Miracle-dz/UniFAR-FTUs huggingface dataset:
Utilizing UAV Payload Design by Undergraduate Researchers for Educational and Research Development

An undergraduate team consisting of mechanical and electrical engineering students at the University of North Dakota developed an electro-optical and un-cooled thermal infrared digital imaging remote sensing payload for an Unmanned Aerial Vehicle (UAV). The first iteration of the payload design began in the fall of 2005 and the inaugural flight tests took place at Camp Ripley, Minnesota, a National Guard facility, in the fall of 2006 with a corporate partner. The second iteration design with increased performance in object tracking and data processing is expected to fly in the summer of 2007. Payload development for integration into a UAV is a process that is not currently well defined by industrial practices or regulated by government. These processes are a significant part of the research being conducted in order to define the “best practices. ” The emerging field of UAVs generates tremendous interest and serves to attract quality students into the research. As with many emerging technologies there are many new exciting developments, however, the fundamentals taught in core courses are still critical to the process and serve as the basis of the system. In this manner, the program stimulates innovative design while maintaining a solid connection to undergraduate courses and illustrates the importance of advanced courses. The payload development was guided by off-the-shelf components and software using a systems engineering methodology throughout the project. Many of the design and payload flight constraints were based on external factors, such as difficulties with access to airspace, weather-related delays, and ITAR restrictions on hardware. Overall, the research project continues to be a tremendous experiential learning activity for mechanical and electrical engineering students, as well as for the faculty members. The process has been extremely successful in enhancing the expertise in systems engineering and design in the students and developing the UAV payload design knowledge base and necessary infrastructure at the university.Copyright © 2007 by ASME
Biofuels-related materials deterioration in biorefineries, transportation and internal combustion engines: A technical review

ABSTRACT Biofuels, like any high-affinity chemical mixtures; can cause tribological effects at interfaces with metallics (ferrous-nonferrous) and non-metallics due to medium assisted activation of corrosion by unsaturated components. The damages; corrosion and tribological effects on surfaces (abrasive wears and edge/cosmetic corrosion), also include contamination and biofuels replacement due to quality decrease. The most common phenomena include the oxidation of biodiesel which increases its affinity towards metallic counterparts, i.e. automotive parts or processing apparatus, via formation of peroxide compounds by oleic acid, linoleic acid, and linolenic acids. This corrosion receptive medium causes pitting; due to high water content and high electronegativity of dissolved oxygen, and galvanic corrosion; due to high electrical conductivity. The main factors for higher aggressive corrosivity of biofuels can be summarized as high electrical conductivity, polarity, solubility, and hygroscopicity. This paper closely reviews the materials deterioration in contact with biofuels and possible corrosions.
New approach for hybrid strip-map/spotlight SAR data focusing

A new algorithm is presented for processing SAR data acquired in the hybrid strip-map/spotlight SAR configuration whose acquisition mode allows the generation of microwave images with an azimuth resolution better than that obtained in the strip-map case and with an imaged area larger than that achieved in the spotlight operation. The algorithm extends the focusing capability of conventional strip-map processing techniques to the hybrid SAR data; this result is achieved by generalising a recently proposed two-step focusing technique for spotlight SAR data processing, the spotlight mode being a particular case of the more general hybrid one. The key point of the procedure is the first filtering step which implements an azimuth convolution between the raw data and a chirp signal whose rate is selected, in the generalised approach, depending on the characteristics of the hybrid acquisition mode. Following this stage, standard strip-map processing procedures can be used to implement the second processing step, leading to fully focused SAR images. The algorithm, mainly oriented to spaceborne systems, is simple and efficient and allows the design of a generalised processing code suitable for data acquired in the hybrid strip-map/spotlight SAR configuration including the strip-map and spotlight modes as special cases. Experiments carried out on simulated data clarify the rationale of the method and confirm its validity.
Using an adaptive INS, monopulse MUSIC, and STAP (AIMS) for targeting

Angle estimation from target signals suffers from mainbeam jamming. One way to counteract the problem is to integrate sensor data from multiple sensors. An adaptive monopulse multiple signal classification (MUSIC) algorithm discerns the azimuth and elevation angle estimation or true spectrum amongst jamming. Relying solely on the algorithm results in an undesirable probability of error in target identification, classification and recognition. By integrating the azimuth and elevation signals from an integrated navigational system (INS) and monopulse radar, the probability of accurate detection of target location increases. The AIMS algorithm is designed for targeting and integrates sensor signals from an adaptive INS system which has repeated measurement location updates from a ground-based target, a four-aperture monopulse radar, which adaptively reduces mainbeam jamming from the MUSIC algorithm for reliable angle estimation, and a space-time adaptive processor (STAP) which isolates targets in the presence of clutter. The results show that the sensor integration of the AIMS algorithm effectively and efficiently identifies the correct target information.
Digital Amplitude-Phase Keying with M-Ary Alphabets

