Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of target acquisition difficulty using recognition distance to measure required retinal area

The psychophysical method of limits was used to measure the distance at which observers could distinguish military vehicles pho- tographed in natural landscapes. Obtained from the TNO-TM Search - 2 dataset, these pictures either were rear-projected 35-mm slides or were presented on a computer monitor. Based on the rationale that more dif- ficult vehicle targets would require more visual pathways for recognition, difficulty of acquisition was defined in terms of the relative retinal area required for recognition. Relative retinal area was derived from the in- verse square of the recognition distance of a particular vehicle relative to the distance of the vehicle that could be seen furthest away. Results are compared with data on the time required to find the vehicles in these pictures. These comparisons indicate recognition distance thresholds can be a suitable means of defining standards for the effectiveness of vital graphic information; and the two methods are complementary with respect to distinguishing different degrees of acquisition difficulty, and together may provide a means to measure the total information process- ing required for recognition. © 2001 Society of Photo-Optical Instrumentation Engi- neers. (DOI: 10.1117/1.1389282)
Differentiating Congestive and Non-congestive Losses on TCP Endpoint

Packet loss in IP networks can be congestive due to IP interrupt queue overflow on the nodes, and non-congestive due to hardware failure, signal-fading or obstacles. Recognition of two types of losses can largely help TCP endpoints in making right decisions. In this paper we apply the Visualized IP-based Network Simulator (VINS) to characterize the key differences between congestive packet losses and that of due to link disruption, which is noncongestive and commonly seen in wireless networks. Based on the analyses, suggested improvements for wireless TCP endpoints are proposed on both kernel and application levels in terms of avoiding useless keep-alive probing and congestion window tuning, but re-routing and re-establishing new connections.
A Generic Approach for Dynamic Business Model Evaluation

The term business model has gained tremendous attention in the recent years. However, the consensus over concrete description of the term is still awaited. Diverse and unsharp descriptions of this term complicate business model evaluation, especially when diverse granularities are to be considered. Both concepts (business model and business model evaluation) have caught relatively lesser attention of the research community. Although the stakeholders of business models have different interpretations of it, which is strictly driven by their positions in the business landscape, all of the stakeholders have mutual agreement on the fact that the business model evaluation should be realistic and accurate. Common business models are based on approximations of existing templates and structures provided commercially or freely available in the state of the art. However, many of the proposed business models were developed on the basis of specific situations. Hence, business model structures hinder the flexibility and compatibility to vast variety of businesses. In order not to develop a distinct evaluation concept for each business model, the challenge is to create a universal business model with an appendant evaluation concept. In this study, we addressed the aforementioned issues and proposed a more dynamic, modular, and richer business model evaluation framework. This hierarchical framework deviates from the commonly used block structures. On the one hand, it helps avoiding the complexity of evaluation (especially when the business model blocks are dynamic), and, on the other hand, provides a transparent and easy way of interactions among evaluation functions residing at different hierarchical levels. With the view to attaining the objective of accuracy in evaluation, in this work, we proposed various concepts, namely, criticalness/non-criticalness of the evaluation parameters, interdependencies among the blocks of the business, etc. Our experiments and validations advocate that the proposed approach exhibits
Information Theory, Memory, Prediction, and Timing in Associative Learning

Two information-theoretic principles—maximum entropy, and minimum description length—dictate a computational model of associative learning that explains cue competition (assignment of credit) and response timing. The theory's primitives are two cue types—state cues and point cues—and two stochastic distributions. The preferred stochastic model gives the relative code lengths for an efficient encoding of the data already seen; it predicts the data not yet seen; and the associated hazard function roughly predicts the observed timing of anticipatory (conditioned) behavior. State cues use the exponential distribution to encode, predict and time; point cues use a form of the Gaussian distribution that allows for event failure. An implementation of the refined minimum-description-length approach to stochastic model selection (Rissanen 1999) determines which stochastic model best compresses the data, and hence which is the best predictive model for a given protocol. The model brings into sharp focus the need to focus neurobiological inquiry on the coding question in memory.
A New Hybrid Power Configuration In HEV and Its Driving BLDC Development

Hybrid electric vehicle (HEV) that has the advantages of high performance, high fuel efficiency, low emission, and long operating range is focused on nowadays. A new hybrid power configuration used in HEV is presented with different control strategies and HEV performances when equipping different weight of fuel power and battery one. In order to realize the new hybrid power configuration especially in the refitted HEV, fractional-slot concentrated-winding BLDC with higher rated spinning speed is given and the prototyped one is developed and fabricated which satisfies successfully the requirements of high performance and demission restriction for the refitted HEV.
The Effects of Inquiry-Based Integrated Information Literacy Instruction: Four-Year Trends

