Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep learning framework for scene based indoor location recognition

Scene recognition and Object detection have made momentous progress lately. While mobile robotics and drone analysis has already reached its growth apex, for robots, which can interact with humans and the indoor environment, having a sense of discerning indoor scenes or interiors of a building is an added benefit. Although, many approaches have been proposed to detect objects and locations such as Indoor Positioning System (IPS), feature based, content based recognition systems etc., indoor scene recognition is yet to gain ground. This is quite justified since, unlike outdoor scenes, indoor scenes lack distinctive local or global visual substance patterns. This paper proposes a new technique of achieving this goal by considering the data from the scene's RGB and Depth images. With advancement in machine learning methodologies such as neural networks, deep neural networks and Convolutional Neural Networks, the workable accuracy in scene recognition is no longer hypothetical. A Deep CNN framework is used with a transfer learning approach for indoor scene recognition implemented on Tensor Flow (python), using the RGB as well as point cloud data i.e., RGB-D images. With this proposed system of deep CNN model, accuracy is able to reach up to 94.4% on the indoor dataset. Further a comparison of the proposed model performance with that of the digits' GoogLeNet and AlexNet framework is conducted. Also a training of the algorithm on the benchmark NYUv2 dataset and have achieved an accuracy of 75.9% which beats the highest accuracy obtained on that model (64.5%).
Convertible Dark Pulse and Bright Pulse Fiber Ring Laser by Adjusting the Polarization

A wavelength tunable, dark pulse, and bright pulse-switched dual-wavelength fiber ring laser is reported. Through adding high nonlinear optical fiber as a nonlinear medium in the fiber ring cavity, the double-wavelength dark-bright pulse pair can be formed. The separation of dark-bright pulse pair can be achieved by polarization beam splitter. The dark pulse and bright pulse with orthogonal polarization correspond to different wavelengths, respectively. Then, via tunable optical filter and polarization controller to filter out the wavelength we need and adjust the polarization, we achieved the interconversion of dark pulse and bright pulse in the same wavelength and the tunableness of wavelengths of dark pulse and bright pulse in our laser.
Impact Melting and the Role of Sub-Surface Volatiles: Implications for the Formation of Valley Networks and Phyllosilicate-rich Lithologies on Early Mars

FORMATION OF VALLEY NETWORKS AND PHYLLOSILICATE-RICH LITHOLOGIES ON EARLY MARS. L. L. Tornabene , A. S. McEwen, G. R. Osinski, P. J. Mouginis-Mark, J. M. Boyce, R. M. E. Williams, J. J. Wray, J. A. Grant, and the HiRISE Team, Lunar and Planetary Laboratory, University of Arizona, Tucson, AZ 85721, livio@lpl.arizona. edu, Canadian Space Agency, Saint-Hubert, QC J3Y8Y9. Hawaii Institute of Geophysics and Planetology, SOEST, University of Hawaii, Honolulu, HI 96822, Planetary Science Institute, Tucson, AZ 85719, Department of Astronomy, Cornell University, Ithaca, NY 14853, Smithsonian Institution, Center for Earth and Planetary Studies, Washington DC 20560.
Knowledge and Awareness Regarding Cervical Cancer and Uptake of Pap Smear among Women in Karachi, Pakistan

