Miracle-dz/UniFAR-FTUs huggingface dataset:
Singularity Analysis and Illustration of Inverse Kinematic Solutions of 6 DOF Fanuc 200IC Robot in Virtual Environment

In this paper, we demonstrate the analytical method for the solving of the inverse kinematics of 6 DOF manipu- lator arm, the FANUC 200IC, those solutions can be chosen after analysis of the Jacobian matrix, simplification and decompo- sition of this matrix leads us to solve a nonlinear equation with two variable, that we will limit the number of solution found, and that will give us the real workspace of robotaccessible by the end-effector. We validate our work by conducting a simulation software platform that allows us to verify the results of manipulation in a virtual reality environment based on VRML and Matlabsoftware, integration with the CAD model.
A Review on Lung Nodule Detection in CT image using Image Processing Techniques

- Early detection of lung cancer is the promising way of patient’s survival which can be detected by using Computed Tomography which is the technique in the detection of lung nodule compared to the other imaging techniques. This paper describes about the comparison of various image processing techniques such as pre-processing, segmentation, feature extraction and classification and gives a better result on the performance. The most preferred technique from the comparison of by using median filter for pre-processing, optimal thresholding for segmentation and BPN for classification which gives the accuracy, sensitivity, specificity of 98%,99%,98% and also other method using SVM classifier. Thus these methods are preferred for lung nodule detection.
Sculpting representations for deep learning

In machine learning, the choice of space in which to represent our data is of vital importance to their effective and efficient analysis. In this thesis, we develop approaches to address a number of problems in representation learning. We employ deep learning as means of sculpting our representations, and also develop improved representations for deep learning models. We present contributions that are based on five papers and make progress in several different research directions. First, we present techniques which leverage spatial and relational structure to achieve greater computational efficiency of model optimization and query retrieval. This allows us to train distance metric learning models 5-30 times faster; optimize convolutional neural networks 2-5 times faster; perform content-based image retrieval hundreds of times faster on codes hundreds of times longer than feasible before; and improve the complexity of Bayesian optimization to linear in the number of observations in contrast to the cubic dependence in its naive Gaussian process formulation. Furthermore, we introduce ideas to facilitate preservation of relevant information within the learned representations, and demonstrate this leads to improved supervision results. Our approaches achieve state-of-the-art classification and transfer learning performance on a number of well-known machine learning benchmarks. In addition, while deep learning models are able to discover structure in high dimensional input domains, they only offer implicit probabilistic descriptions. We develop an algorithm to enable probabilistic interpretability of deep representations. It constructs a transformation to a representation space under which the map of the distribution is approximately factorized and has known marginals. This allows tractable density estimation and.inference within this alternate domain. Thesis Supervisor: Ryan P. Adams Title: Professor Thesis Supervisor: Ankur Moitra Title: Professor
FIBER OPTIC SOS-TYPE BIOSENSOR FOR THE CONTROL OF THE GENOTOXICITY OF SOME ENVIRONMENTAL OBJECTS

It was proposed simple SOS-type biosensor based on the fiber optics worked in differential regime and allowed the control of such environmental objects which are chemical nature. This biosensor was tested at the determination of the genotoxicity of the number substances as: ethanol, dimethylsulfate and mitomycin C. The sensitivity of the proposed biosensor corresponds to the approaches based on the application based on the traditional, complicate and expensive devices. The developed biosensor may be used for the express analysis, namely during 20 min if the optrodes with the appropriate immobilised cells will be prepared in advance. It was informed that according to the preliminary obtained results the functional activity of such prepared optrodes may be served up to one day. Moreover, it was concluded that the proposed biosensor may have perspective in future for the using in field conditions.
A novel MAC scheme for wireless LANs from the perspective of game theory

In this paper, a novel game theoretic MAC scheme is proposed to improve the performance of IEEE 802.11 DCF in wireless LANs. The channel contention process between the nodes is modelled as a dynamic Bayesian game, called a Multiple Access game. According to the Nash equilibrium of the game, a novel MAC scheme, called G-DCF, is proposed to improve the performance of the legacy DCF. In G-DCF, under saturation conditions (i.e., all nodes always have packets to send), each node adjusts its local contention parameters for data transmission to the current game state (i.e. the number of competing nodes), and thereafter updates the game state through the transmission feedbacks; otherwise, i.e., under non-saturation conditions, a virtual frame scheduling mechanism, called VFS, to keep the game state of the idle nodes in a consistent state, should be incorporated in G-DCF. This process is finitely repeated to get the optimal performance. Simulation results show the new scheme can increase the system throughput and decrease the delay bound and packet-loss-rate.
Computational Study of FundamentalFrequency of Standard Yorùbámonosyllabic Utterances

