Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Soft-Switching Bidirectional DC–DC Converter With Coupled Inductors

This paper presents a novel topology for a nonisolated bidirectional dc-dc converter with soft-switching capabilities, which usually operates at a zero-voltage-switching (ZVS) condition. A nonisolated dc-dc converter combines a buck converter and a backward boost converter into one circuit, which consists of a half-bridge power switch, an inductor, and capacitors. In order to realize ZVS conditions, the proposed converter utilizes a coupled inductor, a small independent inductor, and auxiliary switches and diodes. Due to ZVS, switching stress on switch components is reduced, and the reverse recovery problem of MOSFET antiparallel body diodes is also eliminated. Moreover, the operating modes of the proposed converter can be switched between a ZVS mode and a conventional hard-switching mode on the basis of load conditions. The soft-switching mode is for heavy loads, and the hard-switching mode is for light-load conditions. Therefore, the highest efficiency can be obtained at almost all load ranges. The detailed theoretical analyses in each mode are presented, and a 1-kW prototype is also built to verify the principle of the circuit and the theoretical analysis.
Defect association and complexity prediction by mining association and clustering rules

Number of defects remaining in a system provides an insight into the quality of the system. Software defect prediction focuses on classifying the modules of a system into fault prone and non-fault prone modules. This paper focuses on predicting the fault prone modules as well as identifying the types of defects that occur in the fault prone modules. Software defect prediction is combined with association rule mining to determine the associations that occur among the detected defects and the effort required for isolating and correcting these defects. Clustering rules are used to classify the defects into groups indicating their complexity: SIMPLE, MODERATE and COMPLEX. Moreover the defects are used to predict the effect on the project schedules and the nature of risk concerning the completion of such projects.
Soft input channel estimation for turbo equalization

In this paper, we consider soft decision directed channel estimation for turbo equalization. To take advantage of soft information provided by the decoder, a minimum mean square error linear channel estimator is derived under an uncorrelated channel tap model, and a soft input recursive least squares algorithm is also developed by modifying the cost function of the conventional recursive least squares algorithm. The performance of the proposed channel estimators are analyzed in terms of mean square identification error (MSIE) for stationary channels. Simulation results for both time-invariant and time-varying frequency-selective Rayleigh fading channels are also presented.
NIMBLER : A Model of Visual Attention and Object Recognition With a Biologically Plausible Retina

NIMBLE is a cognitively plausible object recognition system that uses a saccadic visual memory to store and retrieve image fragments. These fragments are acquired by scanning an image in a human-like way using a bottom up saliency model to find informative regions, applying a kernel density function to the fragment to determine its familiarity, and then combining the fragments using naïve Bayes. Although it has performed well on the data sets it has been evaluated on, there are numerous extensions that can be made to NIMBLE to improve its biological plausibility and performance. In this work, we incorporate a more realistic retinal representation into NIMBLE. The enhanced architecture, NIMBLER, is evaluated on the COIL-20, COIL-100, and AR image databases.
Why Teach PE? Factors that Affect Students' Decisions to Teach Physical Education Revisited

Many times a child wi ll be asked, "What do you want to be when you grow up? " The answers are va ri ed. yet their responses usually refl ect what their parents employ may be. For this study, factors were investi gated that have an effect on coll ege student 's decision to become a physical education. For thi s study it was fo und that fo rmer physical education and coaches were the most influential people affecting college student's decision to become physical educati on teachers, not parents. It was also found that many of these coll ege sllldent's were actively involved in high school athletics , thus also affect ing thei r decision lo become a physical education teacher. The results from th is study can serve PETE fac ulty to capitalize on their PETE student 's excitement lo teach physica l education.
Turkish Mentors' Perception of Roles, Competencies and Resources for Online Teaching

Developments in computer-mediated communications are not only providing new opportunities for educators but also changing roles and competencies in learning and teaching environments. Experts agree that teaching online requires different roles and competencies. The literature includes several studies on roles and competencies for online teaching. However, as Le Boterf underlines, roles and competencies largely depend on context. This survey study intends to identify roles, competencies and resources for online teaching in Turkey by asking online mentors of Anadolu University what they think about the roles they should perform and the competencies and resources they should possess in order to teach online successfully. Results have shown that the participant Turkish online mentors agree on the significance of the assessor, the content expert and process facilitator roles; on the other hand, they indicate lower level of necessity for the material producer and the administrator roles. Results have also revealed lack of design competencies among online mentors. Overall, the study has supported Le Boterf’s claim about importance of context on identification of roles and competencies.
Robustness of circadian rhythms with respect to molecular noise

