Miracle-dz/UniFAR-FTUs huggingface dataset:
Wavelet-based voice morphing

This paper presents a new multi-scale voice morphing algorithm. This algorithm enables a user to transform one person's speech pattern into another person's pattern with distinct characteristics, giving it a new identity, while preserving the original content. The voice morphing algorithm performs the morphing at different subbands by using the theory of wavelets and models the spectral conversion using the theory of Radial Basis Function Neural Networks. The results obtained on the TIMIT speech database demonstrate effective transformation of the speaker identity.
Farsi/Arabic text extraction from video images by corner detection

Video text information plays an important role in semantic-based video analysis, indexing and retrieval. In this paper, we proposed a novel Farsi text detection approach based on intrinsic characteristics of Farsi text lines, which is more robust to complex backgrounds and various font styles. First, by an edge detector operator, all the possible edges in vertical, horizontal, 45 and 135 degrees are extracted. Then, for extracting text strokes, some pre-processing such as dilation and erosion are done according to the font size. Afterward, by finding the edges cross points, corners map is extracted. To discard non-text corners and finding real font size, histogram analysis is done. After finding real font size, input image is rescaled and a new corner map is extracted. Finally, the detected candidate text areas undergo the empirical rules analysis to identify text areas and project profile analysis for verification and text lines extraction. Experimental results demonstrate that the proposed method is robust to font size, font colour, and background complexity.
VSFS: A Versatile Searchable File System for HPC Analytics

Emerging HPC analytics applications urgently demand filesearch services to drastically reduce the scale of the input data in real-time, so that the speed of computation and data analytics can be greatly accelerated. Unfortunately, the existing file-search solutions are either poorly scalable for large-scale systems, or lack a well-integrated interface to allow applications to easily use them for critical tasks. We believe that the time is ripe for the design of a searchable file system capable of accurate and scalable system-level filesearch functionality. In this paper, we propose a Versatile Searchable File System, VSFS, which provides a transparent, accurate and real-time file-search service through a POSIX-compatible file system namespace that can be integrated into any HPC/Big Data legacy code without modifications. Additionally, to support real-time file search, VSFS uses a DRAM-based distributed architecture to perform real-time file indexing. Moreover, a versatile index scheme is designed to adapt to the various forms of HPC datasets. The results of our VSFS prototype evaluation show that VSFS is scalable in a typical HPC environment. It achieves significantly better file-indexing and file-search performance than the popular SQL/NoSQL solutions, while it only introduces negligible I/O overhead. Finally, we integrate VSFS to a scientific analytics application to show its benefits in terms of performance and ease of use.
Simplifying Buffer Overflow Detection Using Site-Safe Expressions

We present a highly automated technique to identify buffer overflows in C source code, and implement the approach in our prototype cboc. It is a sound tool, and of particular significance is its ability to easily deal with pointer expressions and dynamic memory allocations, which are integral parts of the buffer overflow problem. Our implementation hinges on a key design consideration: introducing the notion of site-safe expression allows us to manage pointer dereference expediently, and the expense is that it may yield some false alarms. Fortunately, only a small number of false alarms are reported, and all probable false alarms belong to a special alarm type non-site-safe. Experiments show that cboc is competitive with state-of-the-art model checker CBMC.
Mental Health in Multiple Sclerosis Patients without Limitation of Physical Function: The Role of Physical Activity

Multiple sclerosis (MS) patients, in general, show reduced physical function, physical activity, and quality of life. Positive associations between physical activity and quality of life have been reported. In particular, we were interested in the relation between physical activity and mental health in MS patients without limitation of physical function, since limitations of physical function may influence both physical activity and quality of life. Assessment comprised the Baecke questionnaire on physical activity, the Short Form 36 Health Survey (SF-36), and Beck Depression Inventory (BDI). We ranked our sample according to physical activity into four groups and performed an ANOVA to analyze the relationship between levels of physical activity and health-related quality of life (HRQoL). Then we performed a subgroup analysis and included patients with unlimited walking distance and a score of less than 18 in the BDI. Most active vs. inactive patients were compared for the mental subscales of the SF-36 and depression scores. From 632 patients, 265 met inclusion criteria and hence quartiles were filled with 67 patients each. Active and inactive patients did not differ considerably in physical function. In contrast, mental subscales of the SF-36 were higher in active patients. Remarkable and significant differences were found regarding vitality, general health perception, social functioning and mental health, all in favor of physically active patients. Our study showed that higher physical activity is still associated with higher mental health scores even if limitations of physical function are accounted for. Therefore, we believe that physical activity and exercise have considerable health benefits for MS patients.
A Novel 180$^{\circ}$ Hybrid Using Broadside-Coupled Asymmetric Coplanar Striplines