Objective: To determine the knowledge regarding cervical cancer, its symptoms and risk factors among women of 18 years and above attending the gynecology OPD in two public hospitals Karachi, Pakistan. Methodology: A cross-sectional survey was held from February to June 2013 in Karachi, Pakistan. 384 females aged 18 years and above attending gynecology clinics in two public sector hospitals were taken through non-probability sampling method. The knowledge was assessed using a point scale method which had binary response i.e. correct and incorrect. A score of 50% (≥ 11 correct responses) was considered as optimum knowledge. Results: Overall knowledge of cervical cancer was 23% based on scoring. Multiparity (29.1%) and unsafe sexual practice (21.8%) were mostly reported risk factors. Vaginal discharge (23.1%) were commonly reported presenting features of cervical cancer. Uptake of pap smear was 11% among all women. Women with younger had much less knowledge (AOR: 0.56, 95% CI: 0.14 0.71) as compare to middle age. Women with no education and 3 or more children were less likely to have sufficient knowledge (AOR: 0.79, 95% CI: 0.51 0.89) as compared to the educated. Women with 6 or more children were less likely to have sufficient knowledge (AOR: 0.44, 95% CI: 0.2 0.68) as compared to the women with less than 3 children. Married women were more likely to have enough knowledge (AOR: 1.2, 95% CI: 1.01 3.11) as compare to unmarried women. Conclusion: Insufficient knowledge of cervical cancer and about its screening services was found among general population. Establishing strategies for spreading awareness and provision of preventive services is essential through health care providers and media advocacy. Hence to improve health seeking behaviour and enhance early screening rates.
An Enhanced Frequency-Ratio Coupled-Line Dual-Frequency Wilkinson Power Divider

This brief presents a novel design of a dual-band equal split Wilkinson power divider. It is based around a single coupled line section as core and uses stub-based port matching networks at each of the ports. It then incorporates only one isolation resistor, which is independent of frequency-ratio, for achieving perfect isolation. Closed form design equations are developed for the general analysis of the power divider and design case studies are provided to evaluate the proposed design. The developed prototypes for frequency-ratios of 2 and 7 show a good agreement between the electromagnetic simulated and measured results and thus validate the reported theory.
Effect of Library Services on the Educational Development of Secondary School Students in Abia State: A Study of Igbere Secondary School Igbere

The focus of this paper is on the effect of library services on the educational development of secondary school students in Abia State, Nigeria. The study investigated the only governmentowned secondary school in Igbere Community of Bende Local Government Area of Abia State. The school was chosen on the basis of availability of school library. Students from Senior Secondary 1 to 3 were the respondents of this investigation. However, a sample size of 99 students out of a total population of 248 students representing 40% of the entire population, were randomly selected. A structured questionnaire was used to collect data. The study investigated the library services provided for the students, the extent of the students’ use of the library services, the effects of the library service on the educational development of the students, the challenges facing library services as well as strategies to enhance library services to ensure the educational development of secondary school students. The paper through its findings concludes that libraries are the drivers of educational development through its numerous services. It therefore recommends the establishment of school library with up-to-date information resources and relevant services as a criterion for the approval of any secondary school programme in Abia State and Nigeria among other recommendations. With this, the educational sector of Nigeria stands to benefit immensely and not only that, there will be a reduction in emigration of Nigeria students as well as increase in Gross Domestic Product (GDP) of Nigeria.
Driving behavior modeling and evaluation for bus enter and leave stop process

Driving behavior optimization not only lowers the occurrence probability of the traffic accident and pollutant emissions, but also improves the energy efficiency level. Current studies indicate that corresponding data processing method deadly influence accuracy and rationality of driving behavior estimation results. However, due to the complexity of road environment, driving behavior estimation always faces the common difficulties of model establishment. In this paper, a new concept, critical zone, is defined to distinguish special driving areas. A typical critical zone, bus stop, is selected as modeling target area, while corresponding driving process—bus enters and leaves bus stop process—is selected to construct driving behavior model. Then, a good driving behavior parameters discovery method, which aims to provide real-time operation recommendations for bus stop accessing procedure, optimize driving technology, reduce fuel consumption and improve comfort, is proposed. A zone and time oriented slicing process is employed to mapping corresponding data into multiple distinguished procedures, in which both clustering and pruning processing are used to deal with data of each slice to get good driving behavior parameters. Moreover, an application based C/S model is used to test effectiveness of proposed method. Test results demonstrate that the developed model and parameter discovery method are effective.
Coordination of fast frequency support from multi-terminal HVDC grids

