Miracle-dz/UniFAR-FTUs huggingface dataset:
Routing optimization for cloud services in SDN-based Internet of Things with TCAM capacity constraint

Distributed in-network cloud architecture is a promising solution to efficiently host next generation internet-of-things (IoT) services. With the rapid increase of IoT devices and applications, the backhaul or backbone networks, which transmit IoT traffic to various in-network clouds, will experience a predicted explosion in the volume of carried traffic. To guarantee the QoS of IoT cloud services and improve the network performance, it is crucial for network operator to implement efficient routing optimization strategies for IoT traffic. As a promising networking paradigm, software-defined networking (SDN) has flexible and programmable control capability for fine-grained flows. The emergence of SDN paves a way for implementing high-performance routing optimization in networks. In SDN networks, the routing strategies are realized through flow rules, which are usually stored in TCAM with very limited capacity. However, the number of IoT flows are enormous. Thus, in this paper, we address the routing optimization problem in SDN-based IoT with TCAM capacity constraint. We first formulate the problem as a mixed integer linear programming problem and prove the problem is NP-hard. Then to solve the problem efficiently, we propose several approximate algorithms, which solve the problem in two stages. In the first stage, the algorithms calculate the routing strategies for flows without considering the TCAM capacity constraint. To meet the TCAM capacity constraint, the algorithms using different strategies to adjust the paths of some flows in the second stage. Extensive simulations are conducted on both real ISP and synthetic topologies to evaluate the performance of the algorithms. The simulation results verify that the algorithms can achieve promising load balancing performance in SDN-based IoT, where the capacity of TCAM in SDN switches is very limited.
A Comparison of Online JavaScript Obfuscators

Obfuscation, obscuring the meaning of source code, has been proposed as a security measure to protect JavaScript applications running in web browsers on the client-side. This paper presents a comparative study of online JavaScript obfuscators, looking at the obfuscation techniques they employ and assessing their resilience, potency and the costs associated with the obfuscation process. We conclude that while several current obfuscators are theoretically quite resilient and potent, in most cases their output can effortlessly be reversed by automatic deobfuscators. We also suggest several methods for strengthening JavaScript obfuscation.
Flexible Wireless ECG Circuit Fabrication Technique

The value of smart medical devices, including heart rate monitors, is forecasted by U.S. Smart Medical Devices to be increased yearly until year 2025. Smartphones play an important role in the healthcare industry, thus, the increase in smartphone usage is in parallel with the rising demand for wireless and smartphone-compatible medical devices. This in turn promotes awareness and focus on health and fitness, and demand-led growth for home usage. There were a few researches related to the methods used in the fabrication of flexible circuits such as screen printing, inkjet printing and direct transfer methods. On top of that, different flexible substrate materials such as paper, plastic (such as Polyethylene terephthalate (PET)), Kapton and textile-fabric were used by researchers to achieve their study objectives. Each method and material used in the previous studies were reviewed to address critical points such as to emphasize the adhesion property of materials as it may affect the quality and reliability of the flexible circuit during and after fabrication process. Thus, the focus of this study is to review a wireless ECG monitoring device which is compact, flexible, and equipped with wireless communication technology.
Optimizing RISC-V ISA Usage by Sharing Coprocessors on MPSoC

Increased device integration has enabled the construction of complex System-on-Chip (SoC) architectures, enabling it to meet the increasing demand for functionality required by emerging embedded applications. Among these architectures is MultiProcessor SoC (MPSoC), which is made up of a processor set containing an Instruction Set Architecture (ISA) with sometimes underused and high-cost implementation instructions, increasing power dissipation and area consumption and losing performance due to the increased critical path. This work proposes an MPSoC that extends the standard ISA of the RISC-V architecture through shared resources among processors. The strategy proposed is to execute instructions in specialized modules distributed in the system when the processor's datapath do not support them. To evaluate the proposed methodology, we implemented a set of scenarios that were evaluated for area consumption, power dissipation, energy consumption, maximum operating frequency, and the number of cycles for the application execution. The experimental results show that, with a low hardware cost, the proposed resource sharing technique reduces several metrics with a low penalty in the execution time of the analyzed applications.
The application of deep learning on fast skin cancer diagnosis

