Adaptive background reconstruction for street surveillance

In recent years, adaptive background reconstruction works have found interest in many researchers. However, the existing algorithms that have been proposed by other researchers still in the early stage of development and many aspects need to be improved. In this paper, an adaptive background reconstruction is presented. Past pixel observation is used. The proposed algorithm also has eliminated the need of the pre-training of non-moving objects in the background. The proposed algorithm is capable of reconstructing the background with moving objects in video sequence. Experimental results show that the proposed algorithms are able to reconstruct the background correctly and handle illumination and adverse weather that modifies the background

Economic Evaluation of Rice IPM Practices in MADA, Malaysia

Environmental protection is a basic element of sustainable agricultural development. Agricultural protection practices however can cause negative externalities. One of main concerns of the externality is the negative effects of pesticide. Concerns on the negative effects of pesticide use have motivated the development of Integrated Pest Management (IPM) programmes. In MADA, Malaysia the IPM collaborative research support programme (CRSP-IPM) was established to specifically address the widespread misuse of pesticides in paddy cultivation, one of the major rice producing regions in the country. An IPM practice in paddy production initiatives includes research on the optimal use of pesticides, complementary weed control strategies, and alternative cultural and biological controls. Results of this study showed that the programme would generate economic benefits which include improvements in water quality, food safety, pesticide application safety, and long term sustainability of pest management systems. A part of savings in environmental costs and the reduction in pesticide use also reduced operating expenses. The calculated economic benefits in terms of aggregate cost savings per season for 454 farmers were MYR756,393 for insecticides, MYR40,537 for herbicides, and MYR94,753 for fungicides. Keywords: IPM, Adoption, Economic evaluatio

Rare Germline Genetic Variants and the Risks of Epithelial Ovarian Cancer.

A family history of ovarian or breast cancer is the strongest risk factor for epithelial ovarian cancer (EOC). Germline deleterious variants in the BRCA1 and BRCA2 genes confer EOC risks by age 80, of 44% and 17% respectively. The mismatch repair genes, particularly MSH2 and MSH6, are also EOC susceptibility genes. Several other DNA repair genes, BRIP1, RAD51C, RAD51D, and PALB2, have been identified as moderate risk EOC genes. EOC has five main histotypes; high-grade serous (HGS), low-grade serous (LGS), clear cell (CCC), endometrioid (END), and mucinous (MUC). This review examines the current understanding of the contribution of rare genetic variants to EOC, focussing on providing frequency data for each histotype. We provide an overview of frequency and risk for pathogenic variants in the known susceptibility genes as well as other proposed genes. We also describe the progress to-date to understand the role of missense variants and the different breast and ovarian cancer risks for each gene. Identification of susceptibility genes have clinical impact by reducing disease-associated mortality through improving risk prediction, with the possibility of prevention strategies, and developing new targeted treatments and these clinical implications are also discussed

Analysis of optimizers on AlexNet architecture for face biometric authentication system

Nowadays, biometric authentication is more important than a password or token-based authentication. There have been many techniques suggested for biometric authentication algorithms, however, it can be observed that the Deep Learning approach is significantly more effective and secure than other methods, specifically Convolutional Neural Networks (CNN) with AlexNet architecture for face recognition. However, an optimization technique is crucial in the Deep Learning models. Therefore, this paper will analyze the best optimizers for AlexNet architecture which are SGD, AdaGrad, RMSProp, AdaDelta, Adam, and AdaMax by using the proposed face dataset includes 7 celebrity classes, each with 35 images obtained from Google Images. To enhance the size of the dataset, data augmentation was employed before it was fed into the AlexNet model. The experiment shows AdaMax performs well when compared to the other optimizers on the proposed dataset

Moving object detection and classification using neuro-fuzzy approach

Public surveillance monitoring is rapidly finding its way into Intelligent Surveillance System. Street crime is increasing in recent years, which has demanded more reliable and intelligent public surveillance system. In this paper, the ability and the accuracy of an Adaptive Neuro-Fuzzy Inference System (ANFIS) was investigated for the classification of moving objects for street scene applications. The goal of this paper is to classify the moving objects prior to its communal attributes that emphasize on three major processes which are object detection, discriminative feature extraction, and classification of the target. The intended surveillance application would focus on street scene, therefore the target classes of interest are pedestrian, motorcyclist, and car. The adaptive network based on Neuro-fuzzy was independently developed for three output parameters, each of which constitute of three inputs and 27 Sugeno-rules. Extensive experimentation on significant features has been performed and the evaluation performance analysis has been quantitatively conducted on three street scene dataset, which differ in terms of background complexity. Experimental results over a public dataset and our own dataset demonstrate that the proposed technique achieves the performance of 93.1% correct classification for street scene with moving objects, with compared to the solely approaches of neural network or fuzzy

Features-based moving objects tracking for smart video surveillances: A review

Video surveillance is one of the most active research topics in the computer vision due to the increasing need for security. Although surveillance systems are getting cheaper, the cost of having human operators to monitor the video feed can be very expensive and inefficient. To overcome this problem, the automated visual surveillance system can be used to detect any suspicious activities that require immediate action. The framework of a video surveillance system encompasses a large scope in machine vision, they are background modelling, object detection, moving objects classification, tracking, motion analysis, and require fusion of information from the camera networks. This paper reviews recent techniques used by researchers for detection of moving object detection and tracking in order to solve many surveillance problems. The features and algorithms used for modelling the object appearance and tracking multiple objects in outdoor and indoor environment are also reviewed in this paper. This paper summarizes the recent works done by previous researchers in moving objects tracking for single camera view and multiple cameras views. Nevertheless, despite of the recent progress in surveillance technologies, there still are challenges that need to be solved before the system can come out with a reliable automated video surveillance

