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Detection of clouds and shadows in remote sensing imagery is important due to its wide range of applications. There are a lot of applications in remote sensing images such as monitoring of the environment, change detection etc. It is an important and booming research area. Ineffective and inaccurate cloud and cloud shadow masking will cause undesirable effects on different task that can be performed by using remote sensing images. Because of high spectral conglomeration and the spectral and temperature discrepancy of the underlying surface the detection of clouds and associated shadows is not candid. In this paper, we propose CSDUNet a modified U-Net network for precise pixel-wise semantic segmentation of cloud and its associated shadow from optical remote sensing images. It uses an encoder network and a decoder network. This method concatenated feature maps at different scales. We have proposed a novel network for cloud detection, which extract features corresponding cloud and shadow at different scales from multilevel layers to generate sharp boundaries. Which will help to detect clouds in heterogeneous landscape, under complex underlying surfaces with varying geometry. Experimental analysis on the Landsat satellite dataset proves that the proposed CSDUNet achieves a dice coefficient of 95.05%. Our method got 95.93% precision, recall of 94.71% and Jaccard index of 97.29%. CSDUNet achieves accurate detection accuracy and surpass several traditional methods. [ABSTRACT FROM AUTHOR]

Aim: Using atenolol as a model active pharmaceutical and galactomannan from the seeds of Trigonella foenumgraecum as a mucoadhesive polymer, an effort was made to develop a gastroretentive bioadhesive floating delivery system to improve the residence time in the stomach. Materials and Methods: Different formulations were made with Hydroxypropyl Methyl Cellulose (HPMC) and galactomannan. Galactomannan was chosen because of its exceptional swelling properties in aqueous environments. In this investigation, citric acid and sodium bicarbonate were utilized as gas-producing components. Pre- and postcompression evaluations were performed on the manufactured tablets. The floating properties as well as the atenolol release pattern were investigated. Results: The extracted polymer was characterized using various techniques and found to be similar to literature. The results from GC analysis showed a residual acetone content of 0.127 ppm, indicating that the extracted polymer is safer to use in the formulation of gastroretentive tablets. The physicochemical properties of the manufactured tablets were satisfactory in terms of swelling index, release characteristics, and buoyancy pattern. All of the manufactured batches had adequate in vitro buoyancy. The gastroretentive tablet exhibited axial and radial swelling throughout the in vitro buoyancy test. According to the testing, the formulation remained buoyant for approximately 8 to 12 hr. Conclusion: According to the results of the evaluation, the manufactured tablet has a pleasing look, is heat stable, and is therapeutically efficient. F3 was determined to be the optimal formulation based on the data collected. [ABSTRACT FROM AUTHOR]

Automation of the various steps of radiotherapy is gaining importance nowadays. Predicting the amount of radiation dose received by the tumor and nearby organs is one among them. Many deep learning architectures that predict the 3D dose distribution images from corresponding CT and contour images have been proposed in the literature. However, a detailed investigation has yet to be done on the significance of input images (CT and contour) in predicting dose distributions. This study introduces a novel two‐stage deep learning framework using a transfer learning technique for the same domain. The main objective of this approach is to accurately extract valuable information from the CT and contour images to determine the amount of radiation dose received by the organs. Training and testing are performed on the public dataset—OpenKBP, consisting of 340 oropharyngeal cancer patient data. The model performance is evaluated using the metrics dose score and DVH score. The proposed model outperforms the single‐stage deep learning models by 0.34% for the DVH score and 0.14% for the dose score. While comparing the mean dose difference between the predicted and actual dose values for each organ, the proposed model shows better performance in almost all cases. The results imply that medical professionals can utilize the predicted dose distributions to aid the optimization process in the treatment planning systems. [ABSTRACT FROM AUTHOR]

The present work aimed to identify the effects of knowledge, attitudes, and practices (KAP) of poultry handlers on the prevalence of Campylobacter along the poultry production chain in Peninsular Malaysia. A total of 1230 microbiological samples were collected from five companies in different Malaysian states. The sampling points involved the entire poultry supply chain from the farm to the retailer. The collected samples were subjected to bacteriological isolation and morphological identification for microbiological analyses. All Campylobacter-positive samples were further confirmed with molecular identification by using a polymerase chain reaction. Campylobacter prevalence in poultry farms, processing plants, and retailers were identified. For the KAP survey, 300 respondents answered a questionnaire evaluating their levels of KAP regarding food safety while handling live birds and subsequently poultry products after slaughtering. Overall, the mean KAP scores of the workers at farms, processing plants, and retail outlets were assessed. The survey data indicated that even though the overall KAP levels of the poultry workers were excellent, the bacterial prevalence of Campylobacter was still high. In conclusion, the KAP of poultry handlers had insignificant effects on the prevalence of Campylobacter along the poultry production chain in Peninsular Malaysia. [ABSTRACT FROM AUTHOR]

