Miracle-dz/UniFAR-FTUs huggingface dataset:
REGULARISED IDENTIFICATION USING MULTI-OBJECTIVE OPTIMISATION METHOD

Although the regularisation increased the popularity of inverse analysis due to its capability of deriving a stable solution, the significant problem is that the solution depends upon the regularisation parameters chosen. This paper presents a technique for deriving solutions without the use of the parameters, and further an optimisation method, which can work efficiently for problems of concern. Numerical examples show that the technique can efficiently search for appropriate solutions. INTRODUCTION It often becomes difficult to solve inverse problems if measurement data are not sufficiently available and/or if measurement data and/or the direct model contains large errors [1]. One of the approaches for overcoming this problem is to introduce a regularisation term to a functional to be minimised [2,3], which normally consists of a function multiplied with weighting factors. The term makes the functional smooth, so that a conventional calculus-based optimisation can obtain an appropriate parameter set without divergence or vibration. The problem of the regularisation is however the selection of its weighting factors as the solution obtained depends upon the selection. Most of the research work thereby shows results with a couple of selections and leaves the selection for further studies. Finding the best value of the weighting factors has not yet been much studied and can been found only in several papers to the best of the authors’ knowledge [4-6]. In some techniques, the best weighting factors are found after a single solution is obtained. In this case, additional parameters are however introduced to find it, and the solution is again dependent on these parameters. The other techniques find solutions each with a different set of weighting factors by a step size before finding a single solution by some criteria, thereby the solutions not depending on the weighting factors. Deriving a number of solutions with a single optimisor is however time-consuming, and, in addition, the solutions are governed by the step size of each weighting factor. On the other hand, multi-objective optimisation methods, which optimise a vector functional thereby giving a set of admissible solutions rather than a single solution, have been proposed, mostly by the evolutionary computation community, and have received remarkable attention [7-9]. The most popular evolutionary algorithm (EA) is the genetic algorithm (GA) [10], which incorporates binary strings and their reproduction. Despite, GA is too inefficient for the minimisation of continuous functions with continuous parameters, which is a typical inverse problem and the problem of the authors’ concern. In this paper, a technique for solving a regularised inverse problem without weighting factors is first proposed. In this technique, regularisation terms are each formulated as another objective function, and the multi-objective optimisation
Machine Learning Techniques to Enable Closed-Loop Control in Anesthesia

The growing availability of high throughput measurement devices in the operating room makes possible the collection of a huge amount of data about the state of the patient and the doctors' practice during a surgical operation. This paper explores the possibility of extracting from these data relevant information and pertinent decision rules in order to support the daily anesthesia procedures. In particular we focus on machine learning strategies to design a closed-loop controller that, in a near future, could play the role of a decision support tool and, in a further perspective, the one of automatic pilot of the anesthesia procedure. Two strategies (direct and inverse) for learning a controller from observed data are assessed on the basis of a database of measurements collected in recent years by the ULB Erasme anaesthesiology group. The preliminary results of the learning approach applied to the regulation of hypnosis through the bispectral index (BIS) in a simulated framework appear to be promising and worthy of future investigation
Beauty Is in the Eye of the (Data) Beholder: Behavioral Researchers' Dilemmas Using Behavioral Big Data

Behavioral Big Data (BBD) refers to very large and rich multidimensional datasets on human and social behaviors, actions and interactions, which have become available to companies, governments, and researchers. Data mining and statistical methods are applied to BBD for prediction and for causal explanation. Researchers trying to extract knowledge and scientific discoveries from BBD experience not only methodological and technical challenges but also ethical and moral dilemmas. In this paper we discuss dilemmas and trade-offs that arise in three steps of BBD research: data acquisition, data analysis, and performance evaluation.
Post Processing Pedestrian Detection with Background Cues

In this project, I develop an approach to post process local pedestrian detection by incorporating cues from the background. This approach uses a combination of several location specific color classifiers to quickly reduce the number of the local detector responses by discarding improbable results. An experimental method for color comparison is explored in this project to supplement existing techniques for color matching. Using the reduced subset feedback from the color classifiers, I estimate the horizon line position and partition the set into overlapping subsets. The final result is determined by the strength of each subset. This framework can be attached to any existing local pedestrian detector.
A comparison of data mining techniques for intrusion detection

The Expositional increase in the traffic across networks has necessitated the need to detect unauthorized access. In this sense Intrusion Detection has become one of the major research areas In this paper three data mining techniques namely C5.0 Decision Tree, Ripper Rule and Support Vector Machines are studied and compared for the efficiency in detecting the Intrusion, It is found that the C5.0 Decision Tree is efficient than the other two. The data mining tool clementine is used for evaluating this on the KDD99 dataset. The results are also given in this paper.
Adapting polarised disambiguation to surface realisation

