Automatic feature extraction and matching modelling for highly noise near-equatorial satellite images

Feature extraction plays an important role in pattern recognition because band-to-band registration and geometric correction from different satellite images have linear image distortion. However, new near-equatorial orbital satellite system (NEqO) images is different because they have nonlinear distortion. Conventional techniques cannot overcome this type of distortion and lead to the extraction of false features and incorrect image matching. This research presents a new method by improving the performance of the Scale-Invariant Feature Transformation (SIFT) with a significantly higher rate of true extracted features and their correct matching. The data in this study were obtained from the RazakSAT satellite covering a part of Penang state, Malaysia. The method consists of many stages: image band selection, image band compression, image sharpening, automatic feature extraction, and applying the sum of absolute difference algorithm with an experimental and empirical threshold. We evaluate a refined features scenario by comparing the result of the original extracted SIFT features with corresponding features of the proposed method. The result indicates accurate and precise performance of the proposed method from removing false SIFT extracted features of satellite images and remain only true SIFT extracted features, that leads to reduce the extracted feature from using three frame size: (1) from 2000 to 750, 552 and 92 for the green and red bands image, (2) from 678 extracted control points to be 193, 228 and 73 between the green and blue bands, and (3) from 1995 extracted CPs to be 656, 733, and 556 between the green and near-infrared bands, respectively.

272 Effect of Frame Size and Supplementation on Performance and Carcass Characteristics of Beef Cattle Finished on Novel Endophyte-infected Tall Fescue Pastures

Objectives were to investigate the effects of frame score (FS) and supplementation on performance and carcass characteristics of cattle finished on novel endophyte-infected fescue pastures. This 2-yr experiment used 80 Angus-sired, crossbred steers and heifers bred for divergent FS. Cattle were allotted to 5 treatments: 1) non-supplemented small frame (S-NON; FS = 3.0 ± 0.9), 2) supplemented small frame (S-SUPP), 3) non-supplemented large frame (L-NON; FS = 4.7 ± 0.6), 4) supplemented large frame (L-SUPP), and 5) grain-based control feedlot ration (CON; FS = 4.2 ± 0.6; target ADG = 1.36 kg/day). Daily rations were delivered individually using Calan gates. Pasture supplement contained corn gluten feed, a commercially available rumen-protected prilled vegetable fat, and dried molasses fed at 0.5% of BW. Treatments started on 7/8/2019 and 5/21/2020, and ended in November of each yr when cattle were slaughtered at a commercial abattoir. Results were analyzed using PROC MIXED of SAS with main effects of treatment, sire, sex, yr, and yr x treatment, with contrast statements comparing large vs. small frame, pasture supplemented vs. non-supplemented, and control vs. pasture groups. As expected, CON had greater (P < 0.001) growth performance (final BW and ADG) and carcass characteristics (HCW, subcutaneous fat, marbling, dressing percentage (DRESS%) than pasture groups, and tended to have greater (P=0.053) REA. Relative to pasture groups, CON had greater (P < 0.001) Minolta L* and a* lean tissue values, and decreased (P < 0.001) b* values for fat tissue. While non-supplemented cattle had decreased (P = 0.016) yield grades (YG), supplemented cattle had greater (P < 0.050) final BW, ADG, subcutaneous fat, HCW, marbling, and DRESS% compared to non-supplemented cattle. Small framed cattle tender to have decreased (P = 0.056) YG; but, large framed cattle had greater (P = 0.006) HCW, and tended (P = 0.060) to have greater ultrasound subcutaneous fat. Results support low-level supplementation in pasture-finishing systems to improve carcass value.

Accessibility to Reproductive Technologies by Low-Income Beef Farmers in South Africa

This study address historical legacy of South Africa that has dual economies resembling low and high income beef sectors. Low-income herds are farmed mainly under communal village or land reform farms. The study focused on providing assisted reproductive technologies (ARTs) to the low-income sector including finding challenges to its implementation and adoption. The study was conducted in Limpopo, Mpumalanga and KwaZulu-Natal provinces using mixed methods that looked at cows and sectors stakeholders. Data collected and evaluated on cows included breed type, frame size, body condition, age parity, and lactation status. Cows were exposed to ART through synchronisation, oestrus detection, fixed time artificial insemination and pregnancy diagnosis. Qualitative data was collected to study perception of key stakeholders on ART implementation and adoption. Chi-Square Test was computed to determine the association among cow factors. Qualitative data was collected, coded and managed into themes using Nvivo Version 11. Themes that emerged were interpreted using critical social and systems thinking. Conception rate was not independent of provinces (P < 0.05), cow body condition score (BCS) and body frame size. KwaZulu-Natal cows had the highest conception rate at 66% (P < 0.05) than Limpopo (44%) and Mpumalanga (60%) provinces. Cows with a BCS higher than 3.5 had higher conception rate (P < 0.05) than those with BCS of <2.5 and 3. Interestingly, large framed cow size had higher conception rate than medium and small framed (P < 0.05) cows. The study achieved a 100% calf survival rate. Calving rate was influenced by body BCS, province and district (P < 0.05). Calving rate of 58% in Mpumalanga and 54% in KwaZulu-Natal was higher than that recorded in Limpopo at 36% (P < 0.05). Interestingly, cows with BCS of <2.5 had a higher calving rate than those with a higher body condition score of 3 (P < 0.05). Perception study results revealed many factors that could affect the adoption and implementation of ART in the study areas. The high success rate and above average reproductive performance led to North West and KwaZulu-Natal provinces adopting ART as part of their low-income beef sector support.

