Enterprise Resource Planning system and its impact on tourism companies' operational performance

Abstract Purpose: The purpose of this study was to find out the relationship between applying the Enterprise Resource Planning system and operational performance, and to develop proposed framework to achieve the requirements of the ERP system, in addition, to measure its availability within tourism companies. Research methodology: The study design is a qualitative study. Data are presented in descriptive form, with in-depth and adaptable analysis. Sample Collection by intentional sampling, the sample chosen depends on the study objectives without regard to the ability of a generalist. The study was based on the distribution of a survey list on a random sample of employees of tourism companies in Egypt. Results: The structural equation modeling results indicate that all the employed dimensions to gauge the impact of ERP system (represented by the components of the system), have direct influence and an indirect impact on the operational performance and then access to the quality of tourism service provided. These findings help to explain the mixed discoveries in the literature concerning the pattern of the causal relationship between ERPs with operational performance and service quality. Limitation: The field study data were collected from survey forms from May to July 2019. Three hundred thirty questionnaire forms were distributed, 310 usable replies were received with a response rate of 93.9%. Contribution: Enterprise Resource Planning (ERP) system has received considerable attention in the last years. Many organizations seek to integrate their IT infrastructures by implementing the Enterprise Resource Planning system (ERP). So implementing ERP system helps tourism companies in raising performance rates through reducing the time to do more business, reducing cost, increasing productivity, which leads to higher performance rates. Keywords: Enterprise Resource Planning system, ERP business value, ERP benefits, Operational performanc

A Robust Object Detection System for Driverless Vehicles through Sensor Fusion and Artificial Intelligence Techniques

Since the early 1990s, various research domains have been concerned with the concept of autonomous driving, leading to the widespread implementation of numerous advanced driver assistance features. However, fully automated vehicles have not yet been introduced to the market. The process of autonomous driving can be outlined through the following stages: environment perception, ego-vehicle localization, trajectory estimation, path planning, and vehicle control. Environment perception is partially based on computer vision algorithms that can detect and track surrounding objects. The process of objects detection performed by autonomous vehicles is considered challenging for several reasons, such as the presence of multiple dynamic objects in the same scene, interaction between objects, real-time speed requirements, and the presence of diverse weather conditions (e.g., rain, snow, fog, etc.). Although many studies have been conducted on objects detection performed by autonomous vehicles, it remains a challenging task, and improving the performance of object detection in diverse driving scenes is an ongoing field. This thesis aims to develop novel methods for the detection and 3D localization of surrounding dynamic objects in driving scenes in different rainy weather conditions. In this thesis, firstly, owing to the frequent occurrence of rain and its negative effect on the performance of objects detection operation, a real-time lightweight deraining network is proposed; it works on single real-time images separately. Rain streaks and the accumulation of rain streaks introduce distinct visual degradation effects to captured images. The proposed deraining network effectively removes both rain streaks and accumulated rain streaks from images. It makes use of the progressive operation of two main stages: rain streaks removal and rain streaks accumulation removal. The rain streaks removal stage is based on a Residual Network (ResNet) to maintain real-time performance and avoid adding to the computational complexity. Furthermore, the application of recursive computations involves the sharing of network parameters. Meanwhile, distant rain streaks accumulate and induce a distortion similar to fogging. Thus, it could be mitigated in a way similar to defogging. This stage relies on a transmission-guided lightweight network (TGL-Net). The proposed deraining network was evaluated on five datasets having synthetic rain of different properties and two other datasets with real rainy scenes. Secondly, an emphasis has been put on proposing a novel sensory system that achieves realtime multiple dynamic objects detection in driving scenes. The proposed sensory system utilizes a monocular camera and a 2D Light Detection and Ranging (LiDAR) sensor in a complementary fusion approach. YOLOv3- a baseline real-time object detection algorithm has been used to detect and classify objects in images captured by the camera; detected objects are surrounded by bounding boxes to localize them within the frames. Since objects present in a driving scene are dynamic and usually occluding each other, an algorithm has been developed to differentiate objects whose bounding boxes are overlapping. Moreover, the locations of bounding boxes within frames (in pixels) are converted into real-world angular coordinates. A 2D LiDAR was used to obtain depth measurements while maintaining low computational requirements in order to save resources for other autonomous driving related operations. A novel technique has been developed and tested for processing and mapping 2D LiDAR measurements with corresponding bounding boxes. The detection accuracy of the proposed system was manually evaluated in different real-time scenarios. Finally, the effectiveness of the proposed deraining network was validated in terms of its impact on objects detection in the context of de-rained images. Results of the proposed deraining network were compared to existing baseline deraining networks and have shown that the running time of the proposed network is 2.23× faster than the average running time of baseline deraining networks while achieving 1.2× improvement when tested on different synthetic datasets. Moreover, tests on the LiDAR measurements showed an average error of ±0.04m in real driving scenes. Also, both deraining and objects detection are jointly tested, and it was demonstrated that performing deraining ahead of objects detection caused 1.45× enhancement in the object detection precision

