---

Counting the population of insect pests is a key task for planning a successful integrated pest management program. Most image processing and machine vision techniques in the literature are very site-specific and cannot be easily re-usable because their performances are highly related to their ground truth data. In this article a new unsupervised image processing method is proposed which is general and easy to use for non-experts. In this method firstly a hypothesis framework is defined to distinguish pests from other particles in a captured image after texture, color and shape analyses. Then, the decision about each hypothesis is made by estimating a distribution function for sizes of particles which are presented in the image. Performance of the proposed method is evaluated on real captured images that belong to plants in green housesand farms with low and high densities of whiteflies. The obtained results show the greater ability of the proposed method in counting whiteflies on crop leaves compared to adaptive thresholding and K-means algorithms. Furthermore it is shown that better counting of the pest by proposed algorithm not only doesn't lead to extracting more false objects but also it decreases the rate of false detections compared to the results of the alternative algorithms.  

---

One of the challenges in non-destructive testing schemes using the ultrasound pulse-echo technique is to identify those defects whose sizes are less than or equal to the detection resolution that is dependent on the width of the ultrasound pulse. Existing methods also require a reference specimen of the same defective material, which may not be available in some cases. We present a new method for detecting and identifying such defects. In the proposed approach, each layer of the test specimen is modeled as a linear time invariant (LTI) filter, and therefore, each defect is characterized by its corresponding impulse response. We use a combination of time gating and system identification techniques to detect and identify the defects, and as such, do not require a reference specimen. To demonstrate the performance of the proposed approach, we tested metallic blocks in which specific defects were impregnated. Results show that the proposed method can detect such defects, does not depend on the test set-up (including the ultrasound transducer), does not require a reference specimen, and is capable of detecting several defects situated in different depth on top of each other

---

To use higher capacities in Iran's energy transmission systems, API standardized pipes made of API X65 steel have been utilized (made of thermo-mechanically controlled rolling process, TMCR steels). The TMCR inherently increases the anisotropic properties of steel coils and plates used for pipe manufacturing. In addition, the production of helical welded pipe involves steps that can lead to different mechanical properties in different directions. The aim of the present study is to measure the orientation dependence of the Charpy fracture energy. Therefore, the effect of changing the angle of specimens relative to the rolling direction and also the effect of changing the notch orientation (three notch A, B and C in total) on the fracture energy in API X65 steel has been experimentally determined. The maximum change in the average Charpy fracture energy at different angles relative to the rolling direction is a maximum of 13% (in notch B), but the largest change in the average Charpy fracture energy between different notches is a maximum of 12.2% (at an angle of 0 °). As a result, the effect of changing the angle of the specimen relative to the rolling direction is greater than the effect of changing the notch orientation on the Charpy fracture energy. Also, at an angle of 67.5 degrees to the direction of rolling (equivalent to the diagonal direction (D-D)), the most fracture energy for all notches was obtained. To quantitatively compare the fracture energy changes in different notches, an index called anisotropy index has been presented