Signal sets employing amplitude and phase keying (APK) with large alphabets conserve bandwidth and do not require as high a signal-to-noise ratio (SNR) as phase-shift keying (PSK). Twenty-nine empirically generated APK sets with M -ary alphabet sizes from 4 to 128 are investigated to determine optimum designs. Selected sets are compared on the basis of a symbol-error-probability bound for both average and peak SNR. Results are presented in the form of symbol error curves. The degradation caused by nonlinearities in a typical TWT amplifier is examined. The effects of AM-AM and AM-PM distortion on APK are presented as a function of power backoff for single-carrier operation (when APK is at the greatest disadvantage compared with PSK). Modem implementation methods, including carrier phase reconstruction techniques, are discussed for basic APK designs.
Predicting Social Reopening Following COVID-19 Lockdown Using Bounded Rationality and Threshold Models

The exercise of reopening optional social spaces following the COVID-19 lockdowns presents each individual with a complex problem in determining whether or not to attend these spaces given how the risks of virus transmission scale with crowding. In order to tackle this problem while recognizing individual cognitive capacity limits, this paper used a simulation model based on the El Farol Bar Problem and generated a population of agents relying on simple predictive strategies to determine their attendance to a retail location. It was determined that the more heterogeneous the threshold for crowding among agents was, the less variance there was in overall attendance numbers. This stability in daily attendance comes at the expense of the ability of the most cautious members to enjoy recreational spaces as these locations become the realm of only those least concerned with potential crowding. © Cognitive Science Society: Comparative Cognition: Animal Minds, CogSci 2021.All rights reserved.
Design of Dual-band Reconfigurable Substrate Integrated Waveguide Cavity-backed Slot Antenna Array

ABSTRACT In this paper, a dual-band reconfigurable substrate-integrated waveguide (SIW) cavity-backed slot antenna 1 × 8 linear array is presented with dual states. The proposed SIW antenna array combines the features of the conventional metalized cavity-backed patch arrays such as surface wave suppression, high efficiency with low-manufacturing cost. The basic element has been designed, fabricated and the performance has been verified in the outdoor antenna test range. Here, PIN diodes have been used as a switching device to achieve the reconfigurability with dual-band operation. A corporate feed network has been designed and integrated with the antenna to make it as a linear array.
3D Digital Imagery a Solution for the Teaching of Osteology: Example of the Thoracic cage

Osteology is a fundamental discipline, its classical teaching becomes difficult because of plethora of students and shortage of bony parts. It’s in this context that we have made, from 3D volume imaging, a modeling of the rib cage as a test using a software for post-treatment of CT images in order to propose a pedagogical tool for studying thorax’s skeletal and adding descriptions with the help of classical works. This was a prospective study involving 27 patients aged between 35 and 45 years. The scanners used were HITACHI ECLOS 16 cuts. Once the CT scan was selected, the DICOM data was transmitted to the post-processing console. The images were processed on the console "Aquarius Intuition Edition Version 4. 4. 7. 855113", for one patient we used Veiwer Osirix 10.6. 8 Mac. All bones have been dynamically described thanks to the volume rendering. We thus obtained volumetric reconstructions of three-dimensional CT images of the different bone structures superimposed on those taught in classical anatomy practical work. We obtained a scenario of practical work in the form of a slide show that the teacher can use for works with or without model and even remotely. The virtual reality obtained with the 3D reconstructions of CT scans of the rib cage is a tool for self-learning of osteology for students but also a way for teachers to do practical work without having to use models, and even at a distance. KEY WORDS: 3D imaging, Teaching, Tomodensitometry, Osteology.
Mobility Characterization and Dynamical Analysis of a Surface Hopper for Low-gravity Environments

The growing scientific interest in the exploration of low-gravity celestial bodies, such as asteroids, comets, or small planetary satellites, has developed a higher need for mobile surface missions. Internally-actuated hopping systems provide an efficient and viable opportunity to achieve surface mobility under such environments, with low operational cost. The rover’s actuation using flywheels, implements a high control, design flexibility, and enclosed mobility mechanism. Through self-righting maneuvers, fewer actuators are needed and a simpler single-axis hopping motion can be achieved. Throughout this work, the rover’s hopping mobility based on these configurations is studied. The dynamics and simulations resulted in innovative proposed implementations to the spike configurations. It is showed the interest of applying a variable spike angle configuration and a variable spike length configuration. The application of a spike that can adjust and control its angle improves significantly the hop distance achieved for different surface inclinations. The implementation of a spike that can change its length works as a trade-off solution between more efficient hops, with shorter spikes, and better transverse capability over higher obstacles, with longer spikes. This later variation presents mainly a potential contribution to the landing stage, however a further study of this application is needed.
Uncooled microbolometers at DRS and elsewhere through 2013

