Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Silent Reading Performance Through Feedback on Eye Movements: A Feasibility Study

ABSTRACT This feasibility study investigated if feedback about individual eye movements, reflecting varying word processing stages, can improve reading performance. Twenty-five university students read 90 newspaper articles during 9 eye-tracking sessions. Training group participants (n = 12) were individually briefed before each session, which eye movement parameter(s) (fixation count, first fixation duration, regression, and/or skipping) to address, and informed about changes achieved in preceding sessions. Control group participants (n = 13) were told that self-instruction to read faster would produce training gains. Total fixation times decreased significantly more for training than for control group participants. Important to note, faster reading did not impair comprehension. Results are interpreted as first indications for a possible applicability of the feedback approach to silent reading. In addition to implications for future studies, alternative result interpretations (e.g., motivational effects, reduction of mindless reading) are discussed.
Improving Routing Scalability with Aggressive Route Aggregation

The size of the Boarder Gateway Protocol (BGP) routing table is continuously increasing, which incurs more memory demands in routers and increasing BGP update messages between peering routers as well. The RIB/FIB does not scale well with the Internet size, which is known as the routing scalability problem of the Internet. There are two major facts relevant to this problem: firstly more and more newly assigned IP blocks come into the routing system and in most cases are not aggregatable with the previously assigned addresses in their origin ASes; secondly, many BGP prefixes are deaggregated into fragments or overlapped with numerous trivial prefixes and these fragmental prefixes are widespread throughout the Internet without effective aggregation. In this paper we address the second point: improving the routing scalability via aggressive aggregation strategies. Our observation of the BGP routing information suggests that there exists a routing “core” of the Internet which is composed of a few “tier-1” Internet Service Providers (ISPs). Numerous “edge” autonomous systems (ASes) get transit routes to the other region of the Internet through the “core”. We propose the “core” to conduct aggressive aggregation before advertising routes to their customers. With this strategy, a considerable portion of the fragmental prefixes can be eliminated from the perspective of the “edge” ASes. Our simulation confirms that this strategy will gain admirable improvements on reducing the size of routing tables for most part of the Internet.
A Dynamic Simulation Model for the Total Packaging System Cost Analysis in an International Supply Chain

To implement a new packaging system for an international supply chain, a packaging and supply chain manager should have a good understanding of the total packaging cost concept. Especially for the reusable packaging system, a poor investment may result in enormous loss of assets and efficiency throughout the supply chain. This paper compares one-way and reusable packaging systems. For the reusable packaging system, two options, company-owned or rental, were considered. A dynamic simulation method was used for calculating the number of reusable plastic containers (totes) and total packaging cost, based on activity-based cost data provided by an automotive company. The variables considered include costs of shipping containers, distance, and transport time required for a minimum 2-year operation. Five scenarios were tested which evaluated system time and cost, resource utilization for the process and number of units processed. The greatest benefit of using the dynamic simulation is that it provides real-time status information about the packaging inventory and various cost-benefit scenarios in the target supply chain. This paper identified the cost associated with each level of various activities (e.g., cost per line item picked, cost per delivery, etc.) which enables to show a clearer picture of the true packaging and logistics costs, so any inefficiency in a supply chain due to adoption of different packaging system. The results of this simulation can help in analyzing the interactive and coherent behavior between different packaging and supply chain systems.
Stripping syntax from complexity: An information-theoretical perspective on complex systems

Claude Shannons information theory (1949) has had a revolutionary impact on communication science. A crucial property of his framework is that it decouples the meaning of a message from the mechanistic details from the actual communication process itself, which opened the way to solve long-standing communication problems. Here we argue that a similar impact could be expected by applying information theory in the context of complexity science to answer long-standing, cross-domain questions about the nature of complex systems. This happens by decoupling the domain-specific model details (e.g., neuronal networks, ecosystems, flocks of birds) from the cross-domain phenomena that characterize complex systems (e.g., criticality, robustness, tipping points). This goes beyond using information theory as a non-linear correlation measure, namely it allows describing a complex system entirely in terms of the storage, transfer, and modification of informational bits. After all, a phenomenon that does not depend on model details should best be studied in a framework that strips away all such details. We highlight the first successes of information-theoretic descriptions in the recent complexity literature, and emphasize that this type of research is still in its infancy. Finally we sketch how such an information-theoretic description may even lead to a new type of universality among complex systems, with a potentially tremendous impact. The goal of this perspective article is to motivate a paradigm shift in the young field of complexity science using a lesson learnt in communication science.
Characterizing street hierarchies through network analysis and large-scale taxi traffic flow: a case study of Wuhan, China