A high-voltage direct-current (HVDC) system should provide frequency support to all ac grids connected to it. Presently, only a reduced number of ac grids receive this ancillary service. In this paper, an HVDC grid is modeled to analyze and compare the effectiveness of three different fast frequency support algorithms. These supplementary schemes allow the exchange of additional power among the ac systems interconnected by the HVDC grid. However, undesired power flows and reduced power transfers may result if all converters within the dc grid are fitted with the frequency support loop. This may be attributed to simultaneous frequency oscillations on multiple ac systems during the support operation. To prevent this adverse effect, an auxiliary dead-band controller (ADC) is proposed, which uses measurements of rate of change of frequency and frequency deviation to modify the dead-band set-point of the fast frequency controllers. Results show that the proposed ADC scheme improves the performance of fast frequency control algorithms fitted to multi-terminal HVDC grids. Moreover, the dc grid is capable of facilitating support to all connected ac grids as needed while restoring a stable operation and improving power transfer capability.
m-GreenCARDIO embedded system designed for out-of-hospital cardiac patients

Today's electronic systems have evolved greatly and enable the design of systems that are safer, more competitive and also more flexible in terms of their built-in features and power consumption. As we see, the number of applications in the medical field and in adjacent areas have skyrocketed, so that monitoring terminals or mobile analysis systems can be purchased relatively easily. This paper presents and describes the concept, results and theory of operating the m-GreenCARDIO device, designed for remote monitoring of out-of-hospital patient's heart condition. This implementation helps to make medical instrumentation more efficient, making it accessible to a larger social range, by the means of Internet of Things (IoT). Thus, through this project, a real and flexible collection of ECG data from patients can be acquired, obtaining valuable information that can be used for remote research and diagnosis.
Methods for evaluating wetland condition # 1 Introduction to Wetland Biological Assessment

ii Notice The material in this document has been subjected to U.S. Environmental Protection Agency (EPA) technical review and has been approved for publication as an EPA document. The information contained herein is offered to the reader as a review of the " state of the science " concerning wetland bioassessment and nutrient enrichment and is not intended to be prescriptive guidance or firm advice. Mention of trade names, products or services does not convey, and should not be interpreted as conveying official EPA approval, endorsement, or recommendation.
Analysis of a power factor regulation strategy for an embedded point-to-point MMC-HVDC system

This paper presents a strategy for regulation of power factor in an embedded high-voltage direct current (HVDC) system based on modular multilevel converter (MMC) technology. Field reported in existing literature are taken as a reference for qualitative assessment of the performance of the proposed strategy. The implication of adding such a type of control mode in an MMC-HVDC system is determined through software experiments performed in DIgSILENT PowerFactory. The results reveal that the power factor can be effectively controlled by an MMC-HVDC link within its power rating limits, even in the case of changes of the active power reference.
How do medium naturalness and personality traits shape academic achievement and perceived learning? An experimental study of face-to-face and synchronous e-learning

This controlled experiment examined how academic achievement and cognitive, emotional and social aspects of perceived learning are affected by the level of medium naturalness (face-to-face, one-way and two-way videoconferencing) and by learners’ personality traits (extroversion–introversion and emotional stability–neuroticism). The Media Naturalness Theory explains the degree of medium naturalness by comparing its characteristics to face-to-face communication, considered to be the most natural form of communication. A total of 76 participants were randomly assigned to three experimental conditions: face-to-face, one-way and two-way videoconferencing. E-learning conditions were conducted through Zoom videoconferencing, which enables natural and spontaneous communication. Findings shed light on the trade-off involved in media naturalness: one-way videoconferencing, the less natural learning condition, enhanced the cognitive aspect of perceived learning but compromised the emotional and social aspects. Regarding the impact of personality, neurotic students tended to enjoy and succeed more in face-to-face learning, whereas emotionally stable students enjoyed and succeeded in all of the learning conditions. Extroverts tended to enjoy more natural learning environments but had lower achievements in these conditions. In accordance with the ‘poor get richer’ principle, introverts enjoyed environments with a low level of medium naturalness. However, they remained focused and had higher achievements in the face-to-face learning. (Published 13 July 2017) Citation: Research in Learning Technology 2017, 25: 1945 - http://dx.doi. org/10.25304/rlt.v25. 1974
UAVFog: A UAV-based fog computing for Internet of Things