Nowadays, health problems have been more and more important. In order to solve the difficulties of diagnosing skin cancer quickly and precisely, we applied a state-of-the-art deep convolutional neural network (CNN) architecture with transfer learning, to help diagnose various types of skin cancers. Combined with proper data augmentation and normalization, the designed model achieves state-of-the-art result, including f1-score to be as high as 0.83, which demonstrates a promising application of the deep neural network on visual diagnosis of skin illness.
Feature Extraction and Feature Selection Methods in Classification of Brain MRI Images: A Review

Magnetic Resonance Imaging, or MRI, is one of the safest ways to observe human tissues and organs, like the brain. It causes no radiation and bad effect for the patient. The necessity of early detection of brain tumor leads the researchers to initiate this study. Early detection of a brain tumor can be observed through MRI image results. The brain MRI images are then processed by using 3 major steps, namely image processing, feature extraction and selection, and classification. The feature extraction and selection are one of the important steps that can determine the accuracy of brain MRI images classification in which its result will determine the disease. This paper examines 9 feature extraction and 3 feature selection methods for classification of brain MRI images. Furthermore, it explores the advantages and disadvantages of each method. Both of them are considered in the selection of the best method to be applied in different cases. The summary of each method is presented in a table as supportive evidence. This study shows that Local Binary Pattern combined with GLRL, ZM, PHOG, and GLCM is the best feature extraction method for BRATS dataset with a classification accuracy of 97.1%, while GLDM and GA are the best combinations of feature extraction and selection method for clinical datasets with a classification accuracy of 98%.
Variations in cyclic adenosine 3′,5′-monophosphate and cyclic guanosine 3′,5′-monophosphate in antibiotic producing strains of Streptomyces hygroscopicus

Although the occurrence and function of cyclic nucleotides have been reported in a variety of prokaryotic microorganisms, expecially Gram-negative bacteria, relatively little is known about these nucleotides in Gram-positive bacteria [1-3]. This paper is concerned with the occurrence of cyclic AMP and cyclic GMP in Streptomyces hygroscopicus and their fluctuations at different stages of fermentation. It is the first report, to our knowledge, on the presence of cyclic nucleotides in actinomycetes [1,4]. S. hygroscopicus produces preferably after the main growth period a sixteen-membered macrolide antibiotic complex, turimycin, structurally related to the leukomycin group. Therefore, it is a suitable organism to study regulation problems of the metabolic change to the so-called secondary metabolism. In this view we have compared the wild type strain with two higher productive mutants and also studied the effect of exogenously added cyclic AMP on growth and turimycin production.
Deployment and Decentralized Identity Management for VANETs

VANET networks are mostly theoretical, and the research is focused on simulations and hypothetical situations. As in the preceding work, micro simulation adopted for assessing traffic, emergency dissemination, and route identification are performed and analyzed utilizing simulators. This paper presents a further study in communication between vehicles focusing on a real deployment to understand the substantive possibilities of VANETs. The main objective of this paper is to perform a real deployment of the vehicular network. Secondly, the network has to ensure identity management to protect misuse of priority services. Finally, the deployment result compared with theoretical studies and simulations to prove the correct method during the development of the design and to give validity to work done. Proposed work ensures, to security and privacy of OBUs taking part in the network. Protection of designed network against reply attack, message integrity, and denial of service attacks is considered carefully. Identity plays a vital role in VANETs, protecting communication form masquerading scenarios, and maintaining privacy plays a significant role. For the protection of identity, a decentralized identity management protocol is proposed in this paper for Emergency Vehicles (EMVs).
Long Short-Term Memory and Fuzzy Logic for Anomaly Detection and Mitigation in Software-Defined Network Environment