The aim of surface realisation is to produce a string from an input semantics. The task may be viewed as the inverse of parsing, and like parsing, it is made more difficult by the problem of lexical ambiguity in natural language. (Bonfante, Guillaume, and Perrier 2004) propose a polarisation technique for parsing that greatly reduces the effects of ambiguity. We show how polarisation can be adapted for surface realisation and how to address two complications which arise: multi and zero-literal semantic input.
A Continuous Software Quality Monitoring Approach for Small and Medium Enterprises

Context: SMEs cannot always afford the effort required for software quality assurance, and therefore there is the need of easy and affordable practices to prevent issues in the software they develop. Object: In this paper we propose an approach to allow SMEs to access SQA practices, using an SQA approach based on a continuous issue and error monitoring and a recommendation system that will suggest quality practices, recommending a set of quality actions based on the issues that previously created errors, so as to help SMEs to maintain quality above a minimum threshold. Method: First, we aim to identify a set of SQA practices applicable in SMEs, based on the main constraints of SMEs and a set of tools and practices to fulfill a complete DevOps pipeline. Second, we aim to define a recommendation system to provide software quality feedback to micro-teams, suggesting which action(s) they should take to maintain a certain quality level and allowing them to remove the most severe issues with the lowest possible effort. Our approach will be validated by a set of local SMEs. Moreover, the tools developed will be published as Open Source.
Impact of P2P traffic on IP communication networks’ performances

Over recent years there has been a large increase in the use of P2P (peer- to-peer) applications around the world. These applications have become very popular today and there are a lot of new users every day. Increasing of P2P users has a very great impact on increasing P2P traffic in communications networks. In this paper we pay attention to measuring of P2P traffic, by analyzing and simulating these kinds of network traffic. The estimated parameters of the measured traffic in analysis were used for modeling such traffic in a simulation tool, where we show how P2P traffic has an impact on IP communication networkspsila performances. For this reason we built a test network in OPNET simulation tool where users, in addition to classical applications, also use P2P applications. We modeled the custom application which is based on the measurement of P2P traffic for a normal user.
02-1 3-D SOUND REPRODUCTION THROUGH STEREO INNER-PHONES

A 3-D sound reproduction method through stereo inner-phones is proposed. This method uses HRTFs and a correction filter, Hc, which compensates the changes of the transfer functions of the ear canals caused by insertion of the stereo inside-phones. The results of the localization tests in the horizontal and the median plane indicated that the perceived direction agrees with the simulated one. Furthermore, non-individual HRTFs among subjects are selected by localization tests. The detailed observation of the selected non-individual HRTFs shows that they have emphasized characteristics in directional dependence.
Pathological changes in the cellular structures of retina and choroidea in the early stages of alloxan-induced diabetes

AIM To investigate the temporal sequence of pathological changes in the cellular structures of retina and choroidea in the early stages of diabetes in laboratory animals. METHODS Experimental type 1 diabetes was modeled by three intraperitoneal injections of an alloxan solution into 30 male nonlinear rats at 16 wk of age. The 30th and 60th days from the final alloxan injection were chosen as the endpoints. Light and electron microscopy and morphometric and immunohistochemical studies were performed on histological slices of eyeballs from experimental animals. RESULTS Diabetic disturbances progressed to 60 d of the experiment. Thus, in the retina, a partial destruction of photoreceptors accompanied by interstitial edema was observed. The morphometric analysis revealed a reduction in the thickness of the retina. A reduction in the number of blood vessels of the choroid with disturbances of the endothelial cells and the vascular walls and a persistent reduction in the number of melanocytes were observed. The number of proliferating Ki-67 positive cells decreased, and the number of macrophages increased with diabetes development. CONCLUSION The starting point in the development of destructive changes involves early reduction in the number of melanocytes of the choroidea and alterations in the retinal pigment epithelium.
Vehicle Lateral Control Under Fault in Front and/or Rear Sensors: Final Report

This report presents the research results of Task Order 4204(TO4204), "Vehicle Lateral Control under Fault in Front and/or Rear Sensors". This project is a continuing effort of the Partners for Advanced Transit and Highways (PATH) on the research of passenger vehicles for Automated Highway Systems (AHS).
Following specific podocyte injury captopril protects against progressive long term renal damage

