Gurum Seeds: A Potential Source of Edible Oil

Cucurbitaceae family seeds are mostly discarded as agro-industrial wastes. Gurum (Citrullus lanatus var. colocynthoide) is an underutilized wild cucurbit plant, closely related to desert watermelon, which is grown abundantly in some African countries. Gurum seeds can play a significant role in health and nutrition due to their high oil content. This review describes the nutritional composition of gurum seeds and their oil profile. Gurum seeds are a good source of oil (27–35.5%), fiber (26–31%), crude protein (15–18%), and carbohydrates (14–17%). Gurum seeds oil is extracted by supercritical CO₂ (SFE), screw press, and solvent extraction techniques. The gurum seeds oil is composed of unsaturated fatty acids with a high proportion of linoleic acid (C18:2) and oleic acid (C18:1). Gurum seeds oil contains various bioactive compounds, such as tocopherols, phytosterols, and polyphenols. It is reported that solvent extraction gives a higher yield than the screw press and SFE, but the SFE is preferred due to safety issues. More studies are required for producing better quality gurum seeds oil by using novel extraction techniques that can increase oil yield.     

An open-source multi-DOF articulated robotic educational platform for autonomous object manipulation

This research presents an autonomous robotic framework for academic, vocational and training purpose. The platform is centred on a 6 Degree Of Freedom (DOF) serial robotic arm. The kinematic and dynamic models of the robot have been derived to facilitate controller design. An on-board camera to scan the arm workspace permits autonomous applications development. The sensory system consists of position feedback from each joint of the robot and a force sensor mounted at the arm gripper. External devices can be interfaced with the platform through digital and analog I/O ports of the robot controller. To enhance the learning outcome for beginners, higher level commands have been provided. Advanced users can tailor the platform by exploiting the open-source custom-developed hardware and software architectures. The efficacy of the proposed platform has been demonstrated by implementing two experiments; autonomous sorting of objects and controller design. The proposed platform finds its potential to teach technical courses (like Robotics, Control, Electronics, Image-processing and Computer vision) and to implement and validate advanced algorithms for object manipulation and grasping, trajectory generation, path planning, etc. It can also be employed in an industrial environment to test various strategies prior to their execution on actual manipulators.     

Vision Based Neuro-Fuzzy Controller for a Two Axes Gimbal System with Small UAV

This paper presents the development of a vision-based neuro-fuzzy controller for a two axes gimbal system mounted on a small Unmanned Aerial Vehicle (UAV). The controller uses vision-based object detection as input and generates pan and tilt motion and velocity commands for the gimbal in order to keep the interest object at the center of the image frame. A readial basis function based neuro-fuzzy system and a learning algorithm is developed for the controller to address the dynamic and non-linear characteristics of the gimbal movement. The controller uses two separate, but identical radial basis function networks, one for pan and one for tilt motion of the gimbal. Each system is initialized with a fixed number of neurons that act as rules basis for the fuzzy inference system. The membership functions and rule strengths are then adjusted with the feedback from the visual tracking system. The controller is trained off-line until a desired error level is achieved. Training is then continued on-line to allow the system to accommodate air speed changes. The algorithm learns from the error computed from the detected position of the object in image frame and generates position and velocity commands for the gimbal movement. Several tests including lab tests and actual flight tests of the UAV have been carried out to demonstrate the effectiveness of the controller. Test results show that the controller is able to converge effectively and generate accurate position and velocity commands to keep the object at the center of the image frame.     

Copy move forgery detection using DCT,PatchMatch and cellular automata

Multimedia Tools and Applications - Copy-move image forgery is a type of digital image forgery where content is copied and pasted within the same image, either by hiding foreground objects within...     

Use of Neural Network Based Prediction Algorithms for Powering Up Smart Portable Accessories

Neural Processing Letters - Emerging Trends in the use of smart portable accessories, particularly within the context of the Internet of Things (IoT), where smart sensor devices are employed for...     

