Pothole Detection under Diverse Conditions using Object Detection Models

One of the most important tasks in road maintenance is the detection of potholes. This process is usually done through manual visual inspection, where certified engineers assess recorded images of pavements acquired using cameras or professional road assessment vehicles. Machine learning techniques are now being applied to this problem, with models trained to automatically identify road conditions. However, approaching this real-world problem with machine learning techniques presents the classic problem of how to produce generalisable models. Images and videos may be captured in different illumination conditions, with different camera types, camera angles, and resolutions. In this paper, we present our approach to building a generalized learning model for pothole detection. We apply four datasets that contain a range of image and environment conditions. Using the Faster RCNN object detection model, we demonstrate the extent to which pothole detection models can generalise across various conditions. Our work is a contribution to bringing automated road maintenance techniques from the research lab into the real-worl

Employee Turnover Intention in Call Center (Punjab) Pakistan

Purpose The purpose of this research was to find out the reasons of employee turnover in call centers of Punjab Pakistan so that the companies could retain their trained work force. Also find out the reasons which are affecting on employee’s turnover intention. The intention of this research is to find out those elements behind the employees turnover intention of job. Design/methodology the target population of this research is Multan and Lahore (Punjab). For getting the response 100 quantities of questionnaire were distributed and with use of application SPSS-18, revile the result on correlation analysis. Research findings the findings of this research identified that that there is negative relationship between the dependent and independent variables. The finding and the recommendation of this research will help the manager to develop a deeper insight of research factor for reducing the employee’s turnover intention Originality/value for determining the employees turnover intention in call center that is original study for newly and existing reader knowledge and there is no any portion of research are copy form anywhere. Implications all the company top level manager/HR manager and marketers of the industry who want to decline the turnover intention can use this research results. Keywords: employee’s turnover, job satisfaction, salary, working conditio

Effectiveness of HIV/AIDS educational intervention in increasing knowledge, attitude and practices for primary school teachers in some part of Africa

Human immunodeficiency virus (HIV) is virus that weakens the immune system of the body through destruction of the white blood cells. Whereas, AIDS term as; acquired immune deficiency syndrome is a disease due to the infection of HIV. Knowledge of health, and practices among teachers of primary school are scanty. Studies indicated that few teachers have heard or even became aware that HIV/AIDS is a viral infectious, and some of them lacked the knowledge about its mode of transmission with low attitudinal behaviours. Thus, this review paper discusses some health promotion measures and relevant information regarding, how the use of educational intervention in primary school teachers, could help in reducing the incidence cases of HIV/AIDS in Africa. We therefore recommend effective educational intervention programmes should be set for primary school teachers, in order that the teachers and the students could have a sound knowledge of health practices that will change their attitude which in turn reduce the risk of HIV/AIDS transmission

Innovativeness of Creative Thinking for Value Creation

The increasing demand to foster creativity in order to enhance value creation has become a global issue. This is because the innovativeness of creative thinking aid the implementing of a new knowledge that supports learning practices. As such, creative thinking is central to innovation leading to value creation. Although there are several issues that confronts creativity from learning to practice, this paper specifically reported the innovativeness associated with creative thinking and provided a structural analogue of the keys to creativity. Furthermore, diversities of creativity were reviewed and the classes of knowledge leading to value creation were reported. Findings showed that a variety of concept possess serious analytical task limiting value creation spurred by innovative creativity. Creative thinking was found to be fundamental to educational processes and serves as an empowerment to value creation

A review on climate change and Malaysia’s actions

One of the biggest global health threats of the 21st century is climate change It is so catastrophic that the climate action has been given a platform as it is the 13th goal of the 17 United Nations Sustainable developmental goals (SDG). This review seeks to understand the factors causing climate change, followed by understanding the impact it has on individual and population health. We also identify the strategies to control and prevent further climate change. Methods: Reviews of local and international articles from the past ten years was conducted. The focus of the review was the causes health effects as well as strategies. Data base used was Pro Quest. Results: This review identified that the main contributor to climate change are man-made activities such as fossil fuels combustion, livestock farming, and deforestation. This change in climate has many repercussions from mass migrations, increase communicable diseases as well as an increase in extreme weather events and natural disasters. All this eventually leads to the deterioration of individual and population health. Strengthening adaptivity to climate-related hazard, climate change integration into national policies, education, awareness-raising, impact reduction and early warning are actions that are present in Malaysia to manage this crisis. Conclusion: Climate change is occurring globally, and its presence can no longer be denied. Actions have been put forth, but only when its importance and impact is taken seriously will the positive changes be sustainable

Detecting Patches on Road Pavement Images acquired with 3D Laser Sensors using Object Detection and Deep Learning

Regular pavement inspections are key to good road maintenance and road defect corrections. Advanced pavement inspection systems such as LCMS (Laser Crack Measurement System) can automatically detect the presence of different defects using 3D lasers. However, such systems still require manual involvement to complete the detection of pavement defects. This paper proposes an automatic patch detection system using object detection technique. To our knowledge, this is the first time state-of-the-art object detection models Faster RCNN, and SSD MobileNet-V2 have been used to detect patches inside images acquired by LCMS. Results show that the object detection model can successfully detect patches inside LCMS images and suggest that the proposed approach could be integrated into the existing pavement inspection systems. The contribution of this paper are (1) an automatic pavement patch detection models for LCMS images and (2) comparative analysis of RCNN, and SSD MobileNet-V2 models for automatic patch detection

