light-sample interaction and hence enable high-throughput Raman flow cytometry, Raman imaging flow cytometry, and even Raman image-activated cell sorting (RIACS). In this Account, we outline recent advances, technical challenges, and emerging opportunities of coherent Raman flow cytometry. First, we review the principles of various types of SRS and CARS and introduce several techniques of coherent Raman flow cytometry such as CARS, multiplex CARS, Fourier-transform CARS, SRS, SRS imaging flow cytometry, and RIACS. Next, we discuss a unique set of applications enabled by coherent Raman flow cytometry, from microbiology and lipid biology to cancer detection and cell therapy. Finally, we describe future opportunities and challenges of coherent Raman flow cytometry including increasing sensitivity and throughput, integration with droplet microfluidics, utilizing machine learning techniques, or achieving in vivo flow cytometry. This Account summarizes the growing field of high-throughput Raman flow cytometry and the bright future it can bring.

Automotive Body Shop Design Problems Using Meta-Models Considering Product-Mix Change and Reconfiguration Strategy

The estimation of production rate (or throughput) is important in manufacturing system design. Herein, we consider the manufacturing system of an automotive body shop in which two types of car are produced, and one car (engine car) is substituted by the other car (electric car) gradually. In this body shop, two different underbody lines are installed because the underbody structures of the two types of cars differ completely; however, the side body line and main body line are shared by the two cars. Furthermore, we assume that the underbody lines are reconfigurable based on an increase in the product mix of the electric car. A simulation-based meta-model, which is in the form of a quadratic polynomial function, is developed to estimate the production rate. In the meta-modelling process, we group some buffer locations and represent them as one variable to reduce the number of variables included in the meta-model. Subsequently, the meta-models have been used to optimize two types of buffer allocation problems, and optimal solutions are obtained easily.

Application of Electronic Diagnosis Technology in New Energy Vehicle Maintenance

With the continuous development of modern society and economy, the speed of new energy vehicles is also rapid, and the number is increasing rapidly. To determine the fault content in a short period of time during maintenance of this type of car, the application of electronic diagnostic technology is essential. This article summarizes the advantages of applying electronic diagnostic technology in the maintenance of new energy vehicles based on previous work experience. The author discusses the specific aspects of electronic diagnosis technology in the maintenance of new energy vehicles from four aspects: application in chassis output power detection, application in automobile circuit maintenance, application in automobile electric motor maintenance, and application in automobile power battery maintenance application content.

Road Overbridges of Car Lift Type for Crossing Railway Tracks in Densely Built-Up Areas of Modern Cities

The theoretical prerequisites for construction of road overbridges of car lift type for crossing railways by automotive vehicles are suggested. A technical solution has been proposed that makes it possible to ensure the crossing by cars of «problem» railway crossings during periods of their long-term closure for road traffic. The same solution can be used to organise a road overbridge in other locations where there is no railway crossing. The technical solution itself is based on the use of overhead road overpasses and is a «simplified» version of the solution implemented by Elon Musk and his company in Los Angeles based on a tunnel, moving platforms and freight elevators. For development of car lift type road overbridges, computational methods of theoretical mechanics, technical diagnostics and monitoring, as well as the theory of queuing should be used to estimate the number of cars passed through it when crossings are closed. It is proposed that the structures of the overbridge should be «built-in» into the landscape, equipped with alternative sources of energy supply and technical means of control, diagnostics and monitoring of rolling stock and of location of direct intersection of automobile and railway roads (an intelligent monitoring zone). The proposed promising technical solution in the form of a road overbridge makes it possible to increase comfort of road transportation and improve traffic safety at level crossings.

Revisiting the CompCars Dataset for Hierarchical Car Classification: New Annotations, Experiments, and Results.

We address the task of classifying car images at multiple levels of detail, ranging from the top-level car type, down to the specific car make, model, and year. We analyze existing datasets for car classification, and identify the CompCars as an excellent starting point for our task. We show that convolutional neural networks achieve an accuracy above 90% on the finest-level classification task. This high performance, however, is scarcely representative of real-world situations, as it is evaluated on a biased training/test split. In this work, we revisit the CompCars dataset by first defining a new training/test split, which better represents real-world scenarios by setting a more realistic baseline at 61% accuracy on the new test set. We also propagate the existing (but limited) type-level annotation to the entire dataset, and we finally provide a car-tight bounding box for each image, automatically defined through an ad hoc car detector. To evaluate this revisited dataset, we design and implement three different approaches to car classification, two of which exploit the hierarchical nature of car annotations. Our experiments show that higher-level classification in terms of car type positively impacts classification at a finer grain, now reaching 70% accuracy. The achieved performance constitutes a baseline benchmark for future research, and our enriched set of annotations is made available for public download.

Pricing and Investment Decision Issues of an Automobile Manufacturer for Different Types of Vehicles

With the raise of consumers’ environmental awareness, automobile manufacturers try to add production lines of new energy vehicles. This paper deals with pricing and investment decision issues of an automobile manufacturer for different types of cars. The consumers’ purchase preference for the new energy vehicle is formulated as a function of the manufacturer’s investment on facility and advertisement. Aiming to maximize the total profit of the manufacturer, we construct a decision model. By solving a differential equation, a necessary condition is proposed for guaranteeing that the manufacturer produces and sells both of the two types of vehicles. It is shown that both the consumers’ preference and the carbon tax affect the decisions of the manufacturer. For the possible scenarios in which the manufacturer only sells one kind of product, we present two simplified models. By comparing different achieved solutions, the optimal decision strategy is achieved. Finally, we show a numerical illustration to examine different decisions of the manufacturer under different sensitivity coefficients with regard to the investment. The main contribution of this paper is providing a jointly pricing and investment decision model under changeable consumers’ purchase preference, and revealing the influence factors of the automobile manufacturer’s transformation.

