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Many intelligent transportation systems, such as advanced driver assistance systems (ADAS), have been being developed to increase traffic safety. ADAS have the potential to save lives and reduce crashes by eliminating the human error in driving process. The Lane detection system is designed to identify and estimate the position of lane boundaries in front of the ego-vehicle. Thus, it serves as a crucial and fundamental component in various ADAS, for instance, lane keeping assistance and lane departure warning assistance systems. In this paper, a proposed method of vision-based lane detection in urban roads is presented. First, we define a region of interest to exclude the misleading parts of the road image, then a bird’s-eye view of the road in front of the ego-vehicle is obtained by employing the inverse perspective mapping. Second, we utilize the distinct colors of lane markings to achieve robust lane markings candidate detection. Finally, the estimated lane boundaries are represented by quadratic models whose parameters are estimated from the detected lane pixels using the RANSAC algorithm. Furthermore, we present a thorough evaluation of the performance of the proposed method using the ground-truth data of the Caltech dataset and a comparative analysis between the quadratic model used and other models presented in the literature. Detection results show the effectiveness of the proposed method in detecting lane boundaries in different conditions in urban roads, including curved lanes, shadows, illumination variations and presence of street writings. Moreover, the overall process takes an average time of 30.63 milliseconds per frame.

The power system must be kept safe during load disturbances in order to control frequency instability during load disturbances change. Cascade Controller (CC) is employed to boost the performance of the power system mainly in the presence of nonlinear aspects. As a result, in this study, A proposed cascade fractional order proportional-derivative proportional integral (FOPDPI) controller is used to fine-tune the load frequency control (LFC) subjects of a three-area power system (thermal-thermal-wind) in the interconnected power system (IPS). As a third area in the studied model, renewable energy is used, such as high penetrating power wind turbines. The FOPDPI controller gains are adjusted using a recently published optimization scheme, such as the Harris hawk optimizer (HHO). To thoroughly test the efficiency and fitness of the proposed controller, the HHO-based FOPDPI and conventional PID controllers are applied to a three-area model with/without nonlinearities such as generation rate constraint (GRC), governor dead band (GDB), and boiler dynamics (BD) under different step load perturbation (SLP). The HHO algorithm's cost function is the Integral time multiply absolute error (ITAE) criterion. The investigation reveals that the proposed scheme HHO: FOPDPI provides greater stability than HHO: PID in both linearities by 58% and nonlinearity aspects by 62%.

The pre-processing ‎ ‎ phase‎ is a crucial step to prepare any data for deep considerable ‎ analysis. ‎Genome-wide data ‎is considered ‎ big data; dealing with such data is not an easy task and still poses ‎a significant challenge. The ‎genome-wide association study (GWAS) ‎ is based on enormous high-‎density data with high throughput. This paper has illustrated the main pre-processing ‎ steps on data ‎from North American Rheumatoid Arthritis Consortium ‎‎(NARAC) for preparing it for haplotype ‎block partitioning using different methods and with different platforms. This paper’s main ‎objective is to summarize the steps of pre-processing the raw genotyped dataset to prepare it for ‎haplotype block partitioning and further analyses. Besides, we present each practical step by clear ‎tables for better visualizing, elucidation, and workflow interpretation. Besides, we aimed to ‎overcome the missing data and normalize the output in a standardized format. Eventually, this will ‎improve the understanding of such data formats and build the foundation stone of critical genome-wide experiments and studies. Thus, this work could a guide for other researchers who use similar ‎data. The pre-processed data will be applied to imputation, BigLD block partitioning under R and ‎Haploview methods. Our sequence of ‎pre-processing steps includes preparing the characters to be ‎in a form that is suitable for imputation. The next step is ‎recording data in 0,1,2 format to be ‎proper for the BigLD. We were finally preparing data for Haploview to ‎provide clear haplotype ‎block partitioning, association analysis, and furthermore.‎

This article presents a compact design of a composite-right-left-handed (CRLH) antenna for wireless applications. The antenna is fed using a coplanar waveguide (CPW) feed structure. The CRLH-antenna is comprised of one CRLH unit cell. The CRLH unit cell has a series capacitance (interdigital capacitor) and a shunt inductor (stub meander inductor). The antenna achieves compactness with a small size of 16.5 mm × 26 mm × 1.6 mm, thanks to the CRLH features such as nonlinear phase. The proposed antenna achieves a size reduction of better than 50 % with respect to the microstrip patch antenna operated at the same frequency band. The operating frequency band of the proposed antenna is from 5.83GHz to 6.3 GHz for WLAN applications, dedicated short range communications (DSRC), and intelligent transportation systems (ITS). Also, the antenna fulfills a radiation performance of omnidirectional pattern. To confirm the antenna design performances, a prototype is fabricated, and the reflection coefficient and radiation patterns are measured. Furthermore, the measured results have a good match with the simulation results.

In the last few decades, a Significant advance in the laser detection techniques have occurred in a civilian application like optical fiber communication system, lidar system and now satellite communication in the aerospace and a military application, one of the most applications in military is the laser guided missiles and bombs encountered high development and formed high threat for strategic and special targets. The development of a laser warning system (LWS) is essential to detect the laser guided weapons attack. A classic LWS is composed of an optical subsystem, laser detector, and processing unit. The design of a LWS is constrained by the cost, optical system size, detector type, and the required processing operations. In this paper, a 15-degree field of view optical subsystem, diffraction grating, and a sky camera is used to reduce the whole system size, reduce the cost, and decrease the number of false alarms initiated by the dark current on the classical detectors. The optical subsystem is designed to shape the laser spot diameter to be 350µm to avoid detection saturation. The design and fabrication of the optical system guaranteed a signal-to-noise ratio up to 175dB in a clear atmospheric condition. This LWS outperforms the state-of-art LWSs in laser guided weapon detection.