Abnormal ciliogenesis in decidual stromal cells in recurrent miscarriage(習慣流産における子宮脱落膜間質細胞の繊毛形成異常)<内容の要旨及び審査結果の要旨>

名古屋市立大学令和4年

Detection, Disease Severity and Chlorophyll Prediction of Date Palm Leaf Spot Fungal Diseases

Date palm leaves are infected with the fungal pathogens genus viz., Alternaria, Curvularia, Aspergillius and Neoscytalidium causing leaf spot diseases. The evaluation of chlorophyll content in the infected seedlings possibly could provide a good indicator for a degree of disease or infection, and changes during pathogenesis. Date palm seedlings at three-month-old were infected with 6 pathogenic fungal inoculums were tested. Disease severity% (DS%) and chlorophyll (Chl) contents using a single-photon avalanche diode (SPAD) meter were recorded at 15. 30 and 45 days after inoculation. Pearson's correlation analysis, Durbin Watson and regression analysis were performed to evaluate the relationship between the variables. It was found that the relationship between DS% with fungi, chlorophyll and days were in multiple regression models (R2 =91.88 and 91.87%, respectively). While, the relationship between chlorophyll with fungi, DS% and days were in multiple regression models (R2 =92.22 and 92.20%, respectively). The SPAD chlorophyll value could be considered as a better alternative over the DS% as the SPAD chlorophyll value was strongly related to DS%, as well as able to detect physiological changes in the infected date palm at the early stages of leaf spot pathogenesis. The aim of this study was to examine the possibility of the relationship between disease severity % with fungi, chlorophyll and days for the detection and quantification of date palm leaf spot diseases This is the first research study done to study the relationship between DS%, chlorophyll and time on date palm leaf spot fungal diseases

The Criminal Contribution to the Crime of Attempting to Change the Constitution of a Country: A Comparative Study

إن القاعدة العامة في الاشتراك الجرمي تقضي بأن يتم فعل الاشتراك بنية المساهمة في الجريمة محل الاشتراك ووقوع الجريمة بناءً على ذلك, وهو ما يعبر عنه بعلاقة السببية بين فعل الاشتراك ووقوع الجريمة, إلاّ أن المشرع في الجريمة محل البحث قد خرج عن القواعد العامة للاشتراك وعده جريمة مستقلة ولو لم تقع الجريمة محل الاشتراك .The general rule in criminal participation is that Participation with the intention of contributing to the crime subject to participation and the occurrence of the crime accordingly, which is expressed by the causal relationship between the act of participation and the occurrence of the crime, except that the legislator in the crime under study has deviated from the general rules of participation and is considered an independent crime even if the running did not occur The subject of subscription.&nbsp

Comparative full genome sequence analysis of wild-type and chicken embryo origin vaccine-like infectious laryngotracheitis virus field isolates from Canada

