Abstract: The cultivation of black glutinous rice rich in anthocyanins can provide great benefits to both farmers and consumers. Total anthocyanins content and yield component data of black glutinous rice cultivar (KHHK) grown with the addition of mineral elements (Ca, Mg, Cu, Cr, Fe and Se) under soilless conditions were studied. Ca application increased seed anthocyanins content by three-folds compared to controls. Cu application to rice plants obtained the highest number of grains panicle, panicle length and subsequently high panicle weight. Se application had the largest effect on leaf anthocyanins content, the number of tillers, number of panicles and 100-grain weight. These findings showed that the addition of mineral elements had a positive effect on increasing anthocyanins content in black rice plants and seeds as well as the heightened development of black glutinous rice plant growth.
Abstract: This research attempts to evaluate the treatment provided by the Qatari media to the decision to allow Saudi women to drive, and then activate this decision after a few months, that is, within the time frame between September 26, 2017 until June 30, 2018. This is through asking several questions, including whether the political dispute between Qatar and Saudi Arabia has cast a shadow over this handling, and if these Qatari media handlings are used to criticize the Saudi regime for delaying this step. Here emerges one of the research hypotheses that says that the coverage did not have the required professionalism, due to the fact that the decision and its activation took place in light of the political stalemate between Qatar and the Kingdom of Saudi Arabia, which requires testing the media framing and agenda theories to know to what extent they apply to this case. The research dealt with a sample of five Qatari media read in this sample: Al-Jazeera Net, The New Arab Newspaper, Al-Sharq Newspaper, The Arab Newspaper, and Al-Watan Newspaper. The results showed that most of the authors who covered the decision to allow Saudi women to drive a car did not achieve a balance in their writing, and that almost half of them did not have objectivity, and this indicates the proof of the hypothesis that there is a defect in the professional competence in covering the decision to allow Saudi women to drive cars by means of Qatari media, and the researcher attributes this result to the political position between Qatar and Saudi Arabia, in addition to the fact that the Arab media in most of them are characterized by a low ceiling of freedom, and most of them are identical in their position with the position of the regime’s official view.
Abstract: In this paper we develop a model that couples Two Concurrent Convolution Neural Network with different filters (TC*CNN) for face recognition and compare its performance to an existing sequential CNN (base model). We also test and compare the quality and performance of the models on three datasets with various levels of complexity (easy, moderate, and difficult) and show that for the most complex datasets, edges will produce the most accurate and efficient results. We further show that in such cases while Support Vector Machine (SVM) models are fast, they do not produce accurate results.
Abstract: Over-parameterized neural networks have attracted a
great deal of attention in recent deep learning theory research,
as they challenge the classic perspective of over-fitting when
the model has excessive parameters and have gained empirical
success in various settings. While a number of theoretical works
have been presented to demystify properties of such models, the
convergence properties of such models are still far from being
thoroughly understood. In this work, we study the convergence
properties of training two-hidden-layer partially over-parameterized
fully connected networks with the Rectified Linear Unit activation via
gradient descent. To our knowledge, this is the first theoretical work
to understand convergence properties of deep over-parameterized
networks without the equally-wide-hidden-layer assumption and
other unrealistic assumptions. We provide a probabilistic lower bound
of the widths of hidden layers and proved linear convergence rate of
gradient descent. We also conducted experiments on synthetic and
real-world datasets to validate our theory.
Abstract: In Algeria agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. Economic development in the last decade has weighed heavily on water resources which are relatively limited and gradually decreasing to the detriment of agriculture. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Foum El-Gherza dam’s reservoir system in south of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 12.32% to 55%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study.
Abstract: This paper presents a multi-objective optimal design of
a cascade control system for an underactuated mechanical system.
Cascade control structures usually include two control algorithms
(inner and outer). To design such a control system properly, the
following conflicting objectives should be considered at the same
time: 1) the inner closed-loop control must be faster than the outer
one, 2) the inner loop should fast reject any disturbance and prevent
it from propagating to the outer loop, 3) the controlled system
should be insensitive to measurement noise, and 4) the controlled
system should be driven by optimal energy. Such a control problem
can be formulated as a multi-objective optimization problem such
that the optimal trade-offs among these design goals are found.
To authors best knowledge, such a problem has not been studied
in multi-objective settings so far. In this work, an underactuated
mechanical system consisting of a rotary servo motor and a ball
and beam is used for the computer simulations, the setup parameters
of the inner and outer control systems are tuned by NSGA-II
(Non-dominated Sorting Genetic Algorithm), and the dominancy
concept is used to find the optimal design points. The solution of
this problem is not a single optimal cascade control, but rather a set
of optimal cascade controllers (called Pareto set) which represent the
optimal trade-offs among the selected design criteria. The function
evaluation of the Pareto set is called the Pareto front. The solution
set is introduced to the decision-maker who can choose any point
to implement. The simulation results in terms of Pareto front and
time responses to external signals show the competing nature among
the design objectives. The presented study may become the basis for
multi-objective optimal design of multi-loop control systems.