Cloud Computing has changed the way we are thinking about computer security and the way how corporations organize their internal processes. Therefore the Cloud computing is a new paradigm to convey computing architecture and assistance in acquiring the chances and difficulties in the region of distributed resources management. Resource scalability and security are the two major issues under Infrastructure as a Service (IaaS) of resource allocation. In this manner, the Entropy-based Adaptive Krill herd optimization for auto-scaling in the cloud is proposed. Here, auto-scaling is a significant cloud computing feature under IaaS, which is utilized to dynamically assign computational resources to applications to coordinate their present loads absolutely, in this way removing resources that would diversely stay idle and waste power. In the first stage, the task is monitored by determining the trust-based anomaly detection objectives such as Frequency Value, Trust Hypothesis Statistics, trust factor value, and trust policy. At that point, the given task is scheduled to find the task status. Then it is scaled using the execution time and workload calculation. After that, the scaled data is optimized utilizing the entropy-based krill herd algorithm. At long last, the comparisons of the proposed and existing methods are evaluated. [ABSTRACT FROM AUTHOR]

Salmonella are widely found in the poultry industry, which subsequently may pose a risk to animal and human health. The aim of this review is to highlight strategies for the prevention and control of Salmonella at each stage in the poultry production chain by monitoring risks from the farm to the retailer. Among the primary approaches for control of Salmonella at the farm level includes the administration of synthetic and natural compounds to live chickens (vaccination and antibiotic), litter management as well as fortification of feed and acidification of drinking water. In the poultry processing plant, multiple hurdle technology and different chilling conditions to reduce Salmonella were discussed. In the retail level, an effective monitoring program to control Salmonella contamination by good manufacturing practices and hazard analysis and critical control points has been reviewed. Overall, we conclude that these approaches play a role in reducing the dissemination of Salmonella in the poultry industry. However, there is no published data related to logistic scheduling of poultry processing. [ABSTRACT FROM AUTHOR]

In this most revolutionized world, the social network plays a vital role in each and everyone's life. Social networking is a pervasive communication platform where the users can search whole over the world via the Internet. Users have similar interest to connect and interact with one another and to share their private and personal interest. In this paper, we examine privacy concern for the social networking users by distributed clustering method. In the proposed scheme, to speed-up, the Kernel k-means algorithm, a prototype based hybrid kernel k-means algorithm is involved in distributing the users into the cluster. Since we are using a large data set, we use a hybrid approach to speed-up the kernel k-means clustering (HSKK). The clustering process used here is to partition a similar set of objects in a dataset. Additionally, in the clustering process, a cryptographic protocol such as homomorphic encryption is involved in every dataset to achieve the goal to protect the private data. To prove the efficiency of the proposed approach, the experiment is done on Movie lens dataset. The experimental study of HSKK shows that the proposed method can significantly reduce the computation time and the private data of users is hidden from the service provider. [ABSTRACT FROM AUTHOR]

Background: Endotracheal intubation may produce haemodynamic fluctuations which may be deleterious in patients with cardiovascular and neurological disorders. This is further worsened in patients with difficult airway. This study was conducted to compare haemodynamic fluctuations produced when intubation was done using Airtraq and fibreoptic bronchoscopy which are used in patients with anticipated difficult airway. Methodology: Prospective randomized study. Eighty patients, ASA PS 1 and 2 undergoing elective surgery were randomized into two groups – Group A and Group F. After routine induction and muscle relaxation, orotracheal intubation was done using Airtraq in Group A and fibreoptic bronchoscope in Group F. Heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP) and mean arterial pressure (MAP) were recorded at regular intervals. Duration and number of attempts for intubation were also noted Results: There was no significant difference in the average of variation in HR (p=0.384), SBP (p=0.179), DBP (p=0.746) and MAP (p=0.057) from the baseline between the two groups. Duration of intubation in FOB group (mean value of 56.98 s) was more than Airtraq® video laryngoscope group (mean value of 37.38 s) which was statistically significant. Conclusion: Use of fibreoptic bronchoscope offer no added advantage over Airtraq video laryngoscope in terms of haemodynamic response for intubation in difficult airway situation such as cervical spine injury. [ABSTRACT FROM AUTHOR]

With the development of controlled converter circuits and the rapid growth of independent electric power station, the self-excited induction generator (SEIG) is increasingly being used for different small power generation systems. This paper investigates the analysis and implementation of a control scheme for maintaining a single phase load RMS voltage and frequency constant, fed by self-excited induction generator under variable speed and load. The proposed control is useful for isolated small power applications such as uncontrolled small hydro turbine or wind turbine. Experimental results confirm good performance and the effectiveness of the proposed control. [ABSTRACT FROM AUTHOR]

