Miracle-dz/UniFAR-FTUs huggingface dataset:
The three dimensions of Inclusive Design: Part three

This is the second part of a three part blog that describes a guiding framework for inclusive design in a digitally transformed and increasingly connected world. Part One can be found here. Part Three can be found here. The three dimensions of the framework are: 1. Recognize, respect, and design for human uniqueness and variability. 2. Use inclusive, open & transparent processes, and co-design with people who have a diversity of perspectives, including people that can’t use or have difficulty using the current designs. 3. Realize that you are designing in a complex adaptive system.
User interaction with word prediction: the eects of prediction quality (preprint)

Word prediction systems can reduce the number of keystrokes required to form a message in a letter-based AAC system. It has been questioned, however, whether such savings translate into an enhanced communication rate due to the additional overhead (e.g., shifting of focus and repeated scanning of a prediction list) required in using such a system. Our hypothesis is that word prediction has high potential for enhancing AAC communication rate, but the amount is dependent in a complex way on the accuracy of the predictions. Due to significant user interface variations in AAC systems and the potential bias of prior word prediction experience on existing devices, this hypothesis is difficult to verify. We present a study of two different word prediction methods compared against letter-by-letter entry at simulated AAC communication rates. We find that word prediction systems can in fact speed communication rate (an advanced system gave a 58.6% improvement), and that a more accurate word prediction system can raise communication rate higher than is explained by the additional accuracy of the system alone due to better utilization (93.6% utilization for advanced vs. 78.2% for basic).
Wave-equation traveltime-offset inversion using a bi-dimensional cross-correlation function

This dissertation addresses the problem of inverting two-dimensional seismic data to determine the compressional wave velocity as a function of the spatial position in the medium. An automatic procedure for velocity estimation is set up using a bi-dimensional cross-correlation function to compare the modelled seismograms with the data. The standard wave-equation traveltime inversion algorithm treats each recorded seismic trace independently, and ignores the offset-dependence of reflected and diffracted arrivals in an ensemble of traces in a shot gather. My new inversion method, wave-equation traveltime-offset inversion, focuses on reflected or diffracted waveforms and introduces the bi-dimensional (offset-time) cross-correlation function to tackle this offset dependence. The velocity model is updaVed using the current velocity model, the observed pressure field, and the fields computed by reverse time propagation of two pseudo-residual functions acting as sources in a particular location. The wave-equation traveltime-offset inversion reconstructs the low frequency content of the velocity model when transmitted arrivals are used. Combined with the full waveform inversion, it succeeds in inverting a synthetic fault model in the crosshole configuration. The proposed method also succeeds in inverting surface reflection datasets while the standard traveltime inversion fails. By taking into account the moveout between traces, the convergence is more stable than with the conventional method. When inverting datasets with surface reflection geometries, the dominant event and the velocity above it are recovered using the traveltime and offset information. The remaining interfaces are defined as well. However, as there is a gap in resolution between the long and short wavelengths, the blocky variations in the velocity model are not observed.
PWM controlling of a new multi DC-DC converter circuit

The design and development of DC-DC converter circuits are important for increasing and decreasing the direct current energy sources at operating the loads and systems. In this study, a multi DC-DC converter structure is described. The purpose of creating this circuit structure is to create a more effective circuit by offering a different circuit structure. For the proposed DC-DC converter, a circuit structure with five switches is created. This circuit structure is described by mathematical models according to the operation of the four parts PWMs in different time periods. After the mathematical analysis of the circuit structure, the proposed circuit and conventional circuit are operated in the Matlab Simulink. The obtained results are compared. According to the comparisons, the proposed circuit produces a higher output voltage than the traditional one and has a higher performance. Additionally, the circuit is operated for values of different loads using different switching times. Finally, voltages and currents are observed on loads.
Mixed domain vs. multi-domain statistical machine translation

Domain adaptation boosts translation quality on in-domain data, but translation quality for domain adapted systems on out-of-domain data tends to suffer. Users of web-based translation services expect high quality translation across a wide range of diverse domains, and what makes the task even more difficult is that no domain label is provided with the translation request. In this paper we present an approach to domain adaptation which results in large-scale, general purpose machine translation systems. First, we tune our translation models to multiple individual domains. Then, by means of source-side domain classification, we are able to predict the domain of individual input sentences and thereby select the appropriate domain-specific model parameters. We call this approach multi-domain translation. We develop state-of-the-art, domain-adapted translation engines for three broadly-defined domains: TED talks, Europarl, and News. Our results suggest that multi-domain translation performs better than a mixed-domain approach, which deploys a system that has been tuned on a development set composed of samples from many domains.
Simultaneous segmentation and recognition of Farsi/Latin printed texts with MLP