Abstract: The inability of organizations to put in place management control measures for Internet of Things (IoT) complexities persists to be a risk concern. Policy makers have been left to scamper in finding measures to combat these security and privacy concerns. IoT forensics is a cumbersome process as there is no standardization of the IoT products, no or limited historical data are stored on the devices. This paper highlights why IoT forensics is a unique adventure and brought out the legal challenges encountered in the investigation process. A quadrant model is presented to study the conflicting aspects in IoT forensics. The model analyses the effectiveness of forensic investigation process versus the admissibility of the evidence integrity; taking into account the user privacy and the providers’ compliance with the laws and regulations. Our analysis concludes that a semi-automated forensic process using machine learning, could eliminate the human factor from the profiling and surveillance processes, and hence resolves the issues of data protection (privacy and confidentiality).
Abstract: This paper presents modeling and control strategy for the grid connected wind turbine system based on Permanent Magnet Synchronous Generator (PMSG). The considered system is based on back-to-back converter topology. The Grid Side Converter (GSC) achieves the DC bus voltage control and unity power factor. The Machine Side Converter (MSC) assures the PMSG speed control. The PMSG is used as a variable speed generator and connected directly to the turbine without gearbox. The pitch angle control is not either considered in this study. Further, Optimal Tip Speed Ratio (OTSR) based MPPT control strategy is used to ensure the most energy efficiency whatever the wind speed variations. A filter (L) is put between the GSC and the grid to reduce current ripple and to improve the injected power quality. The proposed grid connected wind system is built under MATLAB/Simulink environment. The simulation results show the feasibility of the proposed topology and performance of its control strategies.
Abstract: Vehicular Adhoc Networks (VANETs), a subset of Mobile Adhoc Networks (MANETs), refers to a set of smart vehicles used for road safety. This vehicle provides communication services among one another or with the Road Side Unit (RSU). Security is one of the most critical issues related to VANET as the information transmitted is distributed in an open access environment. As each vehicle is not a source of all messages, most of the communication depends on the information received from other vehicles. To protect VANET from malicious action, each vehicle must be able to evaluate, decide and react locally on the information received from other vehicles. Therefore, message verification is more challenging in VANET because of the security and privacy concerns of the participating vehicles. To overcome security threats, we propose Monitoring Algorithm that detects malicious nodes based on the pre-selected threshold value. The threshold value is compared with the distrust value which is inherently tagged with each vehicle. The proposed Monitoring Algorithm not only detects malicious vehicles, but also isolates the malicious vehicles from the network. The proposed technique is simulated using Network Simulator2 (NS2) tool. The simulation result illustrated that the proposed Monitoring Algorithm outperforms the existing algorithms in terms of malicious node detection, network delay, packet delivery ratio and throughput, thereby uplifting the overall performance of the network.
Abstract: The rapid industrialisation and population growth have led to a steady fall in freshwater supplies worldwide. As a result, water systems are affected by modern methods upon use due to secondary contamination. The application of novel adsorbents derived from natural polymer holds a great promise in addressing challenges in water treatment. In this study, the UV irradiation technique was used to prepare acrylamide (AAm) monomer, and acrylic acid (AA) monomer grafted xanthan gum (XG) copolymer. Furthermore, the factors affecting rhodamine B (RhB) adsorption from aqueous media, such as pH, dosage, concentration, and time were also investigated. The FTIR results confirmed the formation of graft copolymer by the strong vibrational bands at 1709 cm-1 and 1612 cm-1 for AA and AAm, respectively. Additionally, more irregular, porous and wrinkled surface observed from SEM of XG-g-AAm/AA indicated copolymerization interaction of monomers. The optimum conditions for removing RhB dye with a maximum adsorption capacity of 313 mg/g at 25 0C from aqueous solution were pH approximately 5, initial dye concentration = 200 ppm, adsorbent dose = 30 mg. Also, the detailed investigation of the isothermal and adsorption kinetics of RhB from aqueous solution showed that the adsorption of the dye followed a Freundlich model (R2 = 0.96333) and pseudo-second-order kinetics. The results further indicated that this absorbent based on XG had the universality to remove dye through the mechanism of chemical adsorption. The outstanding adsorption potential of the grafted copolymer could be used to remove cationic dyes from aqueous solution as a low-cost product.