Study of a New Type of Electric Car: Solar-Powered Car

This article shows the difference between solar-powered cars and pure electric cars, the advantages of using solar panels to provide electricity as well as the distance range increased by converting sunlight into electricity. I also discuss and give some reasons that solar-powered cars can be expected to become widespread in the future.

Disturbance Decoupling and Tracking Controller Design for Lateral Vehicle Dynamics

This paper addresses an augmented nonlinear lateral vehicle and lane keeping dynamics in the presence of some unknown disturbances. In a geometric basin, considering unobservable spaces, their orthogonal complements, and using control invariant properties, a disturbance decoupling mechanism is designed for the mentioned dynamics. Afterward, a nonlinear tracking controller is designed to steer the vehicle on a reference path. The obtained disturbance decoupling and tracking controllers are implemented on a typical passenger car in a simulation environment to demonstrate the effectiveness and performance of the proposed method. It is shown that the controller decouples both the uniformly distributed and exponentially attenuated disturbances from the output.

Influence of road conditions on vehicles’ fuel consumption

The article deals with the influence of road conditions on fuel consumption by vehicles when transporting goods and passengers, which depends on the speed of movement. The optimum fuel consumption corresponds to the optimum speed of movement which is distinctive for each type of car. Increase or decrease of the optimum speed leads to increased fuel consumption. Elevations reduce the speed and increase fuel consumption by up to 30%. Road conditions (width of roadway, condition of surface, presence of horizontal curves, longitudinal slopes, pedestrian crossings, settlements) cause a change in the speed of movement and consumption of fuel and lubricants. It is possible to take into account the road conditions by plotting the speed of movement along the route, the change in the speed occuring during the travel time and socio-economic indicators of the route. Based on this chart, fuel costs and route times are calculated. Since the cost of fuel is 50-52% of the cost of transportation of goods and passengers, the cost will be roughly 2 times higher. The cost of transportation of goods by trucks is characterized by the cost of transportation, and the transportation of passengers by the cost and time spent by passengers when traveling the route.

Balancing Stochastic Mixed-Model Two-Sided Disassembly Line Using Multiobjective Genetic Flatworm Algorithm

The disassembly industry is still labor-intensive, and for the disassembly of products with similar assembly structures, achieving mixed disassembly of these products on the same disassembly line is a more economical solution and very popular in disassembly companies. When large-volume end-of-life (EOL) products are disassembled on the two-sided disassembly line, there is uncertainty in the disassembly time during the disassembly process due to the differences in the recovery quality of EOL products. Therefore, a stochastic mixed-integer programming model is formulated that considers workstation activation cost, workload smoothness index between workstations, and total hazard index considering the order of hazardous task removal. Then, a multi-objective genetic flatworm algorithm is developed in which two different mechanisms for new individual generation are embedded, namely the flatworm genetic operations and the regeneration operations. The effectiveness of the model and the efficiency of the algorithm are verified by the disassembly cases of the printer and the classical mixed-model on the two-sided disassembly line. Finally, the proposed model and algorithm are applied to the disassembly of multiple types of cars, which proves their practical industrial application value.

TROP VOZA KAO SIMBOL TRAUME U KNjIŽEVNOSTI HOLOKAUSTA

Traumatic experience such as the Holocaust requires traumatic ways of representation. Those who dare to write about it encounter various dilemmas and difficulties in finding the right ways to write about something that cannot be written about. Train trope is a usual symbol of the biggest XX century trauma because rail- way system and different types of cars enabled transportation of millions of people from the whole Europe, whose lives were terminated in the death camps, as well as their wealth, gold and other valuables. Trains found their way in literature with both survivor writers and those who didn’t experience the Holocaust. The symbol of train had been interpreted within psychoanalysis of dreams as passage of time and life before it started to operate as a symbol of the very death in reality. In this paper we tried to investigate how train trope functions in this trauma based literary genre with those writers who were inside and those who felt them as cultural heritage. Those who were inside death trains, such as Elie Wiesel, insisted that the only way of representation has to be in documentary and realistic style. On the other hand, writers who were lucky not to experience the hell on Earth couldn’t write from the ‘inside’ and had to find other ways of representation. Their styles vary from allegory in Kosinsi’s autofictional novel to magic realism in David and Thomas’s novels. Thomas also adds Freudian psychoanalysis while Pinter experiments with stage representation.

Разработка каркаса безопасности автомобиля классического семейства для соревнований по зимнему дрифту (предпроектные исследования)

The article presents the results of pre-design studies necessary for the further design of the safety frame for a conventional car type to prepare for winter drift competitions. The collection and analysis of data for the development of the frame was carried out, the main provisions of the official competition regulations of the Russian Automobile Federation for participants of drift competitions were considered.

Проектирование и производство каркаса безопасности автомобиля классического семейства для соревнований по зимнему дрифту (проектно-технологическая часть)

The article presents the development and technological part of design and production of the safety frame for a conventional car type for winter drift competitions. A three-dimensional model of the safety frame was developed, and simulations of the frame behaviour in different situations were carried out.