Infectious laryngotracheitis (ILT), caused by infectious laryngotracheitis virus (ILTV), occurs sporadically in poultry flocks in Canada. Live attenuated chicken embryo origin (CEO) vaccines are being used routinely to prevent and control ILTV infections. However, ILT outbreaks still occur since vaccine strains could revert to virulence in the field. In this study, 7 Canadian ILTV isolates linked to ILT outbreaks across different time in Eastern Canada (Ontario; ON and Quebec; QC) were whole genome sequenced. Phylogenetic analysis confirmed the close relationship between the ON isolates and the CEO vaccines, whereas the QC isolates clustered with strains previously known as CEO revertant and wild-type ILTVs. Recombination network analysis of ILTV sequences revealed clear evidence of historical recombination between ILTV strains circulating in Canada and other geographical regions. The comparison of ON CEO clustered and QC CEO revertant clustered isolates with the LT Blen® CEO vaccine reference sequence showed amino acid differences in 5 and 12 open reading frames (ORFs), respectively. Similar analysis revealed amino acid differences in 32 ORFs in QC wild-type isolates. Compared to all CEO vaccine strains in the public domain, the QC wild-type isolates showed 15 unique mutational sites leading to amino acid changes in 13 ORFs. Our outcomes add to the knowledge of the molecular mechanisms behind ILTV genetic variance and provide genetic markers between wild-type and vaccine strains

A Lightweight Network for Real-Time Rain Streaks and Rain Accumulation Removal from Single Images Captured by AVs

In autonomous driving, object detection is considered a base step to many subsequent processes. However, object detection is challenged by loss in visibility caused by rain. Rainfall occurs in two main forms, which are streaks and streaks accumulations. Each degradation type imposes different effect on the captured videos; therefore, they cannot be mitigated in the same way. We propose a lightweight network which mitigates both types of rain degradation in real-time, without negatively affecting the object-detection task. The proposed network consists of two different modules which are used progressively. The first one is a progressive ResNet for rain streaks removal, while the second one is a transmission-guided lightweight network for rain streak accumulation removal. The network has been tested on synthetic and real rainy datasets and has been compared with state-of-the-art (SOTA) networks. Additionally, time performance evaluation has been performed to ensure real-time performance. Finally, the effect of the developed deraining network has been tested on YOLO object-detection network. The proposed network exceeded SOTA by 1.12 dB in PSNR on the average result of multiple synthetic datasets with 2.29× speedup. Finally, it can be observed that the inclusion of different lightweight stages works favorably for real-time applications and could be updated to mitigate different degradation factors such as snow and sun blare

Autoxidation of 4-Hydrazinylquinolin-2(1H)-one; Synthesis of Pyridazino[4,3-c:5,6-c′ ]diquinoline-6,7(5H,8H)-diones

An efficient synthesis of a series of pyridazino[4,3-c:5,6-c′]diquinolines was achieved via the autoxidation of 4-hydrazinylquinolin-2(1H)-ones. IR, NMR ($^1$H and $^13$C), mass spectral data, and elemental analysis were used to fit and elucidate the structures of the newly synthesized compounds. X-ray structure analysis and theoretical calculations unequivocally proved the formation of the structure. The possible mechanism for the reaction is also discussed

Autoxidation of 4-Hydrazinylquinolin-2(1H)-one; Synthesis of Pyridazino[4,3-c:5,6-c′]diquinoline-6,7(5H,8H)-diones

An efficient synthesis of a series of pyridazino[4,3-c:5,6-c′]diquinolines was achieved via the autoxidation of 4-hydrazinylquinolin-2(1H)-ones. IR, NMR (1H and 13C), mass spectral data, and elemental analysis were used to fit and elucidate the structures of the newly synthesized compounds. X-ray structure analysis and theoretical calculations unequivocally proved the formation of the structure. The possible mechanism for the reaction is also discussed

Autoxidation of 4-Hydrazinylquinolin-2(1H)-one; Synthesis of Pyridazino[4,3-c : 5,6-c ']diquinoline-6,7(5H,8H)-diones

An efficient synthesis of a series of pyridazino[4,3-c:5,6-c']diquinolines was achieved via the autoxidation of 4-hydrazinylquinolin-2(1H)-ones. IR, NMR (H-1 and C-13), mass spectral data, and elemental analysis were used to fit and elucidate the structures of the newly synthesized compounds. X-ray structure analysis and theoretical calculations unequivocally proved the formation of the structure. The possible mechanism for the reaction is also discussed.Peer reviewe