This paper presents the development and evaluation of a computational model for the fundamental frequency (F0) of Standard Yoruba (SY) monosyllabic utterances. This was done with a view to approximating the F0 curves on SY syllables in the context of speech applications and other speech technologies. A list of 39 SY syllables which are the most frequently occurring syllables in Yoruba newspapers and textbooks was compiled and the speech sound corresponding to the selected SY syllables were recorded for 5 adult native male speakers of SY. The F0 of the speech data were extracted using Praat speech processing package. Thereafter, Least Square Method (using polynomial degree of 1 to 7) was used to design the computational model for the F0 patterns extracted. The computational model was evaluated using the quantitative and the qualitative techniques. The results showed that the 7th degree polynomial had the lowest RMSE value for monosyllabic speech data. The results of the model showed that polynomials with degree 3 gave a good approximation for monosyllabic. The study thereafter established the computational and perceptual correlations between the F0 curves and the three Yoruba tones (High, Mid and Low) for SY monosyllabic utterances. The modeling of F0 contour for Yoruba tones for bisyllabic utterances and continuous speech are the areas of further research works, in which the principle of this work could be extended.
Ensures Dynamic access and Secure E-Governance system in Clouds Services - EDSE

E-Governance process helps the public to learn the information and available of data’s themselves rather than being dependent on a physical guidance. They have been driven through e-govern experience over the past decade; hence there is a necessity to explore new E-Governance concepts with advanced technologies. These systems are now exposed to wide numbers of threat while handling theinformation. This paper therefore designing an efficient system for ensuring security and dynamic operation, so Remote Integrity and secure dynamic operation is designed and implemented in E-Governance environment. The data is stored in the server using dynamic data operation with proposed method which enables the user to access the data for further usage. Here the system does an authentication process to prevent the data loss and ensuring security with reliability method. An efficient distributed storage auditing mechanism is planned which overcomes the limitations in handling the data loss. The content was made easy through the means of cloud computing by using innovative method during information retrieval. Ensuring data security in this service enforces error localization and easy identification of misbehaving server. Availability, Confidentiality and integrity are the key factors of the security. In nature the data are dynamic in cloud service; hence this process aims to process the operation with reduced computational rate, space and time consumption. And also ensure trust based secured access control.
Improved de-noising method based on spare representation for remote sensing image

Remote sensing satellite image de-noising is an important step in image preprocessing. Four de-noising algorithms for remote sensing images are investigated in this paper: BM3D, DCT, K-SVD, and wavelet threshold method. A modified method based on K-SVD is also proposed. The basic principles of the four kinds of de-noising methods are introduced, and the modified method is analyzed thoroughly. In the improved method, high-frequency information is extracted through High-pass filtering, and then sparse representation and reconstruction are carried out to maintain the detail information. Comparative experiments are conducted to reveal the advantages and disadvantages of each method in satellite images de-noising, and the results demonstrate that the proposed method can get better de-noising result as well as keeping the details at the same time.
Quality and Reliability in Analytical Chemistry

It is an interdisciplinary branch of science bridges the gap between pharmacy and analytical chemistry which includes related to computational chemistry and molecular modeling, pharmacokinetics, pharmacodynamics, pharmaceutics, medicinal chemistry, pharmacognosy, drug design, pharmacovigilance, and pharmacogenomics. The current volume 2, issue 2 of the journal of pharmaceutical analytical chemistry provides a platform for scientists and researchers of all over the world to present their new ideas.
Syntax and semantics of the faded partitive construction in Dutch

In this study, several theories concerning the syntax and semantics of the faded partitive construction in Dutch are compared. I present a corpus study of which the results indicate that faded partitive constructions are typically found in informal, spoken Dutch. I argue that the construction can be analysed as having the function of marking that a speaker does not know any straightforward word for the concept she wants to describe and therefore appealing to her own estimate of the hearer and speaker’s shared knowledge.
Le projet MidiShare / Open Source