The purpose of this study was to examine the effects of four-year integrated information literacy instruction via a framework of inquiry-based learning on elementary students’ memory and comprehension. Moderating factors of students’ academic achievement was another focus of this study. The subjects were 72 students who have participated in this study since they entered an elementary school in Chiayi district. This elementary school adopted the integrated information literacy instruction, designed by the researchers and elementary school teachers, and integrated it into various subject matters via a framework of inquiry-based learning, such as Super3 and Big6 models. A series of inquiry-based integrated information literacy instruction has been implemented since the second semester of the subjects’ first grade. A total of seven inquiry learning projects has been implemented from grade one through grade four. Fourteen instruments were used as pretests and posttests to assess students’ factual recall and conceptual understanding of subject contents in different projects. The results showed that inquiry-based integrated information literacy instruction could help students memorize facts and comprehend concepts of subject contents. Regardless of academic achievements, if students would like to devote their efforts to inquiry processes, their memory and comprehension of subject contents improved effectively. However, students of low-academic achievement might need more time to be familiar with the inquiry-based learning strategy.
Generic MIDI devices as new input for specialized software

There are plenty of sublime devices, including input devices, for all kinds of specialists working with computers available on the market. Furthermore, the more specific solutions are needed, the more expensive and complicated they are. At the time when many people prefer to try as many things as possible before selecting the specific learning paths, both high price and high entry threshold, can appear as blockers. In the paper, there are selected some hardware and software solutions for facilitating the work of the professionals , who expect more analog-like interfaces and more natural ways to control computers presented. Additionally, the authors describe original software and hardware solution that allows the use of wide range MIDI devices as custom input devices. The concept of the software made is being presented, as well as some results of initial interaction of different kind of professionals and the proposed solution software and hardware.
Outdoor Sonar Sensing

High-precision applications of airborne ultrasonic sensory systems have traditionally been restricted to indoor environments. The number of studies that have proposed the use of ultrasonic sensors outdoors is very limited and most times in a similar way that it has been made indoors. In applications like the guidance of vehicles and mobile robots, ultrasonic sensors are usually integrated in a more complex multi-sensory system, where they have been assigned low-precision tasks. Among these tasks are, for example, the detection of very close obstacles with which there exists an imminent risk of collision, or the coarse ranging of large navigation landmarks (Langer & Thorpe, 1992), (Maeyama et al., 1994) (Guo et al., 2002). Sonar’s reputation as an unreliable sensing technology for outdoor applications is mainly due to the large influence that meteorological parameters have on the propagation of ultrasonic signals, which is a direct consequence of the mechanical nature of these waves. Changes in temperature and humidity, the presence of fog or rain in the atmosphere, and wind-induced refraction can cause strong variations in the attenuation of acoustic waves. As a result, a classical sonar system based on threshold detection of the signal envelope can provide very different results depending on the operating conditions. Furthermore, acoustic noise sources are more likely to be found outdoors. Aircrafts, pneumatic drills, bridge vibrations or even corona effects in high voltage cables are examples of ultrasonic sources which could render sonar in systems completely useless in certain environments. To overcome these problems, the research with ultrasonic sensors outdoors, has evolved to the use of special signal processing techniques such as the continuous transmission frequency modulated (CTFM) ultrasonic sensor used for path edge detection (Ratner & McKerrow, 2003), the use of crosscorrelation with transmitted patterns for an outdoor sonar (Tanzawa et al., 1995) or the wind compensation method based on differential emitters for a positioning system (Jimenez & Seco, 2005). The first part of this chapter describes in detail the phenomenology associated with the propagation of acoustic waves in the atmosphere, placing an emphasis on the effects of the different mechanisms over the entire range of ultrasonic frequencies used in air. In the second part of the chapter, an outdoor sonar prototype is presented as an example of how the most recent signal coding and pulse compression techniques can be used to improve the reliability of sonar systems when operating under varying meteorological conditions. It will be seen that the transmission of ultrasonic encoded signals in the atmosphere entails a new O pe n A cc es s D at ab as e w w w . in te ch w eb . o rg
VLSI Hardware Devices for Acquisition and Processing of Multielectrode Neuronal Signals