A new segmentation and recognition method for multi-font, multi-size Farsi/Arabic text using Multilayer feedforward neural networks is presented. The automatic feedback between segmentation and recognition completely removes or at least remarkably reduces the amount of errors due to segmentation. Furthermore, the common failures in recognizing Farsi/Arabic printed characters and in detecting some special lines are reduced. The OCR recognition method uses MLP type neural networks with Fourier descriptors.
SENTIMENTAL ANALYSIS OF WHATSAPP DATA USING DATA ANALYTICS TECHNIQUES

Data, the one, that made a trend and evolution from good old techniques to modern trendy techniques. Based on the source the data is extracted, its form differs that is in recent decades data are scalable, skeptical and diverse compared to old structured data that are derived from specific known sources.The next criterion for the technological evolution is, the storage space that is needed for data. Structured data storage lies in the database whereas for the unstructured and semi-structured ones the storage trend tips to cloud. The vital thing in addition to storage is data handling and analysis, both process when involved in trendy data results in a complexity in terms of containment, processing and visualization of data. To overcome these complexities on trendy unstructured data there emerged a concept called Big Data Analytics. It uses numerous tools and techniques that resolved the problem from data storage to visualization. One such technique is Analytical sandbox, the most central container that stores and handles data in a very appropriate manner. In addition, Big data tools provide a variety of analytical and visualization techniques that produces efficient graphical view of modern data. This paper centered on sentimental analysis of WhatsApp group data in which text mining was incorporated to the chat file and the resulted chat text file is further processed with analytical tools that analyze the chat contents and produces an graphical visualization of the sentiments shared in the group. Its outcome view lies in high echelon of positive opinions compared to other emotions such as anger, fear, disgust, anticipation, joy, sadness, surprise, trust and negative.
Efficient algorithms for speech pitch estimation

Two novel algorithms for speech pitch estimation are presented. One is based on the average magnitude difference function (AMDF), the other is based on auto-correlation pitch detection algorithms (PDA). Accurate and stable pitch estimation can be obtained by using these fast algorithms. The simulation results prove the effectiveness of these algorithms.
Mobility of queued call requests of a new call-queueing technique for cellular systems

A queueing algorithm for new call requests has been proposed to increase the system capacity of traditional fixed channel allocation (FCA) handoff channel reservation schemes. However, mobility of queued call requests was ignored in previous literature. In this paper, a detailed analysis on the effects of the mobility of queued call requests is included in the analytic model. This is important because we found that the mobiles with queued call requests are very likely to leave the cell before granted a free channel. Computer simulation is performed and the results are compared with the numerical ones. It is found that the mobility of the queued new call requests reduces the average queueing delay, but increases blocking probability generally.
Supporting joint application development (JAD) and electronic meeting systems: moving the CASE concept into new areas of software development

While CASE automates some aspects of the systems development process, it largely neglects others such as including users in the design process. One approach to user involvement is the joint application development (JAD) process, in which users, managers, and systems analysts are brought together for intensive work sessions. The paper reports on a way to support JAD with electronic meeting systems (EMS). A background on JAD and on the University of Arizona GroupSystems EMS is presented. Then an outline is given of how GroupSystems can be used in concert with the JAD approach to automate user involvement. The approach is labeled electronic JAD (E-JAD). <<ETX>>
ANALYSIS OF SOFTWARE COST ESTIMATION USING FUZZY LOGIC

The growing application of software and resource constraints in software projects development need a more accurate estimate of the cost and effort because of the importance in program planning, coordinated scheduling and resource management including the number of programming's and software design using tools and modern methods of modeling. Effectively control of investment for software development is achieved by accurate cost estimation.The accurate Software Cost Estimation (SCE) is very difficult in the early stages of software development because many of input parameters that are effective in software's effort are very vague and uncertain in the early stages. SCE that is the basis of software projects development planning is considered to be of high accuracy, because if the estimate is less than actual values, confidence factor is reduce and this is means the possibility of failure in project. Conversely, if the project is estimated at more than the actual value it would be the concept of unhelpful investment and waste of resources. In the evaluation of software projects is commonly used deterministic method. But software world is totally different from the linear variables and nowadays for performance and estimation should be used nonlinear and non-probabilistic methods. In this paper, we have studied the SCE Using Fuzzy Logic (FL) and we have compared it with COCOMO model. Results of investigations show that FL is a performance model for SCE.
A STUDY ON THE EVALUATION OF UNIT TESTING FOR ANDROID SYSTEMS