Computer networks become complex and dynamic structures. As a result of this fact, the configuration and the managing of this whole structure is a challenging activity. Software-Defined Networks(SDN) is a new network paradigm that, through an abstraction of network plans, seeks to separate the control plane and data plane, and tends as an objective to overcome the limitations in terms of network infrastructure configuration. As in the traditional network environment, the SDN environment is also liable to security vulnerabilities. This work presents a system of detection and mitigation of Distributed Denial of Service (DDoS) attacks and Portscan attacks in SDN environments (LSTM-FUZZY). The LSTM-FUZZY system presented in this work has three distinct phases: characterization, anomaly detection, and mitigation. The system was tested in two scenarios. In the first scenario, we applied IP flows collected from the SDN Floodlight controllers through emulation on Mininet. On the other hand, in the second scenario, the CICDDoS 2019 dataset was applied. The results gained show that the efficiency of the system to assist in network management, detect and mitigate the occurrence of the attacks.
Nutritive and bioactive components in rice fermented with the edible mushroom Pleurotus eryngii

The present research was the first to compare nutritive and bioactive components of Pleurotus eryngii-fermented rice with untreated rice. After fermentation, the total content of crude protein, crude fat, polysaccharides, reducing sugar, and polyphenols was significantly increased in fermented rice. The total content of amino acid in fermented rice was enhanced to 557.71 mg/g in comparison with 258.83 mg/g in non-fermented rice. The content of essential amino acid increased from 79.32 mg/g to 140.36 mg/g. The content of adenosine in fermented rice (175.64 μg/g) is much higher than that of non-fermented rice (14.38 μg/g). In antioxidant assay, the ethanol extract of the P. eryngii-fermented rice showed a strong reducing ability with EC50 value less than 0.25 mg/ml. These results indicated that rice fermented by P. eryngii could be useful as a new functional food.
Performance Analysis of Sea Unmanned Ship Routing Protocol Based on Ad Hoc Network

With the development of society, maritime communication system will affect the future military and civil needs directly. There are a lot of natural resources in the ocean, and some areas have important strategic value. The exploration and development of the ocean will be the focus of future research. The growing scale of research and the lack of offshore infrastructure also put forward severe requirements for future maritime communications. Based on the research of unmanned exploration vessels on the sea, this paper draws on the technical characteristics of wireless Ad Hoc networks to build a sea-based unmanned ship network system. Through simulation, we can see the advantages of ad hoc network in ship networking. In the absence of infrastructure, messages can be transmitted to each other to achieve interoperability.
Visual Analysis of Minsu Research in China Using CiteSpaceV

This study uses the CiteSpaceV software to evaluate research progress that has been achieved from 2007 to 2019 on Minsu in China. The number of literature traced in CNKI database is 488. Although the co-author analysis and co-institution show that research network has not formed yet and high-quality researches are inadequate, keywords co-occurrence timeline analysis identifies seven research streams emerged from the literature, including experience and service; sharing economy; rural revitalization; design and renovation; similar accommodation; local culture; and online review analysis. Specifically, the results show that new trends emerge in Minsu researches, which are the research of Airbnb as the trading platform of Minsu in the context of sharing economy, and the research of host-guest interactions and relationships etc. Lastly, research gaps are discussed and suggestions are provided.
Is Technological Innovation Effective for Energy Saving and Carbon Emissions Reduction? Evidence From China