Background: Angiotensin converting enzyme inhibitors (ACEi) reduce proteinuria and preserve kidney function in proteinuric renal diseases. Their nephroprotective effect exceeds that attributable to lowering of blood pressure alone. This study examines the potential of ACEi to protect from progression of injury after a highly specific injury to podocytes in a mouse model. Methods: We created transgenic (Podo-DTR) mice in which graded specific podocyte injury could be induced by a single injection of diphtheria toxin. Transgenic and wild-type mice were given the ACEi captopril in drinking water, or water alone, commencing 24h after toxin injection. Kidneys were examined histologically at 8 weeks and injury assessed by observers blinded to experimental group. Results: After toxin injection, Podo-DTR mice developed acute proteinuria, and at higher doses transient renal impairment, which subsided within 3 weeks to be followed by a slow glomerular scarring process. Captopril treatment in Podo-DTR line 57 after toxin injection at 5ng/g body weight reduced proteinuria and ameliorated glomerular scarring, matrix accumulation and glomerulosclerosis almost to baseline (toxin: 17%; toxin + ACEi 10%, p<0.04; control 7% glomerular scarring). Podocyte counts were reduced after toxin treatment and showed no recovery irrespective of captopril treatment (7.1 and 7.3 podocytes per glomerular cross section in water and captopril-treated animals compared with 8.2 of wild-type controls, p<0.05). Conclusions: Observations in Podo-DTR mice support the hypothesis that continuing podocyte dysfunction is a key abnormality in proteinuric disease. Our model is ideal for studying strategies to protect the kidney from progressive injury following podocyte depletion. Demonstrable protective effects from captopril occur, despite indiscernible preservation or restoration of podocyte counts, at least after this degree of relatively mild injury.
Ensuring software quality by formal modeling

Software quality is always the target of disagreement between developers and users because of its subjective nature. The problem with software quality is the lack of formal definitions. Furthermore, quality metrics are based on empirical indices. This paper presents a method to the application of formal modeling techniques in the subject of software quality verification. We give a high-level view of the approach, leaving the deep details for a later discussion. We also provide a short summary of Software Quality models and standards.
Mouse Activity as an Indicator of Interestingness in Video

Automatic detection of interesting moments in video has many real-world applications such as video summarization and efficient online video browsing. In this paper, we present a lightweight and scalable solution to this problem based on user mouse activity while watching video. Unlike previous approaches that analyze video content to infer the interestingness, we leverage the implicit user feedback obtained from thousands of online video watching sessions. This makes our method computationally efficient and scalable to billions of videos. Most importantly, our approach can handle a variety of video genres because we make no assumption on what constitutes interestingness: we let the crowd tell us through their mouse activity. By analyzing 106,212 user sessions collected from a popular online video website, we show that mouse activity is highly indicative of interestingness, and that our approach has competitive performance to several state-of-the-art methods.
Auto-tuning GEMM Kernels for a Decoupled Access/Execute Architecture Processor

A typical decoupled access/execute architecture (DAE) processor is consisting of Access Processors (AP) and Execute Processors (EP). The overhead of memory access of AP can be hidden by calculation of EP. Based on this principle, a new optimization algorithm of general dense matrix multiplication operation (GEMM) will be introduced in this paper. The algorithm is divided into four levels, every level of which uses different storage structure of the processor. That makes the algorithm closely combine with the features of DAE architecture. Furthermore, a fetch performance evaluation system - DAEFS will also be introduced. It is a runtime system with very little overhead, and can be used to collect the information about the relationship between fetching and calculation for DAE processors. With the help of DAEFS, several levels of the new algorithm are capable to self-adjust. Consequently, the algorithm can find the best block parameters for several levels during runtime. We implement the algorithm with DAEFS on a DAE processor platform - Godson-3B, which has been used to build up the teraflop computer - KD90. The performance of the optimized GEMM on the real platform matches the best simulation results of this processor.
The Benefits of Individualized Leisure and Social Activity Interventions for People with Dementia: A Systematic Review

This systematic review describes the benefits of individualized leisure and social activity interventions for people with dementia (aim 1), how these interventions were individually tailored (aim 2), and what recommendations or suggestions can be made for these interventions and further studies (aim 3). Thirty-two included studies were organized into four categories based on how the intervention was individually tailored. These categories include: (1) performance factors; (2) self-identity; (3) music preference; and (4) life experiences and past memories. The authors discuss suggestions and benefits by synthesizing the finding of the included studies in each category.
Synchronized Multi-Channel Cognitive MAC Protocol with Efficient Solutions for Second Spectrum Access