Biological cells are characterized by highly complex phenomena and processes that are, to a great extent, interdependent. To gain detailed insights, devices designed to study cellular phenomena need to enable tracking and manipulation of multiple cell parameters in parallel; they have to provide high signal quality and high spatiotemporal resolution. To this end, we have developed a CMOS-based microelectrode array system that integrates six measurement and stimulation functions, the largest number to date. Moreover, the system features the largest active electrode array area to date (4.48×2.43 mm2) to accommodate 59,760 electrodes, while its power consumption, noise characteristics, and spatial resolution (13.5 μm electrode pitch) are comparable to the best state-of-the-art devices. The system includes: 2,048 action-potential (AP, bandwidth: 300 Hz to 10 kHz) recording units, 32 local-field-potential (LFP, bandwidth: 1 Hz to 300 Hz) recording units, 32 current recording units, 32 impedance measurement units, and 28 neurotransmitter detection units, in addition to the 16 dual-mode voltage-only or current/voltage-controlled stimulation units. The electrode array architecture is based on a switch matrix, which allows for connecting any measurement/stimulation unit to any electrode in the array and for performing different measurement/stimulation functions in parallel. *Authors contributed equally. Contribution of J. Dragas: Electrode Array, Digital Control, Functional and Physical Integration at System Level Chapter 2: Multi-Functional HD-MEA System 22 2.
The acquisition of extended ergativity in Mam, Q’anjob’al and Yucatec

Ergativity in Mayan languages is realized in the cross-referencing features on verbs rather than as case marking features on noun phrases. Overt absolutive markers appear with intransitive verbs. Some Mayan languages extend the ergative markers to intransitive verbs in aspectless complement clauses. The languages also make changes to transitive verbs in the same aspectless contexts. We evaluate how Mam, Q’anjob’al and Yucatec children acquire the extension of the ergative markers to intransitive verbs and the changes to transitive verbs in aspectless clauses. In each language we analyzed data of three children in the age range of 2;0 to 3;0. Our findings show that: (i) although the three languages have similar patterns of extended ergativity, children are sensitive to language-specific constraints on extended ergativity; (ii) the input frequency does not predict the acquisition of extended ergativity. We conclude that the structure of each language is responsible for the acquisition of extended ergativity.
Virtualization and Software-Defined Infrastructure Framework for Wireless Access Networks

Virtualization and service-oriented architecture are important concepts that triggered the rapid evolution of cloud computing technologies. Network infrastructure virtualization is now possible by applying similar concepts in conjunction with recent advances in softwaredefined technologies. Since wireless technologies will play an important role in the future of networking technologies, this thesis proposes Aurora, a virtualization framework and testbed platform for supporting multiple types of virtualization techniques and architectures specifically applied on wireless technologies. In the first half of this thesis, a background survey of works in the recently-emerged field of “wireless virtualization” is made in order to identify potential applications, common trends and future research directions. This is followed by the presentation of three main perspectives: flow-based virtualization, protocol-based virtualization and spectrum-based virtualization. Then, a hypothetical ecosystem scenario of a future virtualized wireless infrastructure in which these perspectives coexist is discussed along with some of the challenges and requirements for a sustainable wireless virtualization framework. In the second half of this thesis, the general architecture and design principles behind Aurora are explained. Aurora is designed to fulfil multiple roles as a powerful tool to combine multiple wireless virtualization technologies, a research platform for developing new virtualization architectures and a service-oriented wireless infrastructure manager. Finally, the first iteration of the software implementation of Aurora inside the Smart Applications on Virtual Infrastructure (SAVI) testbed is exposed in order to demonstrate the feasibility of the framework.
Comparing Multiple Social NetworksUsing Mutiple Dimensional Scaling

This paper explores the comparison of social networks and gives a description of a method I developed for comparing many social networks. I developed this new technique by using multi-dimensional scaling to differentiate between several social networks. Others have used various methods and factors for comparing these social networks, such as descriptive network statistics, triads census and network similarities. These other methods compare only one feature of the given networks and are numerical in output. This new method has the advantage of comparing several network features and being an easy graphical method for the end user to compare multiple social networks.
Current Passing Through Grounding System of High Voltage Transformer Substation and Parameters Impacting on It When Lightning Strikes on the Grounding Wire of Transmission Line

(Abstract) Current injecting a grounding system of high voltage transformer substation decides the amplitude and the voltage distribution along the grounding grid [1]-[2]. Therefore, the determination of short circuit current at substation is always cared by the designers. [9] suggested a new method to calculate the current passing through grounding system of high voltage substation when lightning strikes on the grounding wire of transmission line regardless of the impacting parameters. This paper studied clearly the influence of above parameters and from this, some interesting results were received.
Online review courses as preparation for first term remedial exams