Technological innovation is increasingly becoming an important way to develop a low-carbon economy. Recently, exploring the driving path of low-carbon development has become the hot topic, however, the role of energy consumption in the carbon-reduction effect of technological innovation has been ignored. Based on China’s provincial-level panel data from 2005 to 2016, this paper investigates the effect of technological innovation on energy saving and carbon emissions reduction and the role of energy consumption in the influencing process by using linear regression model, mediating effect model and threshold regression model. The results show that technological innovation has effectively promoted energy saving and carbon emissions reduction in China, with different effect coefficients between the three areas of China. Moreover, energy consumption plays a significant partial mediating role in the effect of technological innovation on carbon emissions reduction. Finally, the effect of technological innovation on carbon emissions is limited by energy consumption. Low energy consumption significantly promotes a reduction in carbon emissions through technological innovation. Once energy consumption exceeds a critical level, the promoting effect of technological innovation on carbon emissions reduction will turn into the inhibiting effect. Based on these findings, some policy recommendations are put forward to accelerate the low-carbon transformation of the economy.
SIW Based Self-Diplexing Dumbbell Slot Antenna for X- Band Application

A design of substrate integrated waveguide (SIW) based self-diplexing dumbbell-shaped slot antenna is presented in this paper. The proposed antenna comprises of two micro-strip feed lines of impedance 50Ω and two parallel dumbbell-shaped slots. These transverse parallel slots are of different lengths, etched on the patch (top surface) of the SIW cavity; produce two resonant frequencies at 8.12GHz & 10.15GHz. The proposed self-diplexing antenna is based on the function of operating mode and perturbation of the higher order modes methodology. The better intrinsic isolation of 26.5dB is obtained between two input ports, which define the unique property of the self-diplexing antenna and reduce the space and size of overall wireless transceiver modules. The proposed antenna produces the unidirectional radiation pattern, high front to back ratio (>17 dB) and gain of 4.7dBi & 5.2dBi at two resonant frequencies of 8.12GHz & 10.15GHz for the X- Band application as satellite and wireless communication systems.
Gait analysis based on angular velocity during human walking on five terrains

Gait analysis is the systematic study of human locomotion from the perspective of biology and kinematic. This work investigates the relationship between motion of feet and plantar pressure during human walking on five different types of terrains typical of daily living. Temporal parameters and symmetry index of gaits are calculated by method based on angular velocity of coronal axis. The results show gait features on different terrain and subject have commonness and differences.
A Study on the Identity of Bracon hebetor Say and Bracon brevicornis Wesmael (Hymenoptera: Braconidae)

Literature, mainly Indian, pertaining to the recorded hosts of Bracon hebetor Say and B. brevicornis Wesm. , and on the taxonomy of the two species, has been reviewed. Observations on different morphological characters, including the male and female genitalia, which have been used in establishing the identity of the two species, have been made. A large number of B. hebetor specimens reared in Bangalore on Corcyra cephalonica (Stnt.), Ephestia cautella (Wlk.), Adisura atkinsoni Moore and those collected in food-grain godowns, and of B. brevicornis reared on C. cephalonica and E. cautella in Bangalore, on Nephantis serinopa Meyr. from Coimbatore (South India), on Pyrausta nubilalis (Hb.) from Canada and on cotton bollworms (? ) from Delhi (North India), have been examined. Differences in colour, relative proportions of antennal joints and punctation on the abdomen have been found to be variable and as such are not to be depended upon for distinguishing the two species. The number of antennal joints which has hitherto been considered to be the decisive character by which the two species may be separated is also not reliable as there is a wide range of variation even in the progeny of a single pair of parents. Above all, the fact that the two species interbreed and give rise to fertile offspring, which also show a fairly wide range of variation in the number of antennal joints, proves that the two are identical, and there is no ground to treat them as two distinct species, at least so far as the Indian specimens are concerned, for which Bracon hebetor Say is the valid name.
Disturbance Rejection Control With Voltage Constraint for Electro-Hydraulic System Involving Unknown Dead-Zones and Drastic Supply Pressure Variation