Hierarchy is an important property of a street network, which suggests that only a small number of streets are prominent. A previous empirical study of a European city has identified four levels of scale in a street network, namely the top 1%, top 20%, bottom 80%, and bottom 20%. This paper investigates such street hierarchies in a large Asian city, Wuhan, with a complicated network of streets. Based on network analysis, we find that street hierarchies in this case study are slightly different so that the fourth scale is adjusted from the initial 20 to 25%. The detected street hierarchies are further compared to the intensity of large-scale traffic flows at different time scales. We find that distributions of both daily and hourly traffic conform well to the street hierarchies. More specifically, the 20% of top streets accommodate about 98% of traffic flow, and the 1% of top streets account for more than 60% of traffic flow. Moreover, this finding indicates that the current street network of Wuhan needs to be improved because the top 20% of streets are rather overburdened leading to traffic congestion. Our study not only provides new quantitative evidence as to the emergence of street hierarchies but also highlights the possible traffic congestion.
Energy-efficient medium access control for transmit reference modulation

A Wireless Sensor Network (WSN) consists of sensor nodes distributed across an area to collect and communicate information. Research in the field of WSNs became interesting in recent times because of the challenges and constraints these WSNs impose, e.g., limited available energy, achieve low complexity and low cost. These research challenges and the applications of WSNs require robust communication with low power consumption in the MAC layer, as well as in the physical layer. Transmit reference (TR) modulation in the physical layer offers a simple low power receiver architecture, achieves fast synchronization with short signal acquisition time, and provides multiple frequency offsets that can be used for multiple simultaneous communications. The main contributions of this dissertation are motivated by the research question of how to design a medium access control protocol to exploit the features of the underlying transmit reference modulation to provide energy-efficiency, traffic-adaptive behavior, and robust medium access control in a shared wireless environment. We introduce a new energy-efficient MAC protocol, called TR-MAC, which exploits the benefits of the TR modulation in the underlying physical layer, and minimizes its drawbacks. The analysis of this thesis improves the understanding of the frequency offset based transmit reference modulation, and proposes a medium access control protocol customized for this unique modulation technique, named as the TR-MAC protocol. The TR-MAC protocol exploits the fast synchronization capabilities of the underlying frequency offset based transmit reference modulation. Energy- efficiency is achieved in this TR-MAC protocol by using transceiver duty cycling mechanism and preamble sampling technique. Furthermore, this TR-MAC protocol achieves traffic-adaptive behavior while maintaining energy-efficiency by using a duty cycle adaptation algorithm. The multi-channel multiple access model using frequency offsets and the performance analysis of the TR-MAC protocol in a multiple access scenario show that the TR-MAC protocol together with frequency offset based TR modulation increases the throughput and efficiency of the system while maintaining energy-efficiency. The TR-MAC protocol is suitable for low data rate and low-duty-cycle sparse WSN scenarios, for example, monitoring and tracking applications.
Interference suppression and parameter estimation in wireless communication systems over time-varing multipath fading channels

This dissertation focuses on providing solutions to two of the most important problems in wireless communication systems design, namely, 1) the interference suppression, and 2) the channel parameter estimation in wireless communication systems over time-varying multipath fading channels. We first study the interference suppression problem in various communication systems under a unified multirate transmultiplexer model. A state-space approach that achieves the optimal realizable equalization (suppression of inter-symbol interference) is proposed, where the Kalman filter is applied to obtain the minimum mean squared error estimate of the transmitted symbols. The properties of the optimal realizable equalizer are analyzed. Its relations with the conventional equalization methods are studied. We show that, although in general a Kalman filter has an infinite impulse response, the Kalman filter based decisionfeedback equalizer (Kalman DFE) is a finite length filter. We also propose a novel successive interference cancellation (SIC) scheme to suppress the inter-channel interference encountered in multi-input multi-output systems. Based on spatial filtering theory, the SIC scheme is again converted to a Kalman filtering problem. Combining the Kalman DFE and the SIC scheme in series, the resultant two-stage receiver achieves optimal realizable interference suppression. Our results are the most general ever obtained, and can be applied to any linear channels that have a state-space realization, including time-invariant, time-varying, finite impulse response, and infinite
Equitable multi objective model for public facility location using RLTP technique

In the present research, a multi-objective model is proposed, which considers equity among the citizens in addition to the cost criterion. Then, the model will be solved using Reservation Level Tchebycheff Procedure (RLTP), which is one of the interactive multi-objective decision-making techniques. Subsequently, the obtained results will be compared with those of the single-objective models to determine the effect of considering and not considering the equity criterion on public facilities location. Results of the present study show that the basic models of public facilities location do not consider the equity criterion; thus, in order to protect citizens’ rights, it is necessary for decision-makers of the urban management and planning to consider the objective of equity, along with other objectives of the project, as a multi-objective model in public facilities location problems. The proposed multi-objective model has also desirable and acceptable performance, which can be used in the public facilities location problems.
Noncomplimentary rewriting and serial-data coding scheme for shared-sense-amplifier open-bit-line DRAM