MidiShare est un systeme d'exploitation musical temps-reel, dedie aux applications MIDI. Originellement concu en 1989, il a ete recompense depuis du prix Apple Trophy (1989), du prix Paris-Cite (1990) et plus recemment du Max d'Or au concours international du logiciel musical de Bourges (1999). Parmi les elements remarquables du systeme figurent sa disponibilite sur les principales plates-formes materielles, son puissant systeme de communication inter-applications ainsi que ses performances temps reel. Il faut egalement mentionner la simplicite d'utilisation et de programmation de MidiShare qui ont certainement contribue a en faire un systeme supporte par un nombre grandissant de projets. L'ampleur actuelle du projet ainsi que l'evolution du contexte dans lequel MidiShare est amene a operer nous ont conduit a en faire un projet 'Open Source' et a repenser l'architecture meme du noyau, de telle sorte qu'elle permette une meilleure prise en compte des problemes de portabilite ainsi qu'une plus grande souplesse dans le design de composants tels que les drivers. Ce sont ces evolutions qui sont presentees, notamment a travers une implementation recente de MidiShare pour GNU/Linux, realisee sur la base de cette nouvelle architecture.
The Use of Text Mining Techniques in Electronic Discovery for Legal Matters

Electronic discovery (eDiscovery) is the process of collecting and analyzing electronic documents to determine their relevance to a legal matter. Office technology has advanced and eased the requirements necessary to create a document. As such, the volume of data has outgrown the manual processes previously used to make relevance judgments. Methods of text mining and information retrieval have been put to use in eDiscovery to help tame the volume of data; however, the results have been uneven. This chapter looks at the historical bias of the collection process. The authors examine how tools like classifiers, latent semantic analysis, and non-negative matrix factorization deal with nuances of the collection process
Fundamentals of Machine Learning for Neural Machine Translation

This paper presents a short introduction to neural networks and how they are used for machine translation and concludes with some discussion on the current research challenges being addressed by neural machine translation (NMT) research. The primary goal of this paper is to give a no-tears introduction to NMT to readers that do not have a computer science or mathematical background. The secondary goal is to provide the reader with a deep enough understanding of NMT that they can appreciate the strengths of weaknesses of the technology. The paper starts with a brief introduction to standard feed-forward neural networks (what they are, how they work, and how they are trained), this is followed by an introduction to word-embeddings (vector representations of words) and then we introduce recurrent neural networks. Once these fundamentals have been introduced we then focus in on the components of a standard neural-machine translation architecture, namely: encoder networks, decoder language models, and the encoder-decoder architecture.
Design and Development of Long-Distance Virtual Teaching System Based on VRML and JAVA

通过情境化学习理论的指导,构建出具有真实感和沉浸感的远程虚拟教学系统,在介绍VRML和JAVA语言特点与互补性的基础上,着重描述了平台的结构和功能,对实现平台的关键技术包括虚拟场景的构建、替身及群体感知等进行了详细介绍,是对远距离教学的一种有益的探索.
Investigation of PV inverter MPPT efficiency test platform

In this paper, the test platform of PV inverter MPPT efficiency is researched. The test method of PV inverter MPPT efficiency is analyzed according to evaluation index of PV inverter MPPT efficiency. Based on the MPPT efficiency test method, The PV array simulation should output P-V curve of PV array in different irradiance and different type of PV module. A 500kW PV inverter MPPT efficiency is tested and evaluated by this platform. The test results verify the validity of the test platform which analyzed in this paper.
Accuracy and interpretability, tree-based machine learning approaches in neuroimaging

For several years, neuroscientists have increasingly shown interests in pattern recognition techniques for the analysis of neuroimaging data [1,2]. The main aims are the development of accurate diagnosis systems but also the identification of brain regions related to the disease. In particular, kernel methods such as Support Vector Machine (SVM)[3,4] are commonly used. With linear kernels, these approaches combine good accuracy, despite their simplicity, and good interpretability through the interpretation of feature weight maps [10]. At the cost of interpretability, non-linear kernels can potentially improve performance by capturing non-linear dependencies in the data. So far, tree approaches have not been really popular in neuroimaging. Yet, with minimal tuning they exhibit several very interesting characteristics: they provide non-linear models, state-of-the-art accuracy on many problems and interpretable results through variable importance scores. In this work, we evaluate several standard tree methods and show that the best of them is competitive with SVM both in terms of accuracy and interpretability.
IMPROVEMENT OF HARDWARE AND SOFTWARE SETUP FOR THE ACQUISITION AND PROCESSING OF SIAM PHOTON SOURCE BPM SIGNAL