DRS history in microbolometer and uncooled focal plane array (UFPAA) development mimics that of the entire industry. The history extends over fifteen years as array pitches moved ever-smaller from 51uum to 25um to 17um, and now something smaller than 17uum. The uncooled microbolometer makers have transitioned through smaller pitches about every six years. This has been done while maintaining a noise equivalent temperature difference (NNETD) performance of 20-50mK, and maintaining a thermal time constant (TTTC) of 10-20mmSec. Once a newer pitch is developed to a performance level matching the previous pitch, development on the next smaller pitch is already underway. In this manner, the industry has progressed through smaller pitches without a fundamental performance improvement when measured in NNETD or in TTTC, or more specifically in NNETD*TTC product. Hence, a more-encompassing metric for tracking performance through time would involve the NNETD, the TTCC, and some indicator of bolometer size. Ann NETD*TTC**Area metric, as the appropriate metric for including bolometer size, will be proposed, theoretically justified, and discussed here. A rank-ordering of bolometers which have been published through 22013 is also presented in three charts, one for NETTD, one for NEETD*TTC, and lastly one for NETD*TTC**Area.
A data mining approach to optimise shelf space allocation in consideration of customer purchase and moving behaviours

A good shelf space allocation strategy can help customers easily find product items and dramatically increase store profit. Previous studies generally relied on the space elasticity formula to optimise space allocation models, but space elasticity requires estimates of many parameters, resulting in high costs and frequent errors in the mathematical models. In this study, a three-stage data mining method is proposed for solving the shelf space allocation problem with consideration of both customer purchase and moving behaviours. In the first stage, the customer’s purchasing behaviour is derived from records of previous transactions, while moving behaviour is collected through radio frequency identification systems. In the second stage, the A priori algorithm is applied to obtain frequent product association rules from purchase transactions. In addition, the UMSPL algorithm is adopted to derive high-utility mobile sequential patterns from customer mobile transaction sequences. In the third stage, all product items are classified as either major, minor or trivial according to a set of criteria. A Location preference evaluation procedure is then developed to calculate location preference if a minor item is placed at a given section of the store. Based on the location preference matrix, minor items are reassigned to optimal shelves. The experimental results show the proposed method can reassign items to suitable shelves and dramatically increase cross-selling opportunities for major and minor items.
Robustness Evaluation of Convolutional Neural Networks for Malware Classification

In a world increasingly connected with smart devices, smartphones, tablets and servers in constant communication with each other, malware is a serious threat for the security of users and systems. Every day they are becoming more sophisticated and can rely on a growing attack surface. Traditional malware analysis techniques are becoming unable to deal with this growth; to this reason new approaches are arising. Among these, the most promising ones aim to exploit the disruptive accuracy and flexibility of convolutional neural networks (CNNs) to realize innovative techniques to detect and classify malware by using an intermediate image-based representation. However, several papers have highlighted the natural tendency of CNNs to be fooled by perturbations applied on the input. In this paper we benchmark four different CNNs widely used for images. To this purpose, we have specialized the CNNs, through transfer learning, to classify malware belonging to 9 different families. Then, we have evaluated their robustness against the obfuscation of the malware executable. All the CNNs achieved an impressive classification accuracy on both the original and the obfuscated datasets confirming their suitability for malware classification.
Comparison of the Effectiveness of Various Algorithms on a Recommendation System

Recommender systems attempt to identify user information by proposing related products or resources that customers may be interested. Recommender methods have attracted attention in the ﬁ elds of information technology, ecommerce, and so on, by essentially fertilizing from a standard collection of decisions that led consumers to ﬁ nd information of interest. This research focuses on the three common recommendation systems: Collaborative Filtering, Content-Based Filtering, and Hybrid recommendation systems. For the purposes of this analysis, the well-known MovieLens dataset has been used. The assessment considered both the quantitative and qualitative dimensions of the recommendation systems. This paper describes the ﬁ eld of various recommendation approaches and related fundamental techniques. Any algorithm in this ﬁ eld has both bene ﬁ ts and drawbacks. The goal of the research is to bring various algorithms to the test in order to ﬁ nd the right one based on the layout of the dataset and the researchers’ goals.
Compact dual‐band slot antenna with capacitor loading