Detecting Patches on Road Pavement Images Acquired with 3D Laser Sensors using Object Detection and Deep Learning

Regular pavement inspections are key to good road maintenance and road defect corrections. Advanced pavement inspection systems such as LCMS (Laser Crack Measurement System) can automatically detect the presence of different defects using 3D lasers. However, such systems still require manual involvement to complete the detection of pavement defects. This work proposes an automatic patch detection system using an object detection technique. Results show that the object detection model can successfully detect patches inside LCMS images and suggest that the proposed approach could be integrated into the existing pavement inspection systems.https://arrow.tudublin.ie/cddpos/1016/thumbnail.jp

A hybrid dual-mode trust management scheme for vehicular networks

Vehicular ad-hoc networks allow vehicles to exchange messages pertaining to safety and road efficiency. Building trust between nodes can, therefore, protect vehicular ad-hoc networks from malicious nodes and eliminate fake messages. Although there are several trust models already exist, many schemes suffer from varied limitations. For example, many schemes rely on information provided by other peers or central authorities, for example, roadside units and reputation management centers to ensure message reliability and build nodes’ reputation. Also, none of the proposed schemes operate in different environments, for example, urban and rural. To overcome these limitations, we propose a novel trust management scheme for self-organized vehicular ad-hoc networks. The scheme is based on a crediting technique and does not rely on other peers or central authorities which distinguishes it as an economical solution. Moreover, it is hybrid, in the sense it is data-based and entity-based which makes it capable of revoking malicious nodes and discarding fake messages. Furthermore, it operates in a dual-mode (urban and rural). The simulation has been performed utilizing Veins, an open-source framework along with OMNeT++, a network simulator, and SUMO, a traffic simulator. The scheme has been tested with two trust models (urban and rural). The simulation results prove the performance and security efficacy of the proposed scheme

A survey on sentiment analysis in Urdu: A resource-poor language

© 2020 Background/introduction: The dawn of the internet opened the doors to the easy and widespread sharing of information on subject matters such as products, services, events and political opinions. While the volume of studies conducted on sentiment analysis is rapidly expanding, these studies mostly address English language concerns. The primary goal of this study is to present state-of-art survey for identifying the progress and shortcomings saddling Urdu sentiment analysis and propose rectifications. Methods: We described the advancements made thus far in this area by categorising the studies along three dimensions, namely: text pre-processing lexical resources and sentiment classification. These pre-processing operations include word segmentation, text cleaning, spell checking and part-of-speech tagging. An evaluation of sophisticated lexical resources including corpuses and lexicons was carried out, and investigations were conducted on sentiment analysis constructs such as opinion words, modifiers, negations. Results and conclusions: Performance is reported for each of the reviewed study. Based on experimental results and proposals forwarded through this paper provides the groundwork for further studies on Urdu sentiment analysis

An Exploration of Recent Intelligent Image Analysis Techniques for Visual Pavement Surface Condition Assessment.

Road pavement condition assessment is essential for maintenance, asset management, and budgeting for pavement infrastructure. Countries allocate a substantial annual budget to maintain and improve local, regional, and national highways. Pavement condition is assessed by measuring several pavement characteristics such as roughness, surface skid resistance, pavement strength, deflection, and visual surface distresses. Visual inspection identifies and quantifies surface distresses, and the condition is assessed using standard rating scales. This paper critically analyzes the research trends in the academic literature, professional practices and current commercial solutions for surface condition ratings by civil authorities. We observe that various surface condition rating systems exist, and each uses its own defined subset of pavement characteristics to evaluate pavement conditions. It is noted that automated visual sensing systems using intelligent algorithms can help reduce the cost and time required for assessing the condition of pavement infrastructure, especially for local and regional road networks. However, environmental factors, pavement types, and image collection devices are significant in this domain and lead to challenging variations. Commercial solutions for automatic pavement assessment with certain limitations exist. The topic is also a focus of academic research. More recently, academic research has pivoted toward deep learning, given that image data is now available in some form. However, research to automate pavement distress assessment often focuses on the regional pavement condition assessment standard that a country or state follows. We observe that the criteria a region adopts to make the evaluation depends on factors such as pavement construction type, type of road network in the area, flow and traffic, environmental conditions, and region\u27s economic situation. We summarized a list of publicly available datasets for distress detection and pavement condition assessment. We listed approaches focusing on crack segmentation and methods concentrating on distress detection and identification using object detection and classification. We segregated the recent academic literature in terms of the camera\u27s view and the dataset used, the year and country in which the work was published, the F1 score, and the architecture type. It is observed that the literature tends to focus more on distress identification ( presence/absence detection) but less on distress quantification, which is essential for developing approaches for automated pavement rating