At Universidad Carlos III de Madrid we have developed a review course (R-Course) with a SPOC structure intended for students who failed the first term regular exams. The purpose of the course is to help students prepare for the remedial exams at the same time they study the second term courses. The R-Course is implemented in an Open-EDX platform that holds digital documents, both theory and solved exercise videos, platform integrated exercises, and forums. The content of the course is divided in videos of less than 10 minutes in length, allowing students to include the R-Course in any schedule and making it compatible with the second term courses. Interactive platform integrated exercises have been devised under different types of methodologies to increase the motivation of the students, and the platform forums give students and tutors a space to discuss and interact for a well-rounded academic experience.
The knowledge connections analyzer

We describe the development of an SQL-based formative assessment system, the Knowledge Connections Analzyer (KCA), which is designed to provide evidence on four general questions that students may have about their work in an asynchronous online discussion environment: (1) Are we collaborating? (2) Are we putting our knowledge together? (3) How do ideas develop over time? (4) What is happening to my stuff? These questions are inspired by Scardamalia’s knowledge-building principles. The KCA first converts a Knowledge Forum® tuplestore database to SQL format, and then executes queries relevant to these four questions. It Students and their teacher can employ it to self-assess their knowledge building. This paper elaborates upon a conceptual framework underlying the system design, describes the KCA, and reports the results of several rounds of usability testing involving teachers and students.
scmap - A tool for unsupervised projection of single cell RNA-seq data

Single-cell RNA-seq (scRNA-seq) is widely used to investigate the composition of complex tissues1–9 since the technology allows researchers to define cell-types using unsupervised clustering of the transcriptome8,10. However, due to differences in experimental methods and computational analyses, it is often challenging to directly compare the cells identified in two different experiments. Here, we present scmap (http://bioconductor.org/packages/scmap), a method for projecting cells from a scRNA-seq experiment onto the cell-types or individual cells identified in other experiments (the application can be run for free, without restrictions, from http://www.hemberg-lab.cloud/scmap).
Machine learning classifiers for critical cardiac conditions

Cardiac diseases are one of the leading causes of death in Canada. Current methods of diagnosing cardiac conditions require a manual and visual analysis of ECG and heart rate (RR interval) data. In this thesis, novel features and machine learning classifiers are developed for automating the detection of Congestive Heart Failure (CHF) and Atrial Fibrillation (AFIB). These classifiers can potentially trigger alarms when implemented in wearable devices. In the first experiment, quantitative analysis of easily measurable RR interval data is employed to detect the change in CHF severity. This experiment demonstrates that for a progressive disease such as CHF, 6 hour RR interval data can be used to classify CHF severity. It shows that the separating patients in the least severe class from more severe classes performs better than the separating all three severity classes. AFIB is one of the most frequently occurring critical event that occurs in patients with CHF. The second experiment uses novel features extracted from RR interval data, to detect AFIB within the first minute of its occurrence. This experiment evaluates feature sets engineered through different feature selection techniques. The sensitivity and specificity of the proposed classifier is 98% and 95% respectively. The third experiment aims to identify subjects at a high risk of experiencing AFIB in the future. This experiment develops novel features using RR intervals and ECG signal analysis. The results show that feature sets obtained from ECG signals can improve the classifier performance (92.4% sensitivity and 82.8% specificity). However, classifiers based on RR interval alone also show high sensitivity and specificity (81.4% and 76.9% respectively).
CONGESTION CONTROL AND PACKET REORDERING FOR MULTIPATH TRANSMISSION CONTROL PROTOCOL

Increase in number of connectivity to internet lead to the development of Multipath Transmission Control Protocol or MPTCP. MPTCP, as proposed by the IETF working group mptcp, allows a single data stream to be split across multiple path. This has obvious benefits for reliability, and it can also lead to more efficient use of networked resources. But major problem in MPTCP is the congestion control and packet reordering at the destination. Congestion control for MPTCP is given by the Wischik et al. [9]. But the packet reordering at the destination is not considering which can drastically affect the throughput for the protocol. Therefore, in this work various available packet reordering techniques available for single path TCP are tested for multipath situation. These algorithms are Duplicate Selective Acknowledgement or DSACK, Eifel and Forward Retransmission Timeout or FRTO. A simple topology is simulated in NS-3 and measurement is taken for various path characteristics to see which algorithm works best for the multipath scenario.