In this paper, a new way to realize a 180deg hybrid is presented. This technique utilizes a broadside-coupled asymmetric coplanar-stripline section to meet the tight coupling requirement that usually arises from the traditional reduced-size hybrid-ring configuration. In addition, this coplanar technique facilitates the implementation of a hybrid ring in a cascadable format. While providing a simple design procedure for the device, analytical details are also discussed. An experimental prototype, operating at 2.4 GHz, has been fabricated using conventional printed circuit board technology. Measured performances show good agreement with analytical and full-wave simulations, showing promising potential for a variety of applications such as balanced mixers, power amplifiers, and antenna feed networks.
Automatic Tracking and the Analysis of Human Movement

Tracking player performance in team sports is difficult as games involve quick, agile movements, with many unpredictable changes in direction and frequent collisions between players. Previous approaches have partially solved the motion analysis problem by manually tracking player movements, using observational sheets or computerised digitising pads and rods. However, manual tracking can be a subjective and laborious process which has arguably discouraged researchers from conducting more detailed analyses of multiple player interactions within games. The aim of this investigation is to establish whether an automated, colour- recognition, motion detection system (A-Eye) is suitable as a tool for the analysis of multiple players in a sporting environment. Reliability tests show strong intra-operator reliability scores (2% TEM) and correlations. Validity tests comparing manual and automatic tracking methods at court boundaries during short game sequences demonstrate moderate to strong correlations between the methods in most areas of the court. A comparison of time spent in each zone of the court also largely shows similarities between analysis methods (0.09%-2.53%). This automated player tracking system provides a detailed multi-disciplinary analysis and has practical benefits for coaches, practitioners and researchers by enhancing understandings of sports performance and team work.
Specific vehicle detection and tracking in road environment

In this paper, we propose a real-time method to detect and track specific vehicles, toward monitoring the abnormal activities in the traffic environment. Firstly, a novel background subtraction approach is used to get the accurate foreground segmentations and shadow suppression. Then a HIK (Histogram Intersection Kernel) based SVM classifier is trained to recognize whether a vehicle is suspicious. Finally, the Camshift based tracking is used to fast track the specific vehicles. Experiments in a real traffic scenario show the promise of the proposed approach.
Automated red lesion detection in diabetic retinopathy

Diabetic retinopathy is damage to the retina of human eye which is caused by the complication of increase in blood glucose level which can eventually leads to blindness. The longer the patient has diabetes the higher the chance of developing diabetic retinopathy. DR is the deterioration of retinal blood vessel. Microaneurysm is one of the earliest symptoms of Diabetic Retinopathy. Microaneurysms occur as isolated dark red spots in retina due to the swelling of capillaries and weaking of blood vessels. The number of microaneurysms is used to indicate the severity of the disease. Earlier microaneurysms detection can reduce the incidence of blindness. Here the proposal is about an automated system for diabetic retinopathy detection in color fundus images obtained by fundus camera.
Inferring High Quality Co-Travel Networks

Social networks provide a new perspective for enterprises to better understand their customers and have attracted substantial attention in industry. However, inferring high quality customer social networks is a great challenge while there are no explicit customer relations in many traditional OLTP environments. In this paper, we study this issue in the field of passenger transport and introduce a new member to the family of social networks, which is named Co-Travel Networks, consisting of passengers connected by their co-travel behaviors. We propose a novel method to infer high quality co-travel networks of civil aviation passengers from their co-booking behaviors derived from the PNRs (Passenger Naming Records). In our method, to accurately evaluate the strength of ties, we present a measure of Co-Journey Times to count the co-travel times of complete journeys between passengers. We infer a high quality co-travel network based on a large encrypted PNR dataset and conduct a series of network analyses on it. The experimental results show the effectiveness of our inferring method, as well as some special characteristics of co-travel networks, such as the sparsity and high aggregation, compared with other kinds of social networks. It can be expected that such co-travel networks will greatly help the industry to better understand their passengers so as to improve their services. More importantly, we contribute a special kind of social networks with high strength of ties generated from very close and high cost travel behaviors, for further scientific researches on human travel behaviors, group travel patterns, high-end travel market evolution, etc., from the perspective of social networks.
Prediction of Performance Failures in Video-Streaming Servers