The high-power voltage source inverters are switched at low frequency to reduce the losses in the inverter. The discontinuous pulsewidth-modulation (PWM) sequences reduce the switching frequency to two-thirds compared to the conventional continuous PWM sequences. At low switching frequency, the output will be rich in harmonics, and synchronization is a must to avoid subharmonics. This paper presents four basic types of synchronized discontinuous PWM (DPWM) sequences that ensure synchronization, three-phase symmetry, and half-wave symmetry. The proposed synchronized DPWM sequences are verified through simulation and experiment on a constant- v/f open-loop induction motor drive. The performance of the proposed DPWM algorithms is studied in the entire modulation region, including the overmodulation region, and is compared with that of the conventional synchronized space vector PWM. A different type of DPWM with low common-mode voltage is suggested for low-modulation region and verified experimentally. [ABSTRACT FROM PUBLISHER]

The nonlinear loads in oil drilling rigs result in power quality problems such as harmonic distortion and low power factor. This paper addresses the harmonic problems in onshore rigs that are commissioned in early period of semiconductor technology and use dc drives. Different power filtering solutions are considered, and their performance is presented. The influence of practical constraints such as space limitations, reliability, cost, ease of maintenance, and operating conditions on the choice of filter is discussed. An optimal choice of filter meeting the objective and satisfying the practical constraints is presented. [ABSTRACT FROM AUTHOR]

In computer vision, objects in an image can be described using many features such as shape, color, texture and local features. The number of dimensions for each type of feature has differing size. Basically, the underlying belief from a recognition point of view is that, the more features being used, the better the recognition performance. However, having more features does not necessarily correlate to better performance. The higher dimensional vectors resulting from fusion might contain irrelevant or noisy features that can degrade classifier performance. Repetitive and potentially useless information might be present which further escalates the 'curse of dimensionality' problem. Consequently, unwanted and irrelevant features are removed from the combination of features. Although this technique provides promising recognition performance, it is not efficient when it comes to computational time in model building. This study proposes meta- classifier framework to ensure all relevant features are not ignored, while maintaining minimal computational time. In this framework, individual classifiers are trained using the local and global shape features, respectively. Then, these classifiers results are combined as input to the meta- classifier. Experimental results have shown to be comparable, or superior to existing state-of-the-art works for object class recognition. [ABSTRACT FROM AUTHOR]

Discontinuous pulse-width modulation (PWM) techniques result in reduced power loss in voltage source inverters. This study presents the space vector approach to the three-level discontinuous PWM technique. The switching sequences for four basic types of discontinuous PWM and the implementation are presented. An improved discontinuous PWM algorithm is presented for low modulation index region. All these algorithms are verified experimentally and the results are presented. The performance of discontinuous PWM algorithms is compared with that of conventional space vector-based PWM algorithms. [ABSTRACT FROM AUTHOR]

In high-power applications, the output voltage of a voltage source inverter (VSI) must be synchronized with its fundamental component in order to eliminate subharmonics. With proper selection of switching states, it is possible to obtain synchronization and symmetry in the space vector pulse width modulation (SVPWM) algorithm. This paper presents an improved three-level SVPWM algorithm for the overmodulation region, which guarantees synchronization, half-wave symmetry, quarter-wave symmetry, and three-phase symmetry for all integer values of the pulse number. The proposed synchronized SVPWM algorithm is experimentally verified. The performance of the proposed algorithm is compared with other conventional algorithms. The comparative results prove that the consideration of synchronization and various symmetry results in better performance of the VSI. [ABSTRACT FROM PUBLISHER]

The objective of the present work is to improve the output waveform of three level inverters used in high-power applications, where the switching frequency is very low. This is achieved by maintaining the synchronization, half-wave symmetry, quarter-wave symmetry, and three-phase symmetry in the pulsewidth modulation (PWM) waveforms. The principles of achieving synchronization and symmetries in terms of space vectors for three level inverters are presented. A novel synchronized space vector pulsewidth modulation (SVPWM) algorithms is proposed and verified experimentally. The experimental wave- forms of the inverter output voltage and motor no load current for different operating conditions of the drive are presented. The performance measure in terms of the weighted total harmonic distortion (THD) of the line voltage is computed for the linear modulation region of the drive for the proposed algorithm and compared with that of synchronized SVPWM and synchronized sine-triangle pulsewidth modulation (SPWM) technique. The comparative results show that consideration of synchronization and symmetry results in improved THD. Another significant feature of the proposed algorithm is that the symmetry and synchronization leads to self-balancing of the direct current (dc) bus capacitor voltages over every one third cycle of the fundamental. [ABSTRACT FROM AUTHOR]

Current source inverter (CSI) fed drives are employed in high power applications. The conventional CSI drives suffer from drawbacks such as harmonic resonance, unstable operation at low speed ranges, and torque pulsation. This paper presents a novel CSI drive which overcomes all these drawbacks and results in sinusoidal motor voltage and current even with CSI switching at fundamental frequency. The proposed CSI drive uses a three-level inverter as an active filter across motor terminals replacing the bulky ac capacitors used in the conventional drive. A sensorless vector controlled CSI drive based on proposed configuration is developed. The simulation and experimental results are presented. Experimental results show that the proposed drive has stable operation even at low speeds. Comparative results show that the proposed CSI drive has improved torque ripple compared to the conventional configuration. [ABSTRACT FROM AUTHOR]