A noncomplimentary rewriting scheme is proposed for open-bit-line DRAM's adopting a shared subsense amplifier. The scheme can theoretically cancel inter-bit-line coupling noise down to zero. In order to suppress the peak in unselected word line noise, a serial-data coding scheme was also developed, This scheme can reduce unselected word-line noise by at least 50%.
Öğretim Teknolojileri Kullanımının İlkokul Öğrencilerinin Akademik Başarılarına Etkisi: Bir Meta-Analiz Çalışması

Bu arastirmada egitimde teknoloji kullaniminin ilkokul ogrencilerinin akademik basarilarina etkisini belirlemek amaciyla bir meta-analiz calismasi yapilmistir. Bunun icin Turkiye’de yapilmis calismalarla ilgili literatur taramasi yapilmistir. Arastirmaya dâhil edilecek calismalar, 2005–2013 yillari arasinda Turkiye’de “Ogretim Teknolojileri” ile ilgili yayimlanmis ve yayimlanmamis, arastirma problemine ve gerekli istatistiksel verilere sahip olan yuksek lisans ve doktora tezleri ile hakemli bilimsel dergilerde yayinlanmis makalelerden olusmaktadir. Literatur taramasi sonucunda ogretim teknolojilerinin kullaniminin ilkokul ogrencilerinin akademik basarilarina etkisine iliskin toplam 19 calisma meta-analize dâhil edilmistir. Meta-analiz sonucunda ogretim teknolojilerinin kullaniminin, ilkokul ogrencilerinin akademik basarilarina pozitif etkisi oldugu belirlenmistir. Calismalarin ortalama etki buyuklugunun, rastgele etkiler modeline gore ES=0,973 (%95 CI, SE=0,132) ile guclu duzeye cok yakin bir seviyede oldugu belirlenmistir. Calisma karakteristiklerinden dersler, uygulama suresi, calisma turu ve sinif duzeyi ile ilgili etki buyuklugu farklari belirlenmistir. Yapilan ara degisken analizleri sonucunda en yuksek etki buyuklugu degerlerinin sosyal bilgiler dersinde (ES=1,475), 20 saat ve uzeri ders saatinde (ES=1,133), doktora tezlerinde (ES=1,257) ve ikinci sinif duzeyinde (ES=1,434) gorulmustur. Elde edilen sonuclara gore uygulayici, program gelistirici ve arastirmacilara yonelik onerilerde bulunulmustur. Ogretim teknolojilerinin ilkokul programlarinda daha fazla yer verilmesi saglanabilir.
A Mathematical Model To Predict ThePerformance Of Advanced Therapies InWound Healing

Wound healing is a complex, dynamic process. The ability to simulate this process using mathematical models that incorporate quantitative data on growth factors, tissue repair cells and matrix components would be a powerful tool to predict, analyze, and optimize new therapies. We present such a mathematical framework based on a system of ordinary differential equations and wound healing parameter values from the established literature. In contrast to conventional therapy, advanced modalities can augment certain components of the healing process in a measurable fashion. The performance of specific wound therapies can be simulated and compared to other therapies. We have enhanced the model by incorporating parameters of clinical practice used in the real world setting. This approach has application to predictive performance analysis and optimization of new advanced modalities and determination of best clinical practice.
Pontifícia Universidade Católica do Rio Grande do Sul Faculdade de Informática Programa de Pós-Graduação em Ciência da Computação Linha de produtos de testes baseados em modelos

The continuing evolution of software development methodologies results in challenges emerging simultaneously with this advance. One of these challenges is how to guarantee the quality of software. Several researchers continuously develop different approaches for software testing following this evolution. One approach that aims to provide the increased quality is through model-based testing. There are various techniques of model-based software testing, ensuring a broad range of possibilities. One way to integrate these possibilities is applying the concepts of software product lines. In this work we propose the design of a software product line architecture to integrate the different techniques of model-based software testing.
A Empirical Study of Institutional Repository Service Quality and Users' Loyalty on Library- Users' Satisfaction as a Mediation

Institutional repository is an academic learning system in Taiwan. This research aims at empirical study of institutional repository service quality on users’ loyalty to college library. The outcomes of the questionnaires based on Structural Equation Modeling (SEM), and prove the hypotheses of this study. The results showed that e-service quality has the indirect positive effect through the mediating influence of users’ satisfaction on loyalty.
Pregnancy Outcomes in Women with Strictly Controlled Type 1 Diabetes Mellitus