An ultra-wide scanner for large-area high-speed atomic force microscopy with megapixel resolution

High-speed atomic force microscopy (HS-AFM) is a powerful tool for visualizing the dynamics of individual biomolecules. However, in single-molecule HS-AFM imaging applications, x,y-scanner ranges are typically restricted to a few hundred nanometers, preventing overview observation of larger molecular assemblies, such as 2-dimensional protein crystal growth or fibrillar aggregation. Previous advances in scanner design using mechanical amplification of the piezo-driven x,y-positioning system have extended the size of HS-AFM image frames to several tens of micrometer, but these large scanners may suffer from mechanical instabilities at high scan speeds and only record images with limited pixel numbers and comparatively low lateral resolutions (> 20–100 nm/pixel), complicating single-molecule analysis. Thus, AFM systems able to image large sample areas at high speeds and with nanometer resolution have still been missing. Here, we describe a HS-AFM sample-scanner system able to record large topographic images (≤ 36 × 36 µm2) containing up to 16 megapixels, providing molecular resolution throughout the image frame. Despite its large size, the flexure-based scanner features a high resonance frequency (> 2 kHz) and delivers stable operation even at high scans speeds of up to 7.2 mm/s, minimizing the time required for recording megapixel scans. We furthermore demonstrate that operating this high-speed scanner in time-lapse mode can simultaneously identify areas of spontaneous 2-dimensional Annexin A5 crystal growth, resolve the angular orientation of large crystalline domains, and even detect rare crystal lattice defects, all without changing scan frame size or resolution. Dynamic processes first identified from overview scans can then be further imaged at increased frame rates in reduced scan areas after switching to conventional HS-AFM scanning. The added ability to collect large-area, high-resolution images of complex samples within biological-relevant time frames extends the capabilities of HS-AFM from single-molecule imaging to the study of large dynamic molecular arrays. Moreover, large-area HS-AFM scanning can generate detailed structural data sets from a single scan, aiding the quantitative analysis of structurally heterogenous samples, including cellular surfaces.

Security and collision in RFID systems

Radio Frequency Identification (RFID) is a promising technology to provide automated contactless identification of objects, people and animals. The identification process is performed as the reader receives simultaneous responses from various tags over a shared wireless channel and without no requirement of line-of-sight in the interrogation zone. The communication between the reader and tags is separated into two processes: identification and acknowledgment processes. Both processes suffer from serious drawbacks that limit the proliferation of RFID. Such drawbacks are security and privacy and collision problems. This thesis has two main parts. The first part examines the security and privacy of the existing RFID authentication protocols. We introduced a novel cryptographic scheme, Hacker Proof Authentication Protocol (HPAP) that allows mutual authentication and achieves full security by deploying tag static identifier, updated timestamp, a one-way hash function and encryption keys with randomized update using Linear Feedback Shift Register (LFSR). Cryptanalysis and simulation show that the protocol is secure against various attacks. In comparison with the various existing RFID authentication protocols, our protocol has less computation load, requires less storage, and costs less. The second part focuses on solving RFID collision arbitration imposed by the shared wireless link between a reader and the many tags distributed in the interrogation zone. In most proposed anticollision algorithms, tags reply randomly to the time slots chosen by the reader. Since more than two tags may choose the same time slot in a frame, this Random Access (RA) causes garbled data at the reader side resulting the identification process fails. Towards this challenge, two ALOHA based anti-collision algorithms that adopt a new way for tags to choose their replied time slots to enhance system efficiency are presented. In MBA and LTMBA, tags use modulo function to choose their owned time slot. The difference between the two algorithms relies on the method by which the reader estimates the next frame size. The performance evaluation of the two algorithms shows better performance than previously proposed algorithms in terms of fewer communication rounds and fewer collided/empty slots considering the limitation of the EPCglobal Class-1 Gen-2 standard.