Abstract: Constant potometer is an important component of pipeline anti-corrosion systems in the chemical industry. Based on Internet of Things (IoT) technology, Programmable Logic Controller (PLC) technology and database technology, this paper developed a set of a constant potometer remote monitoring management system. The remote monitoring and remote adjustment of the working status of the constant potometer are realized. The system has real-time data display, historical data query, alarm push management, user permission management, and supporting Web access and mobile client application (APP) access. The actual engineering project test results show the stability of the system, which can be widely used in cathodic protection systems.
Abstract: The goal of this paper is to converge upon a design of a brake system that could be used for a roller coaster found at an amusement park. It was necessary to find what could be deemed as a “comfortable” deceleration so that passengers do not feel as if they are suddenly jerked and pressed against the restraining harnesses. A human factors engineering approach was taken in order to determine this deceleration. Using a previous study that tested the deceleration of transit vehicles, it was found that a -0.45 G deceleration would be used as a design requirement to build this system around. An adjustable linear eddy current brake using permanent magnets would be the ideal system to use in order to meet this design requirement. Anthropometric data were then used to determine a realistic weight and length of the roller coaster that the brake was being designed for. The weight and length data were then factored into magnetic brake force equations. These equations were used to determine how the brake system and the brake run layout would be designed. A final design for the brake was determined and it was found that a total of 12 brakes would be needed with a maximum braking distance of 53.6 m in order to stop a roller coaster travelling at its top speed and loaded to maximum capacity. This design is derived from theoretical calculations, but is within the realm of feasibility.
Abstract: Economic and population growth in densely-populated urban areas introduce major challenges to distribution system operators, planers, and designers. To supply added loads, utilities are frequently forced to invest in new distribution feeders. However, this is becoming increasingly more challenging due to space limitations and rising installation costs in urban settings. This paper proposes the conversion of critical alternating current (ac) distribution feeders into direct current (dc) feeders to increase the power transfer capacity by a factor as high as four. Current trends suggest that the return of dc transmission, distribution, and utilization are inevitable. Since a total system-level transformation to dc operation is not possible in a short period of time due to the needed huge investments and utility unreadiness, this paper recommends that feeders that are expected to exceed their limits in near future are converted to dc. The increase in power transfer capacity is achieved through several key differences between ac and dc power transmission systems. First, it is shown that underground cables can be operated at higher dc voltage than the ac voltage for the same dielectric stress in the insulation. Second, cable sheath losses, due to induced voltages yielding circulation currents, that can be as high as phase conductor losses under ac operation, are not present under dc. Finally, skin and proximity effects in conductors and sheaths do not exist in dc cables. The paper demonstrates that in addition to the increased power transfer capacity utilities substituting ac feeders by dc feeders could benefit from significant lower costs and reduced losses. Installing dc feeders is less expensive than installing new ac feeders even when new trenches are not needed. Case studies using the IEEE 342-Node Low Voltage Networked Test System quantify the technical and economic benefits of dc feeders.
Abstract: The study aims to establish the virtual size and fit technology features to enhance fashion online retailing platforms, utilising digital human measurements to provide customised style and function to consumers. A few firms in the UK have launched advanced interactive fashion shopping domains for personalised shopping globally, aided by the latest internet technology. Virtual size and fit interfaces have a great potential to provide a personalised better-fitted garment to promote mass customisation globally. Made-to-measure clothing, consuming unstitched fabric is a common practice offered by fashion brands in Pakistan. This product is regarded as economical and sustainable to be utilised by consumers in Pakistan. Although the manual sizing system is practiced to sell garments online, virtual size and fit visualisation and recommendation technologies are uncommon in Pakistani fashion interfaces. A comparative assessment of Pakistani fashion brand websites and UK technology-driven fashion interfaces was conducted to highlight the vast potential of the virtual size and fit technology. The results indicated that web 2.0 technology adopted by Pakistani apparel brands has limited features, whereas companies practicing web 3.0 technology provide interactive online real-store shopping experience leading to enhanced customer satisfaction and globalisation of brands.
Abstract: This article presents an analytical model to estimate the harvested power from a Magnetostrictive cantilevered beam with tip excitation. Furthermore, the effects of internal and external damping on harvested power are investigated. The magnetostrictive material in this harvester is Galfenol. In comparison to other popular smart materials like Terfenol-D, Galfenol has higher strength and machinability. In this article, first, a mechanical model of the Euler-Bernoulli beam is employed to calculate the deflection of the harvester. Then, the magneto-mechanical equation of Galfenol is combined with Faraday's law to calculate the generated voltage of the Magnetostrictive cantilevered beam harvester. Finally, the beam model is incorporated in the aforementioned combination. The results show that a 30×8.5×1 mm Galfenol cantilever beam harvester with 80 turn pickup coil can generate up to 3.7 mV and 9 mW. Furthermore, sensitivity analysis made by Response Surface Method (RSM) shows that the harvested power is only sensitive to the internal damping coefficient.