Objective: To evaluate the pregnancy outcomes in mothers with controlled Type 1 diabetes mellitus (T1DM). Materials and Methods: Thirty seven pregnant patients with controlled T1DM were included in the study. Results: Twenty (54%) out of 37 patients had preterm delivery (<37 weeks of gestation). The type of delivery was induced vaginal delivery in 9 (24.3%) patients and cesarean section in 27 (72.9%) patients. Preeclampsia developed in 6 (16.2%) patients. Macrosomia was found in 9 (24%) patients. Two antenatal death occured. Conclusion: Even in the most favorable conditions, the pregnant patients with T1DM would have a great risk for preterm delivery and cesarean section, moderate risk for macrosomia, preeclampsia, and an undefined risk for antenatal death.
Forensic speaker profiling in a Hungarian speech corpus

Humans and also machines recognize the known persons based on their voice characteristics. If the speakers are unknown, some specific information or estimates may be still available about them: their sex, age, height, weight etc. Previous research has proven that there is a high correlation between the length of vocal tract and the speaker's physical conditions such as sex, age, height, weight etc. Results suggest that some acoustic- phonetic cues of human speech are related to body conditions. In this research we would like to examine how successfully can we predict the speaker's body conditions from their speech using machine learning techniques. We build various models to predict the speaker’s sex, age, height and weight. All of the models are trained on collected speech features including prosody, voice quality and spectra based features. The contribution of the individual features is analysed. The results show that sex, body weight and height can be used to predict speaker characteristics with very high precision, however predicting the age is a more complex task i.e. predicting the age of older speakers gets more and more difficult. These results also allow for automatic speaker profiling in cognitive infocommunication or is forensic speech research.
Word Adoption in Online Communities

In this paper, we examine the origination and dispersion of neologisms from the perspective of both communities and cognitive modeling. We use the Reddit corpus to identify words that were first used by Reddit communities from 2013 to 2014. We induce a hierarchy on Reddit based on the specificity of the topic. Generally, less specific communities have more users, while more specific communities likely feature closer social ties. We ask whether larger numbers of people or closer social ties are better environments to faster the adoption of new words. We found that the majority of new words are first adopted/created in more general communities; though this account is relativized by the size of the communities. We also examined the pace of dispersion of such words in new communities and discuss how this relates to models of memory by using an ACT-R cognitive model. We discuss some parameterizations of such a model of memory and its implications in the word adoption paradigm. Finally, we show that there is an increasing trend in the number of new words being adopted/created in Reddit communities, even during a relatively short time period.
Large Minibatch Training on Supercomputers with Improved Accuracy and Reduced Time to Train

For the past 6 years, the ILSVRC competition and the ImageNet dataset have attracted a lot of interest from the Computer Vision community, allowing for state-of-the-art accuracy to grow tremendously. This should be credited to the use of deep artificial neural network designs. As these became more complex, the storage, bandwidth, and compute requirements increased. This means that with a non-distributed approach, even when using the most high-density server available, the training process may take weeks, making it prohibitive. Furthermore, as datasets grow, the representation learning potential of deep networks grows as well by using more complex models. This synchronicity triggers a sharp increase in the computational requirements and motivates us to explore the scaling behaviour on petaflop scale supercomputers. In this paper we describe the challenges and novel solutions needed in order to train ResNet-50 in a large scale environment. We demonstrate above 90 percent scaling efficiency and a training time of 28 minutes using up to 104K x86 cores. This is supported by software tools from Intel's ecosystem. Moreover, we show that with regular 90 - 120 epoch train runs we can achieve a top-l accuracy as high as 77 percent for the unmodified ResNet-50 topology. We also introduce the novel Collapsed Ensemble technique that allows us to obtain a 77.5 percent top-l accuracy, similar to that of a ResNet-152, while training a unmodified ResNet-50 topology for the same fixed training budget.
NLOS Identification and Machine Learning Methods for Predicting the Outcome of 60GHz Ranging System

Millimeter-wave (MMW) signals in 60GHz band have shown immense potential for accurate range estimation with precise time and multipath resolution. Nonline of sight (NLOS) propagation is a primary factor affecting the range precision. To improve range estimation, an Energy detector (ED) based normalized threshold algorithm which employs a Neural network (NN) is developed on the basis of NLOS identification. The maximum curl and standard deviation of the received energy block values are used to determine NLOS environment and the normalized thresholds for different Signal-to-noise ratios (SNRs). The effects of the channel and integration period are evaluated. Performance results are presented which show that the proposed approach provides better precision and is more robust than other solutions over a wide range of SNRs for the CM1.1 and CM2.1 channel models in the IEEE 802.15. 3c standard.