Input-parallel output-parallel configuration of boost half bridge DC-DC converter with control strategy

The concept of connecting two boost half bridge DC-DC converter modules in input-paral- lel output-parallel configuration is presented. The input-parallel-output-parallel （IPOP） converter consists of multiple boost half bridge （BHB） DC-DC converter modules which are connected in par- allel at the input and output side. This kind of converter is an attractive solution for high power ap- plications. The correlation between input current sharing （ICS） and output current sharing （OCS） of the IPOP converter basic modules is described. Two loop control strategies, consisting of input cur- rent loop and output voltage loop, have been developed to achieve equal ICS and OCS in this present work. The control strategy for the IPOP configuration of boost haft bridge DC-DC converter has been verified for different load conditions （half load and full load）, The IPOP system proposed here is comprising of two modules but it can be extended to three or more. The performance of the pro- posed system along with the control strategy is verified by simulation in MATLAB using Simpower tool. Finally the satisfactory simulation results are obtained.     

A review on microwell and microfluidic geometric array fabrication techniques and its potential applications in cellular studies

The ability to trap precise quantities of cells or particles into confined areas has numerous applications for biological purposes. In particular, single cell trapping has received considerable attention because it permits the study of heterogeneity in a population, while trapping larger groups of cells have been used to form aggregates. Among several methods, the use of microwell offers a simple platform to capture cells or particles using hydrodynamic forces. This review examines the use of microwells in both static and microfluidic environments, and the application of microfluidic geometric arrays for trapping. This paper discusses the design and fabrication methods of microwells and compares the trapping and release techniques used in both static and microfluidics‐integrated microwells. Finally, we will summarize novel microfluidic geometric arrays used to capture cells or particles through hydrodynamic trapping.     

WiMA: Towards a Multi-Criterion Association in Software Defined Wi-Fi Networks

Despite the planned installation and operations of the traditional IEEE 802.11 networks, they still experience degraded performance due to the number of inefficiencies. One of the main reasons is the received signal strength indicator (RSSI) association problem, in which the user remains connected to the access point (AP) unless the RSSI becomes too weak. In this paper, we propose a multi-criterion association (WiMA) scheme based on software defined networking (SDN) in Wi-Fi networks. An association solution based on multi-criterion such as AP load, RSSI, and channel occupancy is proposed to satisfy the quality of service (QoS). SDN having an overall view of the network takes the association and reassociation decisions making the handoffs smooth in throughput performance. To implement WiMA extensive simulations runs are carried out on Mininet-NS3-Wi-Fi network simulator. The performance evaluation shows that the WiMA significantly reduces the average number of retransmissions by 5%–30% and enhances the throughput by 20%–50%, hence maintaining user fairness and accommodating more wireless devices and traffic load in the network, when compared to traditional client-driven (CD) approach and state of the art Wi-Balance approach.     

Differential response of glaciers with varying debris cover extent: evidence from changing glacier parameters

Supraglacial debris (SGD) cover on mountain glaciers is known to greatly influence various glacier processes and alter their response to climate change. In this study, vital glacier parameters of five glaciers with varying debris coverage (about 7–26%), located in Zanskar basin, Ladakh Himalaya, were monitored using Landsat imagery (from 1977 to 2013) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) global digital elevation model (GDEM). Results reveal how varying amounts of SGD induce categorically distinct responses on glaciers, sharing same geographical settings. The clean glaciers (CG) in the area were found to have higher retreat rates (about 8–19 m year^?1), comparable areal shrinkage (about 13–15%), higher accumulation area ratios (AARs) (>0.5), rapid increase in SGD (about 1.6–3.0-fold), and association with increasing numbers of peri- and proglacial lakes (2–8 per glacier). The debris-covered glaciers (DCG) showed minimal frontal changes (about 2–5 m year^?1), higher areal shrinkage (about 14–21%), low AARs (<0.5), slow SGD changes (about ≤1.2-fold), and association with increasing numbers of peri- and supraglacial lakes (SGLs) (2–39 per glacier). Moreover, while changes in SGD had a strong negative correlation with changes in glacier area, retreat rates, and AAR, they were positively related with increase in area of SGLs.