We use a core molecular model capable of generating circadian rhythms to assess the robustness of circadian oscillations with respect to molecular noise. The model is based on the negative feedback exerted by a regulatory protein on the expression of its gene. Such a negative regulatory mechanism underlies circadian oscillations of the PER protein in Drosophila and of the FRQ protein in Neurospora. The model incorporates gene transcription into mRNA, translation of mRNA into protein, reversible phosphorylation leading to degradation of the regulatory protein, transport of the latter into the nucleus, and repression of gene expression by the nuclear form of the protein. To assess the effect of molecular noise, we perform stochastic simulations after decomposing the deterministic model into elementary reaction steps. The oscillations predicted by the stochastic simulations agree with those obtained with the deterministic version of the model. We show that robust circadian oscillations can occur already with a limited number of mRNA and protein molecules, in the range of tens and hundreds, respectively. Entrainment by light/dark cycles and cooperativity in repression enhance the robustness of circadian oscillations with respect to molecular noise.
Exploring Factors Affecting Post-Divorce Adjustment in Iranian Women: A Qualitative Study.

Background : Divorce is a complex, multidimensional concept and its direct and indirect impacts affects thousands of people in Iran each year. However, the concept of post-divorce adjustment in Iranian women has not been studied in detail. The aim of the present qualitative study was to determine the factors contributing to post-divorce adjustment in divorced women. Methods: A qualitative research was carried out using grounded theory approach, followed by three phases of open coding, axial coding, and selective coding. The participants consisted of 21 divorced women who were selected using purposive sampling method. Semi-structured interviews were conducted and then interviews were recorded and transcribed for further analysis. Results: A total of 21 divorced women participated in the current study. The majority of the participants were between 20-30 years old; they were between 17 to 30 years when they married. Also, most of the participants had bachelor’s degree (11) and most of them had a job (16). In the primary data coding, 35 open concepts were extracted. These concepts were then reduced into 32 secondary concepts. At the final stage, 6 main categories contributing to post-divorce adjustment were extracted including: (a) demographics, (b) interpersonal, (c) attitudinal, (d) relational, (e) supportive, and (f) coping strategies. Conclusion: The present study emphasizes the value of lived experiences of divorced women. Based on the findings of our study, it is important to develop a solid support network and provide interventions targeting the quality of life in divorced women.
Interoperable IPv6 Sensor Networking over PLC and RF Media

The evolution of technology has made the connection of all types of devices to IP networks possible. In this paper, the authors investigate the possible usage of IPv6 in sensor networks connected through the Power Line Communication PLC non-wireless medium and demonstrate possible interoperability. This work is based on the adaptation of the IEEE 802.15. 4 standard protocol constrained by the low-power, lossy and low data-rate context of PLC transceiver that uses pulse modulation. The aim is to provide interoperability features with other media using a robust and reliable communication stack. The target application of such results ranges from smart metering and environment monitoring to home control and urban area energy efficiency applications. This paper proposes the first adaptation of the IEEE 802.15. 4 standard commons for the PLC medium. Following this standard interface, the authors demonstrate data communication on PLC with low power energy requirement using the pulse PLC physical layer. This paper also presents an initial implementation of the Routing Protocol for Low power and lossy networks RPL setup proposed by the IETF working group. In this context, the authors demonstrate interoperability in a testbed between PLC and Wireless Sensor Networks WSN.
Simulation of a Cost Model Response Requests for Replication in Data Grid Environment

Data grid is a technology that has full emergence of new challenges, such as the heterogeneity and availability of various resources and geographically distributed, fast data access, minimizing latency and fault tolerance. Researchers interested in this technology address the problems of the various systems related to the industry such as task scheduling, load balancing and replication. The latter is an effective solution to achieve good performance in terms of data access and grid resources and better availability of data cost. In a system with duplication , a coherence protocol is used to impose some degree of synchronization between the various copies and impose some order on updates. In this project, we present an approach for placing replicas to minimize the cost of response of requests to read or write, and we implement our model in a simulation environment. The placement techniques are based on a cost model which depends on several factors, such as bandwidth, data size and storage nodes.
On the role of distributed computing in Symbolic Computation for Algebraic Topology ∗

In this work, we report on the preliminary analysis carried out in order to undertake the task of designing and building distributed systems for Symbolic Computation in Algebraic Topology. We try to make explicit how the peculiarities of the programs computing homology and homotopy groups can influence on the development of distributed systems to perform the same calculations. We stress not only on the (well-known) benefits of distributed computing, but also in the challenges and difficulties that appear due to the distinctive characteristics of our domain of computation.
A new secure routing protocol to defend Byzantine attacks for ad hoc networks