Fog computing technology can provide many advantages for supporting Internet of Thing (IoT) applications. These advantages include better low latency support, mobility, location awareness, scalability, and efficient integration with other systems such as cloud computing. At the same time, Unmanned Aerial Vehicle (UAV) technology has been significantly developed and used for many applications. UAVs can provide fast, cost-effective, and safe deployments for many civil and military applications. This paper proposes the UAV Fog, a UAV-based Fog computing platform for the Internet of Things applications. In this proposal, we aim to utilize the advantages and features of both technologies, Fog computing and UAVs, to effectively support some IoT applications. UAVFog provides fast deployment of fog capabilities at remote or challenging locations to effectively support dynamic IoT applications. A UAV equipped with fog computing capabilities travels to a specific location when needed and remains in that location to support the local IoT applications. In this paper, we discuss some scenarios for such deployments, their advantages, and the issues involved when using the proposed model.
Apocrine Encapsulated Papillary Carcinoma of the Breast: The First Reported Case with an Infiltrative Component

Apocrine encapsulated papillary carcinoma (EPC) of the breast is a rare neoplasm, and only 10 cases have been reported in the literature to date. Although EPC by definition lacks a peripheral myoepithelial layer, all previously published apocrine EPC cases were clinically indolent and lacked a conventional invasive component. Herein, we report the 11th case of apocrine EPC, which had a conventional invasive carcinoma component and provides evidence of the malignant potential of this entity. We postulate that apocrine EPC is most likely a morphological variant of conventional EPC, with the same unpredictable malignant potential as non-apocrine cases.
Comparative analysis on features extraction strategies for GPCR classification

Protein is an alphabetical sequence of amino acids, this form of sequence can never be processed by data mining and machine learning algorithms that are needed for numerical data. Feature extraction strategies are used to transform the alphabetical sequence into a feature vector representing the properties of this sequence. But each method produces an attributes vector of different size and properties to others. Our work aims to compare three most used feature extraction strategies that are AAC, PseAAC and DC using five selected machine learning algorithms deployed on weka platform, they are evaluated based on Accuracy, F-measure, MCC and error rate measures. This comparison helps us to decide what feature extraction strategy is best suited to work while applying computationally expensive selected machine learning algorithms on a protein sequence data. Experiments suggested that AAC, PseAAC and DC methods would be optimal on GPCR classification at sub sub-family level using MLP algorithm. While working with other classifiers would be optimal if we do not use a huge subset of data so a grand class number. Hence this study concludes that a better performance would be reached when a good classifier is established.
Application of deep learning image-to-image transformation networks to GPR radargrams for sub-surface imaging in infrastructure monitoring

The corrosion of reinforced concrete sewer pipes in aging infrastructure is a serious ongoing issue and as such, research into technologies that allow for autonomous site assessments are of major priority to wastewater managing utilities. The use of Ground Penetrating Radar (GPR) is being investigated for providing sub-surface images of sewer crowns. Due to the nature of GPRs, the analysis of a radargram for identifying sub-surface features is non-intuitive and usually require the use of an expert. Traditional methods to help ease analysis involve the use of Synthetic Aperture Radar (SAR) and migration techniques. These techniques refocus dipping and point reflectors to be closer to their true shape but require an accurate velocity model to be effective. This is not always readily available and difficult to estimate especially in regards to sewer conditions. We instead provide an alternative and present a deep learning framework for transforming ground penetrating radargrams into sub-surface permittivity maps. An evaluation of various state-of-the-art deep learning architectures is also conducted, comparing the performance of different objective functions and identifying current limitations. This work provides the base for further exploration of the application of deep learning for use in infrastructure monitoring.
The Contribution of Sulfated Glycosaminoglycans to the Inflation Response of the Human Optic Nerve Head