Unit testing is a method for quickly assessing the building blocks of a program and for obtaining accurate error localizations. However, in order to achieve these qualities, the tests cases need to be isolated, since an external call may imply a connection to a remote database. This requirement also makes unit testing difficult to initiate for classes with outside dependencies, and consequently several approaches have been devised to facilitate unit testing of these methods. This paper focuses on the different ways of unit testing Java methods with external dependencies in an Android application. Additionally, it covers a new category of testing methodology called shadow objects. First, the study examines some of the current methods of testing. Then, it details the different ways a class with an external dependency could be unit tested. Finally, the paper presents a discussion and evaluation of the study.
Reliable CFD-based estimation of flow rate in hemodynamics measures. Part II: Sensitivity analysis and first clinical application

In Ponzini et al. (2006) a new approach has been proposed for estimating in a reliable way blood flow rate from velocity Doppler measurements. In that paper, basic features of the approach and some “in silico” test cases were furnished. Here, we give more insights of this approach by performing a sensitivity analysis of the formulae relating blood flow rate to blood velocity. In particular we analyze their sensitivity to the physiological parameters in comparison with the standard formula proposed in Doucette et al. (1992). A first glance at “in vivo” validation of the formulae is given too.
Distributed control architecture for intelligent systems

In contrast to a hierarchical and centralized structure, distributed or decentralized control architectures reveal their main advantages when it is necessary to enhance the system, to integrate components, and to maintain the system. The main disadvantage of not centralized architectures is having to make sure that the system will fulfill an overall or global goal. To investigate these problems, a distributed control architecture for intelligent systems was developed at the University of Karlsruhe. In this paper, the methods for dead-lock-free coordination and cooperation are explained.
Improving search through Event-based Biomedical Text Mining

there has been a major focus on event extraction for biomedical applications. In this paper, we focus on search, highlight some of the drawbacks of popular search methods, and show how event extraction and associated technologies, e.g., named entity recognition, can help to improve the efficiency of search. We also explore how event extraction can be enhanced through a new type of annotation, i.e. meta-knowledge annotation, which can facilitate the extraction of high-level information relating to the intended interpretation of events, e.g. whether they represent a hypothesis, a claim, a belief, an opinion, a well established fact, a tentative or more confident analysis of experimental results, etc.
Selective Efficient Quantum Process Tomography

We present a new method for quantum process tomography. The method enables us to efficiently estimate, with fixed precision, any of the parameters characterizing a quantum channel. It is selective since one can choose to estimate the value of any specific set of matrix elements of the super-operator describing the channel. Also, we show how to efficiently estimate all the average survival probabilities associated with the channel (i.e., all the diagonal elements of its χ–matrix).
Enhanced Elliptic Curve Cryptography

Background/Objectives: Today’s Technological world Information Security is an essential for commercial and legal trading, secrecy, truthfulness and non-reputability. The Elliptic Curve Cryptography (ECC) has become one of the latest trends in the field of Public-Key Cryptography (PKC). ECC promises a faster, efficient and more secured. In this paper, the Standard ECC and proposed Improved ECC (IECC) are compared. Methods/Statistical Analysis: The proposed IECC algorithm is designed to be more challenging as the repetitive characters of the text are replaced with the different cipher text in each of the iteration and outperforms the standard ECC in terms of cipher text, encryption, decryption time and security. This algorithm helps to assure end to end encryption for Online Social Network (OSN) users. Findings: The statistical analysis approach reveals a significant feature that the cipher text of IECC does not correlated with the plain text. This approach is improved ECC reduces more security than the Standard ECC. The proposed method is concluded that implemented IECC is better than standard ECC. Applications/Improvements: Except the proposed algorithm used for this research, the possibility of using other algorithms are implemented in future work.
Cortical processing of human and emoji faces: an ERP analysis