To secure ad hoc networks, a particularly challenging problem is how to feasibly detect and defend the internal attacks against the routing protocols, such as Byzantine behaviors. In this paper, we develop: (1) an efficient distributed key management scheme that a source node can authenticate its neighbors and establish a session key on-demand; (2) a novel detection algorithm that can detect the internal attacks, such as Byzantine attacks, by using both message and route redundancy; (3) a new secure routing protocol (SRP), behavior-based secure routing (BBSR), in which a node selects its best route based on its accumulated trust on the nodes along the candidate routes; (4) a cost function that directly measures the cost of the increased trustworthiness and its impact on network performance. The simulation results have demonstrated the effectiveness of the proposed key management scheme, attack detection algorithm, and routing protocol.
Towards anticipatory service composition in Ambient Intelligence

Anticipatory cognitive mechanisms have been investigated so far in gaze control or in simple robot navigation. This is in order to build cognitive systems endowed with the ability to predict the outcome of their actions. However, research on the actual benefit of anticipatory behavior in Ambient Intelligence (AmI) for user assistance is still in its infancy. This paper proposes some use cases to illustrate the benefits of anticipatory service composition in AmI, highlights issues resulting from the incorporation of anticipation into ubiquitous environments, comes up with guideline principles and existing approaches that have shown promising results to address the identified challenges, and emphasizes the questions and issues that still need a suitable research program before they can be addressed.
Use of multilocus variable number of tandem repeats analysis genotyping to determine the role of asymptomatic carriers in Clostridium difficile transmission.

BACKGROUND Previous studies have suggested that asymptomatic carriers of toxigenic Clostridium difficile are a source of hospital-associated (HA) infections. Multilocus variable number of tandem repeats analysis (MLVA) is a highly discriminatory molecular subtyping tool that helps to determine possible transmission sources. METHODS Clostridium difficile isolates were recovered from perirectal swabs collected for vancomycin-resistant Enterococcus (VRE) surveillance as well as from clinical C. difficile toxin-positive stool samples from July to November 2009 at the University of Pittsburgh Medical Center Presbyterian (UPMC). MLVA was performed to determine the genetic relationships between isolates from asymptomatic carriers and patients with HA C. difficile infection (HA-CDI). Asymptomatic carriage and HA-CDI isolates were considered to be associated if the carriage isolate was collected before the HA-CDI isolate and if the MLVA genotypes had a summed tandem-repeat difference of ≤ 2. RESULTS Of 3006 patients screened, 314 (10.4%) were positive for toxigenic C. difficile, of whom 226 (7.5%) were detected only by VRE surveillance cultures. Of 56 incident cases of CDI classified as HA at UPMC during the study with available isolates, 17 (30%) cases were associated with CDI patients, whereas 16 (29%) cases were associated with carriers. Transmission events from prior bed occupants with CDI (n = 2) or carriers (n = 2) were identified in 4 of 56 cases. CONCLUSIONS In our hospital with an established infection control program designed to contain transmission from symptomatic CDI patients, asymptomatic carriers appear to have played an important role in transmission. Identification and isolation of carriers may be necessary to further reduce transmission of C. difficile in such settings.
Estimating Effort in Global Software Development Projects Using Machine Learning Techniques

Effort estimation is crucial for the control, quality and success of any software development project and it become even more crucial in GSD where stakeholders are from different background and interest and there is a huge cultural, linguistic and temporal difference involved between them. Software Effort estimation techniques fall under the categories of Expert judgment, Algorithmic estimation and Machine Learning. In this study a comparative analysis is made between traditional effort estimation techniques and ML techniques. Results show us that ML methods give us more accurate effort estimation as compared to the traditional methods of effort estimation. Moreover the comparisons of different ML techniques are done in this paper to study that which ML method is more suitable in which situation.
NEUROSCIENCE FOREFRONT REVIEW AUDITORY CORTEX INVOLVEMENT IN EMOTIONAL LEARNING AND MEMORY

Emotional memories represent the core of human and animal life and drive future choices and behaviors. Early research involving brain lesion studies in animals lead to the idea that the auditory cortex participates in emotional learning by processing the sensory features of auditory stimuli pairedwith emotional consequences andby transmitting this information to theamygdala.Nevertheless, electrophysiological and imaging studies revealed that, following emotional experiences, the auditory cortex undergoes learninginduced changes that are highly specific, associative and long lasting. These studies suggested that the role played by the auditory cortex goes beyond stimulus elaboration and transmission. Here, we discuss threemajor perspectives created by these data. In particular, we analyze the possible roles of the auditory cortex in emotional learning,we examine the recruitment of the auditory cortex during early and late memory trace encoding, and finally we consider the functional interplay between the auditory cortex and subcortical nuclei, such as the amygdala, that process affective information. We conclude that, starting from the early phase of memory encoding, the auditory cortex has a more prominent role in emotional learning, through its connections with subcortical nuclei, than is typically acknowledged. 2015 IBRO. Published by Elsevier Ltd. All rights reserved.
The onset of X-ray emission in young stellar objects - A Chandra observation of the Serpens star-forming region