Security and collision in RFID systems

Radio Frequency Identification (RFID) is a promising technology to provide automated contactless identification of objects, people and animals. The identification process is performed as the reader receives simultaneous responses from various tags over a shared wireless channel and without no requirement of line-of-sight in the interrogation zone. The communication between the reader and tags is separated into two processes: identification and acknowledgment processes. Both processes suffer from serious drawbacks that limit the proliferation of RFID. Such drawbacks are security and privacy and collision problems. This thesis has two main parts. The first part examines the security and privacy of the existing RFID authentication protocols. We introduced a novel cryptographic scheme, Hacker Proof Authentication Protocol (HPAP) that allows mutual authentication and achieves full security by deploying tag static identifier, updated timestamp, a one-way hash function and encryption keys with randomized update using Linear Feedback Shift Register (LFSR). Cryptanalysis and simulation show that the protocol is secure against various attacks. In comparison with the various existing RFID authentication protocols, our protocol has less computation load, requires less storage, and costs less. The second part focuses on solving RFID collision arbitration imposed by the shared wireless link between a reader and the many tags distributed in the interrogation zone. In most proposed anticollision algorithms, tags reply randomly to the time slots chosen by the reader. Since more than two tags may choose the same time slot in a frame, this Random Access (RA) causes garbled data at the reader side resulting the identification process fails. Towards this challenge, two ALOHA based anti-collision algorithms that adopt a new way for tags to choose their replied time slots to enhance system efficiency are presented. In MBA and LTMBA, tags use modulo function to choose their owned time slot. The difference between the two algorithms relies on the method by which the reader estimates the next frame size. The performance evaluation of the two algorithms shows better performance than previously proposed algorithms in terms of fewer communication rounds and fewer collided/empty slots considering the limitation of the EPCglobal Class-1 Gen-2 standard.

Full-frame and high-contrast smart windows from halide-exchanged perovskites

Window glazing plays an essential role to modulate indoor light and heat transmission, which is a prospect to save the energy cost in buildings. The latest photovoltachromic technology has been regarded as one of the most ideal solutions, however, to achieve full-frame size (100% active area) and high-contrast ratio (>30% variable in visible wavelength) for smart window applicability is still a challenge. Here we report a photovoltachromic device combining full-transparent perovskite photovoltaic and ion-gel based electrochromic components in a vertical tandem architecture without any intermediated electrode. Most importantly, by accurately adjusting the halide-exchanging period, this photovoltachromic module can realize a high pristine transmittance up to 76%. Moreover, it possesses excellent colour-rendering index to 96, wide contrast ratio (>30%) on average visible transmittance (400-780 nm), and a self-adaptable transmittance adjustment and control indoor brightness and temperature automatically depending on different solar irradiances.

An Efficient Early Frame Breaking Strategy for RFID Tag Identification in Large-Scale Industrial Internet of Things

With the increase in the number of tags, an efficient approach of tag identification is becoming an urgent need in Industrial Internet of Things (IIoT). However, the identification performance of existing Aloha-based anticollision schemes is limited when the initial frame size is seriously mismatched with the actual tag population size. The performance will degrade further when IIoT is deployed in the error-prone channel environment. To optimize the identification performance of RFID system in an error-prone channel environment, we propose an efficient early frame breaking strategy based anticollision algorithm (EFB-ACA) with channel awareness. The EFB-ACA divides the whole tag identification process into two phases: convergence phase and identification phase. The function of convergence phase is to make the adjusted frame quickly converge to an appropriate size. The early frame breaking strategy is embedded in the convergence phase. Numerical results show that the proposed EFB-ACA algorithm outperforms the other methods on efficiency and stability in the error-prone channel. In addition, EFB-ACA algorithm also outperforms the other methods in the error-free channel.

Exploring the association of riders’ physical attributes with comfortable riding posture and optimal riding position

In recent years, there has been a keen interest in the design improvisation of motorcycles. However, the theoretical model of association between motorcycle design attributes (like frame size/riding position) and rider’s physical attributes (like anthropometry, range of motion (ROM), and comfort joint angles) are not well established. This study aims to estimate the relationship between rider’s physical attributes and motorcycle design attributes. During this experimental study, the data was collected from 120 motorcyclists (aged between 19 and 44 years) belonging to 20 major states of India. A test-rig was fabricated to obtain the perceived comfort posture and position data using image processing technique. The anthropometry and ROM were manually measured and verified by reliability testing. The principal component analysis (PCA) and multiple linear regression were used to reduce the set of variables and estimate the relationship between 10 comfortable riding position and joint angles (as dependent variables), and the reduced set of 29 anthropometry and 20 ROM measurements (as the independent variables). These results indicate that the comfort joint angles and riding position were significantly associated with the anthropometrics and ROM of the riders. Highly significant regression models were formulated to examine the relationship between the comfort joint angles/riding position and the anthropometrics and ROM of the riders. The findings may support the motorcycle designers to design a comfortable motorcycle complying with Indian anthropometry and ROM.