Continuity is a critical aspect of video-streaming services due to large user abandonment costs resulting from interruptions in the middle of video playback. Server performance problems in particular are in the origin of soft failures manifested as degradation of video quality, which can have the same impact on viewer experience as hard failures (e.g., abrupt connection termination). Predicting both failure types is essential to avoid their propagation to end-users by means of proactive repairs. This paper addresses the problem of predicting and diagnosing performance problems in streaming servers in terms of its main cause (client-workload overloading and performance anomaly) for proactive repair, server capacity planning and fault repair. Evaluation of the approach using several machine learning algorithms showed that (1) Bayesian Networks predicted 93% of failures, (2) prediction performance is worse for performance anomalies than for client-workload overloading, (3) diagnosis correctness for predicted failures is 100% for client-workload overloading failures and approximately 98% for performance anomalies.
A Classification Framework for Product Design Optimization

Research on design optimization has developed and demonstrated a variety of modeling techniques and solution methods, including techniques for multidisciplinary design optimization, and these approaches are beginning to migrate into product development practice. Software tools are appearing to assist with the optimization task. However, the complexity of the optimization problems being considered continues to increase because changing business strategies stress the importance of concurrent engineering and considering multiple disciplines simultaneously. This paper presents a novel classification framework for design optimization problems. The framework sorts design optimization problems based on the type of variables being considered and the objective functions being optimized. It does not focus on the algorithms used to solve the problems. This classification framework provides a new perspective that can help design engineers use optimization in the most appropriate way.Copyright © 2006 by ASME
Non-local sparse models for SAR image despeckling

This paper propose a non-local sparse model for SAR image despeckling. Sparse coding models and non-local means have been both proven very effective in natural image restoration tasks. While self-similarities exist widely in SAR images, which encourages combining these two approaches together for SAR image despeckling tasks. A grouped-sparsity regularizer is imposed to enforce similar image patches to admit similar estimates. Image adaptive dictionary is learned by block-coordinate descent algorithm. Considering the importance of point targets, a new term is integrated into sparse coding models for preserving of point targets. Experimental results show the effectiveness of the proposed algorithm in SAR image despeckling task.
Evaluation of arm-to-leg coordination in freestyle swimming

This study proposes a new method to evaluate arm-to-leg coordination in the freestyle swimming. Eight international-level youth swimmers were tested on a 50m swim at the speed of their 400m personal best (V400), and recorded at 60Hz bilaterally. The discrete relative phase angles between the arm-to-leg movements were identified by video analysis, using four key points adapted from Maglischo (2009): the hand entry corresponding to the lowest point of the ipsilateral kick (C1), the arm catch corresponding to the lowest point of the ipsilateral kick (C2), the lowest point on the arm pull corresponding with the lowest point of the contralateral kick (C3), and the hand exit corresponding to the lowest point of the ipsilateral kick (C4). International-level youth swimmers showed arm-to-leg discrete relative phase values of355.9o±32.7o, 0.5o±38.7o, 352.9o±35.1o and17.5o±33.0o, respectively, for each of the four key events on the freestyle swimming cycle. This coordinative parameter allowed evaluating if the arm-to-leg movements of the swimmer were coordinated in-phase (between 330o and 30o), anti-phase (between 150o and 210o) or out-of-phase on the different phases of freestyle swimming. Therefore, it represented a practical tool to be used by coaches and researchers to quantitatively evaluate their swimming technique.
Giant Cell Tumor of the Patella Tendon Sheath Presenting as a Painful Locked Knee

Patient: Male, 26 Final Diagnosis: Giant cell tumor of the patella tendon seath Symptoms: Efusion • locking knee • pain Medication: None Clinical Procedure: Arthroscopy and open resection of the tumor Specialty: Orthopedics and Traumatology Objective: Rare disease Background: The giant cell tumor of the tendon sheath (GCT-TS) is a benign proliferative synovial tumor manifesting as an intra-articular solitary nodule. When it involves the infrapatellar fat pad it can present acutely as a painful locked knee. Case Report: A 26-year-old white male presented with a 2-week history of painful locking in his right knee. Clinical examination revealed lack of extension by approximately 20°. To help establish the diagnosis, an MRI scan of the right knee was performed, showing a large (5×4×2 cm), oval, well-circumscribed mass with a low-intensity homogenous signal. The size of the mass prohibited the removal by arthroscopy and we therefore proceeded with an open arthrotomy. Histological examination showed a tendosynovial giant cell tumor of the patella tendon sheath. At the latest follow-up, 2 years postoperatively, there was no local tumor recurrence. Conclusions: These rare tumorous lesions should be included in the differential diagnosis of painful locking knee, especially in the absence of definite traumatic history.
Conformance and Interoperability in Open Enviroments