The MAC protocols for cognitive radio network should permit access to unused white spectrum without (or with minimal) interference to incumbent devices. With in mind the fact that channel availability can rapidly change over space and time, the coordination between the users is important. In this paper a synchronized cognitive MAC protocol for decentralized network is proposed, the protocol works in multiple channels so it can deal with resource availability and with the aide of time slots the scarcity of the dedicated common control channel had been resolved. With the enhancement of GPS receiver capabilities, a prominent neighboring discovery, transmission power estimation and synchronization have been achieved. Efficient sensing and updating information exchange mechanism enhance the primary detection and resolve the hidden terminal problem. The protocol enables the secondary users to identify and utilize the leftover frequency spectrum in a way that constrains the level of interference to the primary users, preserve the transmission energy, and improves the network performance as demonstrated by the analysis and simulation.
Understanding the effect of environmental factors on link quality for on-board communications

A research topic that is becoming increasingly popular is that of on-board mobile communication, where users on a vehicle are connected to a local network that attaches to the Internet via a mobile router and a wireless link. One critical issue in such a moving network architecture is the possibility of temporary outages due to low quality of wireless links between on-board routers and base stations. In an on- board communication network, a single link outage may impact a large number of existing connections. The ability to predict link outages before they occur, which becomes possible when the route of the vehicle is known in advance (e.g. for public transport), can significantly improve the performance of on-board moving networks. In this work, we show some results on the impact of different factors on the signal strength in a metropolitan area. Our study suggests that location is a promising factor in the context of outage prediction for on-board mobile networks. We observe that signal strength is strongly correlated with locations across different times of a day. Additionally, we find that, while the signal strength levels measured at low and medium speeds are similar, there are larger variations and more frequent handoffs at a lower speed. These insights may be useful for designing realistic detailed simulations. Index Terms— GPRS, Outage prediction, On-board network
Assessing the bus factor of Git repositories

Software development projects face a lot of risks (requirements inflation, poor scheduling, technical problems, etc.). Underestimating those risks may put in danger the project success. One of the most critical risks is the employee turnover, that is the risk of key personnel leaving the project. A good indicator to evaluate this risk is to measure the concentration of information in individual developers. This is also popularly known as the bus factor (“number of key developers who would need to be incapacitated, i.e. hit by a bus, to make a project unable to proceed”). Despite the simplicity of the concept, calculating the actual bus factor for specific projects can quickly turn into an error-prone and time-consuming activity as soon as the size of the project and development team increase. In order to help project managers to assess the bus factor of their projects, in this paper we present a tool that, given a Git-based repository, automatically measures the bus factor for any file, directory and branch in the repository and for the project itself. You can also simulate with the tool what would happen to the project (e.g., which files would become orphans) if one or more developers disappeared.
COMPARISON OF PROSODIC FEATURES IN SWEDISH AND FINNISH IDS/ADS SPEECH

A set of speech corpora, spoken in both IDS and ADS modes containing similar sentences in terms of complexity, was collected in Sweden and Finland in 2007. Prompts for each language were designed by selecting 10 obj ect words and 10 carrier sentences for each language to produce approximately 100 diff erent sentences. Each sentence was spoken 10 times in adult-directed speech (ADS) mode and 10 times in infant-directed speech (IDS) mode, for a total of 2000 sentences pe r speaker. Four speakers, typically two pairs of married couples from each language, were used to produce a total of 8000 utterances per language. The corpora, that also inc luded Dutch and English, were collected to aid in the exploration of new architec tures for speech recognition, as is currently taking place in the ACORNS 1 project This study describes the main prosodic differences found in IDS/ADS speech from the collected Swedish and Finnish material. Statistical analysis of the following main features are reported: - F0 histograms: these may reveal speaking style di fferences in the F0-contours. - Spectral tilting and its fluctuation: this also i s affected by the voice source and the “softer” speaking style encountered with IDS. - Segmental durations and their variations: average speaking rate and indications of monotonic/non-monotonic speaking style. - Differences in spectral properties: the signals a re analyzed in frames of 10 ms and the MFCC-coefficient vectors clustered in a vector spac e. The cluster centres reveal average spectral properties and differences in spea king style that can be detected as differences in the number of clusters found as well as differences of their mean vectors. The analysis is performed for four Swedish and four Finnish speakers (two males and two females for each language). Tests are carried out t o detect any common characteristics between IDS and ADS speech for these two languages.
MoM analysis of radiation and scattering of broadband array antenna

This paper describes the comparison of numerical and experimental results of the radiation and scattering characteristics of a tapered slot array antenna (TSA). The purpose of the comparison is to validate the effectiveness of a developed analysis technique based on the method of moments for broadband antennas. Since the radiation and scattering characteristics depend on the electrical property of the circuits connected to antenna terminals, 50Ω or open terminators are connected to the input ports of the TSA. The numerical and experimental results are in good agreement; thus, it indicates that the developed technique enables us to analyze the electric characteristic of broadband antennas.