A compact dual‐band slot antenna with capacitor loading is proposed for the wireless local area network bands (2.4–2.49 and 5.15–5.35 GHz). The antenna is composed of a modified L‐shaped slot and a capacitor. The capacitor is used to generate two surface‐current paths on the ground and to miniaturize the antenna size. The proposed antenna has an omni‐directional radiation pattern with antenna peak gains of 2.2 dBi at 2.44 GHz and 2.7 dBi at 5.25 GHz. Radiation efficiencies are greater than 60% over the operating frequency bands. © 2014 Wiley Periodicals, Inc. Microwave Opt Technol Lett 56:1653–1658, 2014
Fostering Learner Agency in a Digital Literacies Course in Egypt: Reflections on Several Iterations

Nurturing learner agency can foster critical citizenship for young adults in a relatively safe environment. The American University in Cairo (AUC) has a mostly Egyptian student body, coming from diverse educational backgrounds: some have experienced schooling which centers around memorization and teacher authority, thus stifling agency and critical thinking. In addition, we are surrounded by a culture and political environment that does the same: an authoritarian government that makes questioning authority and free speech in general risky. This chapter reflects on attempts to create space for learner agency over three years of teaching the course, Digital Identities and Digital Literacies in an Intercultural Context. Four co-authors reflect on these three approaches:
Review and Analysis of Different Approaches to Semantic Level Question Answering and Information Retrieval

: Question Answering and Information Retrieval plays an important application of Natural Language Processing and Data Mining. It aims to retrieve relevant documents for natural language queries. Here we performed a survey on different models for Information Retrieval and Question Answering. And also performed the comparison and analysis of various models. From the literature, we identified that information retrieval systems use the methods from Data Analytics, Natural Language Processing, Machine Learning, and Neural Network etc. Also, we noticed there are many works are done in the English language, but a few works are done in native languages such as Malayalam, Kannada, and Tamil etc.
In the blink of an eye? Evidence for a reduced attentional blink for eyes

Eye contact serves as an important social signal and humans show a special sensitivity for detecting eyes. Here, we asked whether people’s sensitivity to eyes would enable them to overcome temporal limitations in visual attention. We used an “attentional blink” (AB) paradigm, in which the second of two visual stimuli presented in quick succession typically cannot be detected. Participants performed a rapid serial visual presentation (RSVP) task and were asked to identify, within a stream of symbols, a target and to detect whether the target was succeeded by a probe. The probe was either an image of an eye (with direct gaze) or of a star. As expected, participants’ detection rate for the star was poor, demonstrating the typical attentional blink. Crucially, detection rate for the eye was significantly better. This reduced attentional blink suggests that people’s sensitivity to eyes is strong enough to circumvent fundamental limitations in visuotemporal attention.
Study on Dynamic Equilibrium of Sediment Transport by Qingshuigou Course of the Yellow River

The multi-object application of the Xiaolangdi Reservoir and water and sediment regulation have greatly changed flow and sediment conditions emptying into the Yellow River Estuary. By use of flow and sediment field data at the Lijin Hydrological Station and river cross-section elevation data during 2001~2010, the paper has analyzed characteristics of the Yellow River Estuary in terms of incoming flow and sediment conditions, main flume area, average river longitudinal section and river length. The results show that annual total water volume emptying into the Estuary since 2003 has maintained about 200×108 m3, annual total sediment 1.77×108 t, whole annual average sediment concentration 9.3kg/m3, which are stable and beneficial for dynamic equilibrium of sediment transport. Interannual stability of main flume area, average river bed elevation and river length since the Lijin Section during 2007-2010 indicate that current Qingshuigou Course of the Yellow River has achieved dynamic equilibrium of sediment transport.
Numerical Objective Assessment Using Structural Similarity for Diffuse Optical Reconstructed Images

The work within this study develops an algorithm based on the structural similarity index to assess numerically between reconstructed images with a reference image to separate the homogeneity and heterogeneity for diffuse optical tomography. Global geometry and region of interest assessment have been measured to yield the similarity. The results indicate that the mean of structural similarity index shows potential performance to distinguish between visible and invisible inclusion inside the model. Therefore, the structural similarity index may promise to assist the image assessment for evaluating breast structural information.
A method of direct corona imaging on a dielectric transparency

The standard scheme of Kirlian photography is modified to have water on top of a thin mylar dielectric layer, underneath which the object is placed. Water serves both as an electrode and as a constant-temperature heat reservoir. HV is applied between object and water to create sustained corona discharges. Experiments showed that, under an AC or pulsating-current excitation over a duration of minutes, a permanent optical image becomes retained on the mylar surface, which is then usable for projection or for direct viewing with slanted lighting. Direct current approaches were found inefficient to produce the same results. A thermo-plastic theory is hypothesized to account for the observations. <<ETX>>