An important issue, in open environments like the web, is guaranteeing the interoperability of a set of services. When the interaction scheme that the services should follow is given (e.g. as a choreography or as an interaction protocol), it becomes possible to verify, before the interaction takes place, if the interactive behavior of a service (e.g. a BPEL process specification) respects it. This verification is known as “conformance test”. Recently some attempts have been done for defining conformance tests w.r. t. a protocol but these approaches fail in capturing the very nature of interoperability, turning out to be too restrictive. In this work we give a representation of protocol, based on message exchange and on finite state automata, and we focus on those properties that are essential to the verification the interoperability of a set of services. In particular, we define a conformance test that can guarantee, a priori, the interoperability of a set of services by verifying properties of the single service against the protocol. This is particularly relevant in open environments, where services are identified and composed on demand and dynamically, and the system as a whole cannot be analyzed.
A Game-Theoretical Model Applied to an Active Patrolling Camera

In patrolling, an agent perceives portions of an environment to detect the presence of an intruder. Usually, the agent cannot perceive the whole environment at once, but can change over time the observed portion. Finding an optimal patrolling strategy that minimizes the possibility of intrusions constitutes one of the main scientific problems in this field. Game theoretical models have been recently employed to compute effective patrolling strategies that explicitly consider the presence of a rational intruder. In this paper, we present a general game theoretical framework for computing patrolling strategies for different kinds of patrollers. In particular, we study the case of an active patrolling camera.
Modeling the Reliability of Packet Group Transmission in Wireless Network

Most previous models about wireless channel are proposed to capture long-time channel characteristics. However, when we combine group transmission with error correcting mechanisms, the steady-state probabilities are no longer accurate enough to depict the short-time loss states. In this paper, we propose a new analytical model for group transmission which can capture influences of initial channel state and group length on transmission reliability. The model offers us a significant insight into loss characteristics of group transmission, which is essential to design reliable wireless protocols. Finally to illuminate the strength of our model, we also apply our model to compare the reliability performance of multipath transmission with single path transmission.
Living on the Edge: Roe Deer (Capreolus capreolus) Density in the Margins of Its Geographical Range

Over the last decades roe deer (Capreolus capreolus) populations have increased in number and distribution throughout Europe. Such increases have profound impacts on ecosystems, both positive and negative. Therefore monitoring roe deer populations is essential for the appropriate management of this species, in order to achieve a balance between conservation and mitigation of the negative impacts. Despite being required for an effective management plan, the study of roe deer ecology in Portugal is at an early stage, and hence there is still a complete lack of knowledge of roe deer density within its known range. Distance sampling of pellet groups coupled with production and decay rates for pellet groups provided density estimates for roe deer in northeastern Portugal (Lombada National Hunting Area - LNHA, Serra de Montesinho – SM and Serra da Nogueira – SN; LNHA and SM located in Montesinho Natural Park). The estimated roe deer density using a stratified detection function was 1.23/100 ha for LNHA, 4.87/100 ha for SM and 4.25/100 ha in SN, with 95% confidence intervals (CI) of 0.68 to 2.21, 3.08 to 7.71 and 2.25 to 8.03, respectively. For the entire area, the estimated density was about 3.51/100 ha (95% CI - 2.26–5.45). This method can provide estimates of roe deer density, which will ultimately support management decisions. However, effective monitoring should be based on long-term studies that are able to detect population fluctuations. This study represents the initial phase of roe deer monitoring at the edge of its European range and intends to fill the gap in this species ecology, as the gathering of similar data over a number of years will provide the basis for stronger inferences. Monitoring should be continued, although the study area should be increased to evaluate the accuracy of estimates and assess the impact of management actions.
Listening to the voices of young children in a nurture class

ABSTRACT The inclusion of the student perspective in helping to promote more effective learning, engagement and positive behaviour is becoming increasingly evident in both educational research and school and classroom practice. Giving students the opportunity to have a meaningful and influential voice enhances both the teaching and learning processes, impacting both academic and social behaviours. The student voice perspective is also making inroads into the area of special educational needs, where children are participating more actively in their own assessment and individual educational plans. This paper presents the findings of a project in a nurture class (NC) in Malta which sought to capture the views of the pupils attending NCs. Through a child friendly, qualitative approach young children were given the opportunity to discuss and express their feelings and thoughts of what it means for them to be a pupil in a NC in primary school. The paper presents the themes which emerged from a thematic analysis of children’s voices during semi-structured group interviews and collaborative mapping and poster design, and concludes with suggestions on how the NC may operate as a more child friendly space at the school.