Abstract: Background: Dynamic, challenging instances during the management of major trauma patients requires optimal team intervention to ensure patient safety and effective crisis management. These factors highlight the importance of increased awareness in both technical and non-technical skills (NTS) training. Simulation based training (SBT) is an effective tool that replicates and teaches the required clinical skills, resulting in teamwork improvement, better patient safety, and care. Aims: This study investigates change in NTS, during the management of major trauma patients, using SBT. We also investigated the relationship between NTS performance and participation in previous NTS workshop (NTSW), years of experience, previous simulation (PS), previous exposure to major trauma patient management (MTPM) and group size. Methods: NTS behaviours were assessed by a single rater using previously validated framework for observing and rating Anaesthetists’ Non-Technical Skills (ANTS) for anaesthetists and Anaesthetic Non-Technical Skills for Anaesthetic Practitioners (ANTS-AP) for anaesthetic nurses during SBT. Two anaesthetists (one senior, one junior) together with one to four registered anaesthetic nurses formed 17 teams. The SBT consisted of 3 major trauma scenarios: 1) Major haemorrhage following multiple stab wounds to the torso, 2) Traumatic brain injury complicated by unanticipated difficult intubation, and 3) Penetrating neck injury with major haemorrhage, complicated by a failed intubation. The scores of each NTS category for each scenario are evaluated for significance in change and used to correlate whether NTS during the simulation were affected by previous NTSW, PS, previous exposure to MTPM and group size. Results: The resulting anaesthetists and anesthetic nurses’ p-values were < 0.05 indicating a significant improvement in all NTS resulting from score differences between scenarios 1 & 2 and 1 & 3. Anaesthetists’ NTS categories were not influenced by PS, previous NTSW, and exposure to MTPM. However, anaesthetic nurses NTS categories were influenced by PS, exposure to MTPM but not by NTSW. Conclusions: SBT has shown to be effective in improving the NTS for both anaesthetists and anaesthetic nurses. This enhances safety and team performance for MTPM. The impact of SBT in the clinical environment for patient management and safety warrants further research.
Abstract: Radio Frequency Identification (RFID) is one of the most commonly used technologies in IoTs and Wireless Sensor Networks which makes the devices identification and tracking extremely easy to manage. Since RFID uses wireless channel for communication, which is open for all types of adversaries, researchers have proposed many Ultralightweight Mutual Authentication Protocols (UMAPs) to ensure security and privacy in a cost-effective manner. These UMAPs involve simple bitwise logical operators such as XOR, AND, OR & Rot, etc., to design the protocol messages. However, most of these UMAPs were later reported to be vulnerable against many malicious attacks. In this paper, we have presented a detailed overview of some eminent UMAPs and also discussed the many security attacks on them. Finally, some recommendations and suggestions have been discussed, which can improve the design of the UMAPs.
Abstract: Nowadays, physical processes are becoming digitized
by the evolution of communication, sensing and storage technologies
which promote the development of smart cities. The evolution of
this technology has generated multiple challenges related to the
generation of big data and the active participation of electronic
devices in society. Thus, devices can send information that is captured
and processed over large areas, but there is no guarantee that all
the obtained data amount will be effectively stored and correctly
persisted. Because, depending on the technology which is used,
there are parameters that has huge influence on the full delivery of
information. This article aims to characterize the project, currently
under development, of a platform that based on data science will
perform a performance and effectiveness evaluation of an industrial
network that implements LoRaWAN technology considering its main
parameters configuration relating these parameters to the information
loss.
Abstract: Electrical faults in transmission and distribution networks can have great impact on the electrical equipment used. Fault effects depend on the characteristics of the fault as well as the network itself. It is important to anticipate the network’s behavior during faults when planning a new equipment installation, as well as troubleshooting. Moreover, working backwards, we could be able to estimate the characteristics of the fault when checking the perceived effects. Different transformer winding connections dominantly used in the Greek power transfer and distribution networks and the effects of 1-phase to neutral, phase-to-phase, 2-phases to neutral and 3-phase faults on different locations of the network were simulated in order to present voltage sag characteristics. The study was performed on a generic network with three steps down transformers on two voltage level buses (one 150 kV/20 kV transformer and two 20 kV/0.4 kV). We found that during faults, there are significant changes both on voltage magnitudes and on phase angles. The simulations and short-circuit analysis were performed using the PSCAD simulation package. This paper presents voltage characteristics calculated for the simulated network, with different approaches on the transformer winding connections during symmetrical and asymmetrical faults on various locations.
Abstract: In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.