In the article, we use the proportional directional valve (PDV) with unknown dead-zones to regulate the electro-hydraulic system (EHS) which has parametric uncertainties including the drastic supply pressure variation; moreover, the external disturbance occurs when the EHS works; in addition, the control voltage applied to the PDV is expected to satisfy the prescribed bound. All of these factors make controller design a challenging problem. The unknown dead-zones, the external disturbance, the drastic supply pressure variation and other parametric uncertainties are viewed as a total disturbance which can be estimated by the linear extended state observer (LESO). Furthermore, a novel robust disturbance rejection position controller with voltage constraints is proposed to compensate for the dead-zones and improve the tracking performance of the EHS regulated by the PDV when the drastic supply pressure variation and the external disturbance occur. The stability analysis is given to ensure that the tracking error of the closed-loop EHS regulated by the proposed controller can converge to the arbitrarily small neighborhood of the origin. Experiments are carried out to verify the effectiveness of the proposed control method. Comparative experimental results demonstrate that the proposed controller can make the load follow the reference trajectory accurately in the presence of the unknown dead-zones and the external disturbance when the supply pressure varies drastically.
Efficient Parallel-Beamforming Based on Shared FIFO for Ultra-Compact Ultrasound Imaging Systems

The realization of a parallel-beamforming (pBF) method in ultra-compact ultrasound imaging systems is challenging to achieve uncompromised beamforming accuracy in limited hardware and power resources. In this paper, we present a new hardware- and power-efficient pBF method that utilizes a shared first-in-first-out block on a post-fractional delay filtering architecture (pBF-sFIFO). For an analog-to-digital conversion (ADC) rate given, the proposed pBF-sFIFO method yielded beamforming accuracy comparable to that by an unconstrained pBF (pBF-CON) method, with up to 15% less power consumption. Otherwise, a conventional time-sharing pBF method (pBF-TS) was more vulnerable to aliasing artifacts. Even though increasing ADC rate in the pBF-TS method could recover the beamforming accuracy, exponential need in power consumption was inevitable. Therefore, the pBF-sFIFO method would be an effective solution to enable advanced imaging features in ultra-compact ultrasound imaging systems.
Deforestation Prediction Using Time Series and LSTM

Wildfires and deforestation are dragging the Amazon rainforests into a disaster, an irreversible cycle of collapse. The speed of deforestation must be calculated, aided by advanced technologies in an effort to save these rainforests. The paper proposed two AI techniques, namely Time Series and LSTM, which were used to predict the future deforestation of Amazon rainforests. The calculations revealed an urgent need to take action to prevent further deterioration. It is believed that the assistance of the advanced AI techniques will efficiently slow down deforestation, thus improving the environment in the foreseeable future.
Radiation Hardened Digital Direct Synthesizer With CORDIC for Spaceborne Applications

The Coordinate Rotation Digital Computer algorithm (CORDIC) is a simple mechanism to compute a set of elementary functions, such as trigonometric functions, using fixed-point devices. It is widely adopted, also in applications running in harsh environments such as space, where radiation is a cause of errors in nanoelectronic devices. A single event upset in a configuration bit of a Field Programmable Gate Array (FPGA) can completely change the behavior of the implemented circuit, so it is important to detect and reconfigure the FPGA when this happens. Dual modular redundancy is the typical method to detect errors in electronic circuits, but it has an important overhead in area and power consumption and it does not provide any additional functionality apart from the activation of the FPGA reconfiguration trigger in presence of error. This paper presents two ad-hoc techniques to protect the Digital Direct Synthesizer with CORDIC when it is implemented into an FPGA, with limited overhead in terms of area and power consumption when compared with the traditional solution. The first solution slightly increases the percentage of undetected errors, about 11%, reducing to almost half the area overhead of the circuit. The second solution introduces a trade-off between the percentage of error detection and the precision of the trigonometric output of the CORDIC by means of a polymorphic structure with lower area resources than the existing solutions. This last proposal allows the system to increase the precision of the digital synthesis signal under absence of errors or to activate the error protection in scenarios with external disturbances such as radiation.