Purpose In this study, we measured the effect of the removal of sulfated glycosaminoglycans (sGAGs) on the pressure-induced strains of the human lamina cribrosa (LC). Methods We applied an ex vivo inflation method to measure the three-dimensional (3D) deformation response of six human LCs to pressure, before and after the degradation of chondroitin and dermatan sulfates. The experiment used a laser-scanning microscope (LSM) to acquire the second harmonic generation (SHG) signal of the collagen structure in the LC. Digital volume correlation (DVC) was used to calculate the deformation in the LC after a change in pressure from 5 to 45 mm Hg. Results The average strains between 5 and 45 mm Hg in the LC decreased significantly after sGAG degradation (P ≤ 0.03), with the greatest change occurring in regions of previously high strain (P ≤ 0.003) and the peripheral regions of the LC (P ≤ 0.02). The stiffening effect was greater in the LC of middle-aged (42–49 years) donors compared with those of older (64–88 years) donors (P < 0.0001). Conclusions The LC experienced less strain at the same pressures after most sGAGs were removed. These results suggest that the natural decrease in sGAGs within the LC with age may contribute to the stiffer inflation response of older LC to IOP. Likewise, the increase in the amount of sGAGs observed in the LC of glaucomatous eyes, may contribute to a more compliant LC, which may affect the susceptibility and progression of axon damage.
Jamming of UAV remote control systems using software defined radio

Unmanned aerial vehicles (UAVs) have become widely available and their potential unlawful usage introduces new security risks. It has therefore become highly desirable to restrict the unauthorized usage of UAVs in certain areas such as airports, nuclear power plants, etc. Most commercially available UAVs rely on spread spectrum techniques, such as direct sequencing and frequency hopping, in the remote control systems to reduce the impact of interference from neighboring communication systems (including e.g. other remotely controlled UAVs), to increase resistance to jamming and to prevent detection. In this paper, an efficient protocol-aware UAV remote control jamming system is proposed and implemented using an open-source software defined radio (SDR) platform. Experimental results show that for FASST and ACCST remote control systems, the proposed jammer achieves successful jamming at relatively low jam-to-signal ratios (JSRs) as compared to a sweep jammer, therefore requiring less transmitted power to achieve similar results. Furthermore, the proposed jammer impacts other communication systems significantly less than the sweep jammer.
Biocontrol of Orchid-pathogenic Mold, Phytophthora palmivora, by Antifungal Proteins from Pseudomonas aeruginosa RS1

Abstract Black rot disease in orchids is caused by the water mold Phytophthora palmivora. To gain better biocontrol performance, several factors affecting growth and antifungal substance production by Pseudomonas aeruginosa RS1 were verified. These factors include type and pH of media, temperature, and time for antifungal production. The results showed that the best conditions for P. aeruginosa RS1 to produce the active compounds was cultivating the bacteria in Luria-Bertani medium at pH 7.0 for 21 h at 37 °C. The culture filtrate was subjected to stepwise ammonium sulfate precipitation. The precipitated proteins from the 40% to 80% fraction showed antifungal activity and were further purified by column chromatography. The eluted proteins from fractions 9–10 and 33–34 had the highest antifungal activity at about 75% and 82% inhibition, respectively. SDS-PAGE revealed that the 9–10 fraction contained mixed proteins with molecular weights of 54 kDa, 32 kDa, and 20 kDa, while the 33–34 fraction contained mixed proteins with molecular weights of 40 kDa, 32 kDa, and 29 kDa. Each band of the proteins was analyzed by LC/MS to identify the protein. The result from Spectrum Modeler indicated that these proteins were closed similarly to three groups of the following proteins; catalase, chitin binding protein, and protease. Morphological study under scanning electron microscopy demonstrated that the partially purified proteins from P. aeruginosa RS1 caused abnormal growth and hypha elongation in P. palmivora. The bacteria and/or these proteins may be useful for controlling black rot disease caused by P. palmivora in orchid orchards.