Quality Measurement for Mobile M-ERP Applications

Mobile business boosting the popularization of the M-ERP(Mobile ERP) in the enterprise: The high penetration of mobile phones enables each employee to become an effective information carrier of the enterprise. The information application of the enterprise becomes more clear-cut. The mobile M-ERP pivots on the frequently changing key indexes of the enterprise operation, and takes the personalized and format-based data collection, analysis and processing platform as tool. It consolidates and unifies quickly diverse people, internal data, and external applications of the enterprise into an integrated whole, and provides real-time, key, and overall data reports to the management personnel. The recent wave of enterprise resource planning (M-ERP) systems adoption is a significant commitment of resource and may affect almost all business processes. M-ERP systems are integrated systems in that they promote cooperation among groups, teamwork, and process expertise and business knowledge. Firm that successfully implements an M-ERP system should raise revenues or decrease costs. The main purpose of this paper is to investigate the relationship among M-ERP system internal control, quality and performance in Korean firms. To investigate the relationship, the questionnaires were collected from 131 M-ERP – adopting Korean manufacturing companies. The following results were determined by verifying six hypotheses using LISREL. Internal control support perceived quality and quality support perceived performance. We expect that the results of the research can be used as the guidance of the implementation strategy of M-ERP systems. And these results provide important insights that complement extant research findings and also raise future research issues

Development of smart talking plant with voice recognition function

Plants can tell us what is affecting them with the electrical signals they emit with the help of (Internet of things) IoT.In such ways that is your plant thriving under current light levels? Is your plant thirsty? Or even satisfy with your care? The goal this project is to encourage a happy relationship between plants and people as a lot of people are afraid of plants. Not they are not green handed. The idea of taking good care is a responsibility. This makes it possible for them to have a plant in their lives. As Arduino came into the picture in bringing a better solution for plant care, we proposed an ideal smart plant based on an existing system that will add more features to it to make an all in one architecture. We also presented some useful projects related to this for comparison and future references

Domain model as problem-oriented architecture application for mobile applications

Domain modeling is an activity that develops a generic model of a family of systems. It has been considered as one of the significant activities in systematic reuse. Frameworks can be used for allowing the design layers, permitting the construction of an intricate structures and reusing development information. In this paper, we will discuss the domain modeling supporting tool that extracts candidate domain model objects to construct frameworks from domain descriptions in a typical text form

A STUDY ON AUTONOMOUS DRIVING ADAPTIVE SIMULATION SYSTEM USING DEEP LEARNING MODEL YOLOV3

For the safety of autonomous vehicles, it is not necessary that the human driver does not have much trouble detecting other vehicles and maintaining a certain distance between them, but in the case of autonomous vehicles, that's not an easy task. The problem of detecting and recognizing the front state of autonomous vehicles is known as object detection by Yolov3 bounding boxes. Therefore, we propose this study to avoid accidents before they occur due to autonomous driving on the road and for a better future.  Our purpose in this study is to put autonomous vehicles on the road in practice using Simulink Matlab, and it is a reflection on the ability of autonomous vehicles to ensure curve road safety And to quickly determine responses on curve road situations such as acceleration/deceleration, stopping, and keeping the same speed direction so that better decisions can be made quickly. Simulation represents a possible solution by enabling the creation of reliable bounding boxes, as a first step, in this study, we discuss the feasibility of a simulation framework to detect the speed of different autonomous vehicles using Yolov3 in the real world. We first developed the YOLOV3 algorithm for autonomous vehicle image recognition using the dataset from the Matlab site. The YOLO v3 model, with an optimal performance compared to the performances of deep learning algorithms, is applied. The training parameters are refined through experiments and in the second part we proposed an effective system using "Vision Vehicle Detector test brake adapter" adaptive HighwayLaneFollowingTestBench/Simulation 3D Scenario to prepare Matlab Simulink simulation environment and sensors, Vision Vehicle Detector. The training parameters are refined through experiments. The vehicle detection rate is approximately 95.8% As per our best knowledge, as a result of the experiment, the proposed system has shown favorable results.For the safety of autonomous vehicles, it is not necessary that the human driver does not have much trouble detecting other vehicles and maintaining a certain distance between them, but in the case of autonomous vehicles, that's not an easy task. The problem of detecting and recognizing the front state of autonomous vehicles is known as object detection by Yolov3 bounding boxes. Therefore, we propose this study to avoid accidents before they occur due to autonomous driving on the road and for a better future.  Our purpose in this study is to put autonomous vehicles on the road in practice using Simulink Matlab, and it is a reflection on the ability of autonomous vehicles to ensure curve road safety And to quickly determine responses on curve road situations such as acceleration/deceleration, stopping, and keeping the same speed direction so that better decisions can be made quickly. Simulation represents a possible solution by enabling the creation of reliable bounding boxes, as a first step, in this study, we discuss the feasibility of a simulation framework to detect the speed of different autonomous vehicles using Yolov3 in the real world. We first developed the YOLOV3 algorithm for autonomous vehicle image recognition using the dataset from the Matlab site. The YOLO v3 model, with an optimal performance compared to the performances of deep learning algorithms, is applied. The training parameters are refined through experiments and in the second part we proposed an effective system using "Vision Vehicle Detector test brake adapter" adaptive HighwayLaneFollowingTestBench/Simulation 3D Scenario to prepare Matlab Simulink simulation environment and sensors, Vision Vehicle Detector. The training parameters are refined through experiments. The vehicle detection rate is approximately 95.8% As per our best knowledge, as a result of the experiment, the proposed system has shown favorable results

Acetylation changes tau interactome to degrade tau in Alzheimer’s disease animal and organoid models

© 2019 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.Alzheimer's disease (AD) is an age-related neurodegenerative disease. The most common pathological hallmarks are amyloid plaques and neurofibrillary tangles in the brain. In the brains of patients with AD, pathological tau is abnormally accumulated causing neuronal loss, synaptic dysfunction, and cognitive decline. We found a histone deacetylase 6 (HDAC6) inhibitor, CKD-504, changed the tau interactome dramatically to degrade pathological tau not only in AD animal model (ADLPAPT) brains containing both amyloid plaques and neurofibrillary tangles but also in AD patient-derived brain organoids. Acetylated tau recruited chaperone proteins such as Hsp40, Hsp70, and Hsp110, and this complex bound to novel tau E3 ligases including UBE2O and RNF14. This complex degraded pathological tau through proteasomal pathway. We also identified the responsible acetylation sites on tau. These dramatic tau-interactome changes may result in tau degradation, leading to the recovery of synaptic pathology and cognitive decline in the ADLPAPT mice11Nsciescopu

Video Browsing Service for U-health Care Systems Environments

Recently, Digital video is one of the important information media delivered on the Internet and playing an increasingly important role in multimedia. This paper proposes a Video Browsing Service(VBS) that provides both the video content retrieval and the video browsing by the real-time user interface on Web. For the scene segmentation and key frame extraction of video sequence, we proposes an efficient scene change detection method that combines the RGB color histogram with the χ 2 (Chi Square) histogram. Resulting key frames are linked by both physical and logical indexing. This system involves the video editing and retrieval function of a VCR's. Three elements that are the date, the field and the subject are used for video browsing. A Video Browsing Service is implemented with MySQL, PHP and JMF under Apache Web Server