Aims. To study the properties of X-ray emission from young stellar objects (YSOs) through their evolution from Class I to Class III and determine whether Class 0 protostars emit X-rays. Methods. A deep Chandra X-ray observation of the Serpens star-forming region was obtained. The Serpens Cloud Core is ideally suited for this type of investigation, being populated by a d ense and extremely young cluster whose members are found in all evolutionary stages, including six well-studied Class 0 sources . Results. None of the six Class 0 protostars is detected in our observations, excluding the presence of sources with typical X-ray luminosities> 0.4× 10 30 erg s −1 (for column densities of the order of 4×10 23 cm −2 , or AV∼ 200). A total of 85 X-ray sources are detected and the light curves and spectra of 35 YSOs are derived. There is a clear trend of decreasing absorbing column densities as one moves from Class I to Class III sources, and some evidence of decreasing plasma temperatures, too. We observe a strong, long-duration, flare from a Class II low-mass star, for which we derive a flaring loo p length of the order of 20 stellar radii. We interpret the flar ing event as originating from a magnetic flux tube connecting the star t o its circumstellar disk. The presence of such a disk is supported by the detection, in the spectrum of this star, of 6.4 keV Fe fluoresc ent emission.
On the role of gamification and localization in an open online learning environment: javala experiences

Massive Open Online Courses (MOOCs) have rapidly become an important tool for educational institutes in teaching programming. Nevertheless, high drop-out rates have always been a problem in online learning. As MOOCs have become an important part of modern education, reducing the drop-out rate has become a more and more relevant research problem. This work studies a nine-year-long period of maintaining an open, online learning environment of programming. The aim is to find out how the implementation of the learning environment could engage the students to learning and this way affect the drop-out rate. We provide an insight to experiences stemming from nine years of data collected with Javala, an online system created to help shifting from C++ to Java programming. The paper also discusses two key properties of Javala, gamification, and localization, together with data to assess their significance.
Bi-channel sensor fusion for automatic sign language recognition

In this paper, we investigate the mutual-complementary functionality of accelerometer (ACC) and electromyogram (EMG) for recognizing seven word-level sign vocabularies in German sign language (GSL). Results are discussed for the single channels and for feature-level fusion for the bichannel sensor data. For the subject-dependent condition, this fusion method proves to be effective. Most relevant features for all subjects are extracted and their universal effectiveness is proven with a high average accuracy for the single subjects. Additionally, results are given for the subject-independent condition, where subjective differences do not allow for high recognition rates. Finally we discuss a problem of feature-level fusion caused by high disparity between accuracies of each single channel classification.
Side channel analysis on android smartphones

In recent years, smartphones have become inseparable components of people's daily life. However, the great popularity of smartphones causes some security problems. For example, users may store their contact lists, passwords and other credentials in their smartphones. In addition to various features, smartphones also have various motion sensors like accelerometer and gyroscope. Therefore, number of malwares focused on smartphones goes up while capabilities of smartphones increase. It is well-known fact that Android is the leader of smartphone market. This unluckily leads attackers to the Android platform. Furthermore, attackers use motion sensors as a side-channel information to obtain user's private data. There are several studies in the literature which show how motion sensors can be used as a side-channel. In this study, the main object is to determine user's age interval by using accelerometer sensor as a side-channel. We show that by analyzing user's tap event on the touchscreen we can determine whether the user is child or adult. This is actually our great contribution to the literature because this information may give attackers extra avenues for their malicious activities.
İnsan Yüzlerinde 2B Nirengi Noktalarının Otomatik Saptanması∗ 2D Automatic Face Landmarking

Accurate detection of landmark points plays an important role in many applications, such as face verification, face tracking, face expression analysis, 3D face modelling, etc. There are a lot of approaches proposed for this problem in the literature. These methods are generally based on two types of information: local texture around a given feature and geometric configuration of a given set of facial features or combination of two types of information. In this work, we investigate the performance of four transformation techniques: Gabor Wavelets, Independent Component Analysis (ICA), Non-negative Matrix Factorization (NMF), Discrete Cosine Transform (DCT). Since these methods are based on the texture information and aim to model the facial features in a suitable subspace, they are called ”Appearancebased Methods”. We also present some experimental results of proposed methods in conjunction with structural information.