Functional outcomes after internal and external hemipelvectomy in HUSM

Background: Although great advancements have been made in survival rates over the last half century with adjuvant therapies and current surgical techniques, hemipelvectomy as the surgical treatment for pelvic tumours continue to have significant associations with morbidity and complications. Using the Enneking’s criteria as adopted by the Musculoskeletal Tumor Society (MSTS), we evaluated the functional outcomes of patients who have had an internal hemipelvectomy with and without reconstruction, and external hemipelvectomy. Method: We evaluated patients who underwent hemipelvectomy in our institution between 2001 and 2010. Patients who had had an internal or external hemipelvectomy surgery at any point in their clinical course were included in the study. Patients with follow up periods of less than four months were not included. MSTS scores were obtained at various times after the surgery. Results: A total of 50 patients who had undergone various types of resection and reconstruction techniques were included in this study. The average age is 40.1 years (range 12-79). Average duration of follow up is 10 months. The average MSTS percentage score was 44.32% (range: 6.67%-100%). Results show that external hemipelvectomy in our patients have a high morbidity and mortality rate. Various techniques of resection and reconstruction give different functional scores. Conclusion: Hemipelvectomies have a profound impact on patients’ lives as illustrated by their low MSTS scores. Proper patient selection is crucial to obtain the best outcome. This study is an effort to obtain a proper reference for preoperative discussion with patients and relatives regarding expected outcomes following such a procedure

Functional outcomes after internal and external hemipelvectomy in HUSM

Background: Although great advancements have been made in survival rates over the last half century with adjuvant therapies and current surgical techniques, hemipelvectomy as the surgical treatment for pelvic tumours continue to have significant associations with morbidity and complications. Using the Enneking’s criteria as adopted by the Musculoskeletal Tumor Society (MSTS), we evaluated the functional outcomes of patients who have had an internal hemipelvectomy with and without reconstruction, and external hemipelvectomy. Method: We evaluated patients who underwent hemipelvectomy in our institution between 2001 and 2010. Patients who had had an internal or external hemipelvectomy surgery at any point in their clinical course were included in the study. Patients with follow up periods of less than four months were not included. MSTS scores were obtained at various times after the surgery. Results: A total of 50 patients who had undergone various types of resection and reconstruction techniques were included in this study. The average age is 40.1 years (range 12-79). Average duration of follow up is 10 months. The average MSTS percentage score was 44.32% (range: 6.67%-100%). Results show that external hemipelvectomy in our patients have a high morbidity and mortality rate. Various techniques of resection and reconstruction give different functional scores. Conclusion: Hemipelvectomies have a profound impact on patients’ lives as illustrated by their low MSTS scores. Proper patient selection is crucial to obtain the best outcome. This study is an effort to obtain a proper reference for preoperative discussion with patients and relatives regarding expected outcomes following such a procedure

Torrefaction of hydrotreated palm kernel shell and mesocarp fiber mixture

This paper examines the torrefaction of a hydrotreated mixture of palm shell and mesocarp fiber and its physicochemical and thermal properties after torrefaction. The weight ratio was fixed at 60:40 (palm shell to mesocarp fiber) for the untreated and hydrotreated mixture of palm shell and mesocarp fiber. The untreated and hydrotreated mixture was subsequently torrefied from 250 to 300°C. The results revealed that the physical appearance of the untreated and hydrotreated mixture darkened after torrefaction. Higher torrefaction temperature increased the mass loss, fixed carbon, ash and heating value of torrefied products. The ash content of torrefied hydrotreated mixture decreased by 42% (maximum) if compared to the torrefied untreated mixture. Likewise, the heating value of the torrefied hydrotreated mixture (23 MJ/kg) was higher than the untreated mixture. However, the moisture content and volatile matter gradually decreased with increasing torrefaction temperature. The mass loss and volatile matter of the torrefied hydrotreated mixture were considerably improved compared to the torrefied untreated mixture. Overall, the results showed that hydrotreatment resulted in a promising torrefaction end-products. Therefore, combined hydrotreatment and torrefaction is a practical and promising technique for producing low-ash oil palm biomass

Real-time moving objects tracking for distributed smart video surveillances

Tracking the object of interest within a camera's view is essential for crime prevention. This study focuses on analyzing video surveillance in public places. It presents a novel approach to track moving objects across non-overlapping cameras' views that is able to give a consistent label to the objects throughout the whole multi-camera system in real-time. The proposed algorithm is also expected to be able to handle common problems in multiple-camera object tracking including variation of poses, object appearances and occlusion problems. The proposed algorithm was formulated based on visual and temporal cues for multiple cameras using entering/exiting and merging/splitting cases to deal with appearance changes and occlusion problems. Spatial cues are adopted in single-camera object tracking for real-time performance. A novel object segmentation technique based on the observed mask binary value is presented to deal with pose variation across different cameras. In the result section, the comparison between past works and the proposed tracking algorithm are presented. The experimental result