ABSTRACT Social networks have become an effective tool of interaction, frequently replacing face-to-face communication by using non-verbal emotional cues, such as emojis. The aim of the present study was to investigate whether human and emoji faces are analogously processed cortically. We recorded P100, N170, and LPP event-related potentials (ERPs) in response to happy, neutral, and angry expressions of human and emoji faces in 30 participants. The results showed that P100 and LPP amplitudes were larger in response to human faces but emoji faces generated larger N170 amplitude. Angry faces elicited significantly larger P100 and LPP amplitudes. The neural time-course of processing human and emoji faces was similar, however, human faces generate greater attentional orientation response, emoji faces increase the structural encoding processes, and human faces elicited greater arousal and attentional engagement. These results suggest that the use of emoji faces in computer-mediated communication produces neural responses that are similar to those that are observed in face-to-face communication.
Automated Answering for Subjective Examination

Online courses are getting popular among students. Trends of objective examination for such courses are already available but many courses require assessment in traditional way so that the subject understanding of the candidate can be evaluated which requires subjective assessment i.e. descriptive based examination. Thus in our paper we are focusing on the inference process required for development of such type of systems. Our system is able to assess one word and one sentence based answer with more than 80% of efficiency. While answering single sentence answers paraphrasing is consider for assessing the variations occurring due to the use of vocabulary.
Duality of Link Prediction and Entailment Graph Induction

Link prediction and entailment graph induction are often treated as different problems. In this paper, we show that these two problems are actually complementary. We train a link prediction model on a knowledge graph of assertions extracted from raw text. We propose an entailment score that exploits the new facts discovered by the link prediction model, and then form entailment graphs between relations. We further use the learned entailments to predict improved link prediction scores. Our results show that the two tasks can benefit from each other. The new entailment score outperforms prior state-of-the-art results on a standard entialment dataset and the new link prediction scores show improvements over the raw link prediction scores.
Face Recognition Using 2D and 3D Facial Data

Results are presented for the largest experimental study to date that investigates the comparison and combination of 2D and 3D face recognition. To our knowledge, this is also the only such study to incorporate signicant time lapse between gallery and probe image acquisition, and to look at the effect of depth resolution. Recognition results are obtained in (1) single gallery and a single probe study, and (2) a single gallery and multiple probe study. A total of 275 subjects participated in one or more data acquisition sessions. Results are presented for gallery and probe datasets of 200 subjects imaged in both 2D and 3D, with one to thirteen weeks time lapse between gallery and probe images of a given subject yielding 951 pairs of 2D and 3D images. Using a PCA-based approach tuned separately for 2D and for 3D, we nd that 3D outperforms 2D. However, we also nd a multi-modal rank-one recognition rate of 98.5% in a single probe study and 98.8% in multi-probe study, which is statistically signicantly greater than either 2D or 3D alone.
Review: Quick-Start for TCP and IP (JFAS05)

This review thoroughly analyses draft 01 of the Quick-Start proposal, focusing mostly on security issues. It is argued that the recent new QS nonce proposal gives insucient protection against misbehaving receivers, and a new approach is suggested. But it would be perverse to strengthen protection against malicious receivers too much when the protocol only works if all senders can be trusted to comply. The review argues this is an inevitable result of choosing to have routers allocate rate to senders without keeping per-flow state. The paper also questions whether Quick-Start’s under-utilisation assumption defines a distinct range of operation where fairness can be ignored. Because trac variance will always blur the boundary, we argue that under-utilisation should be treated as the extreme of a spectrum where fairness is always an issue to some extent. If we are to avoid per-flow state on routers, the review points to an alternative direction where endpoints allocate rate to themselves. Counter-intuitively, this allows scalable security and a spectrum of fairness to be built in from the start, but rate allocation is less deterministic. Issues not related to security are also raised, including the possibility of a catastrophic overload if path delays are atypical. A solution to this is oered, as well as solutions to scalability issues with the range and precision of the Rate Request field. Many other more minor review comments are given.
Research on the Cross-Coupling of a Two Axes Gimbal System with Dynamic Unbalance

The aim of the gimballed stabilization system is to stabilize the sensor's line of sight towards a target by isolating the sensor from the disturbance induced by the operating environment, such as various disturbance torques and body motions. This paper presents a two axes gimbal assembly. The torque relationships are derived considering the angular motion of the base body and the dynamic unbalance. The stabilization loops for the two axes gimbal system are constructed and related to each other with a cross-coupling unit. Next, the overall model is simulated using two approaches and the obtained results are compared to show the correction of the model proposed. Finally, numerous tests are applied to evaluate the model's performance and investigate the effects of torque disturbance considered in this research.