Data acquisition and processing system has been developed for the Siam Photon Source (SPS) storage ring BPM system in order to improve monitoring and logging performances. BPM readout, i.e. scanning of BPM electrode voltage outputs and subsequently converting to X-Y position values, is now performed by an upgraded Programmable Logic Controller (PLC) with higher bit resolution (16-bit) analog-to-digital converter (ADC). Moving averaging is then performed on the obtained BPM data utilizing a LabVIEW code to reduce background noise during on-line measurement. All data is then stored on a dedicated computer serving as a central data logging system, which can be remotely accessed via a network communication link. In this report, details of the new setup will be presented, and comparison will be made between the performance of the new and previous setups, together with suggestions on further improvements.
Analisis Komparatif Evaluasi Performa Algoritma Klasifikasi pada Readmisi Pasien Diabetes

Abstract. Readmission is associated with quality measures on patients in hospitals. Different attributes related to diabetic patients such as medication, ethnicity, race, lifestyle, age, and others result in the calculation of quality care that tends to be complicated. Classification techniques of data mining can solve this problem. In this paper, the evaluation on three different classifiers, i.e. Decision Tree, k-Nearest Neighbor (k-NN), dan Naive Bayes with various setting parameter, is developed by using 10-Fold Cross Validation technique. The targets of parameter performance evaluated is based on term of Accuracy, Mean Absolute Error (MAE), dan Kappa Statistic. The selected dataset consists of 47 attributes and 49.735 records. The result shows that k-NN classifier with k=100 has a better performance in term of accuracy and Kappa Statistic, but Naive Bayes outperforms in term of MAE among other classifiers. Keywords: k-NN, naive bayes, diabetes, readmission Abstrak. Proses Readmisi dikaitkan dengan perhitungan kualitas penanganan pasien di rumah sakit. Perbedaan atribut-atribut yang berhubungan dengan pasien diabetes proses medikasi, etnis, ras, gaya hidup, umur, dan lain-lain, mengakibatkan perhitungan kualitas cenderung rumit. Teknik klasifikasi data mining dapat menjadi solusi dalam perhitungan kualitas ini. Teknik klasifikasi merupakan salah satu teknik data mining yang perkembangannya cukup signifikan. Di dalam penelitian ini, model algoritma klasifikasi Decision Tree, k-Nearest Neighbor (k-NN), dan Naive Bayes dengan berbagai parameter setting akan dievaluasi performanya berdasarkan nilai performa Accuracy, Mean Absolute Error (MAE), dan Kappa Statistik dengan metode 10-Fold Cross Validation. Dataset yang dievaluasi memiliki 47 atribut dengan 49.735 records. Hasil penelitian menunjukan bahwa performa accuracy, MAE, dan Kappa Statistik terbaik didapatkan dari Model Algoritma Naive Bayes. Kata Kunci: k-NN, naive bayes, diabetes, readmisi
3D imaging systems based on projectors and mobile phones

In this paper the multi-view 3D display system which includes the modules of capturing three-dimensional objects, image processing (creation of 3D image files) and display screen for the 3D image displaying based on integral imaging technology is developed. Large display screens using multi-projectors are created. Multi-projector system is used for improving the performance, such as viewing resolution, viewing angle, etc. Preliminary experimental results obtained using Full HD multi-projectors are discussed. 3D display based on mobile devices is also developed. 3D image files are created using 2D + depth files and 2D images captured at different view angles. Images on smartphones Sony 4K (resolution 3840 x 2160) and Samsung and LG (resolution 2560 x 1440) are demonstrated.
Privacy, integrity, and incentive-compatibility in computations with untrusted parties

In this dissertation, I study privacy, integrity, and incentive compatibility in computations with untrusted parties. The study of privacy and integrity belongs to the research area of secure multi-party computation , while incentive compatibility is a natural extension of the research on secure multi-party computation. First, I present a mix network tailored for election systems, with a substantial speedup over previous work. Second, I design and analyze efficient algorithms for distributed mining of association rules. Third, to protect data integrity in an untrusted storage service, I study the possibility of entangling multiple users' data together in such a way that loss of one user's data implies loss of all others'. Fourth, I introduce VDOT, a new cryptographic primitive, which can be viewed as an extension of oblivious transfer with malicious servers. I also apply VDOT to the problem of mobile-agent security to implement the key components of an architecture for mobile agents. Finally, I propose a way to add incentive considerations to the study of secure multi-party computation, by stimulating cooperation among selfish mobile nodes in an ad hoc network. I propose Sprite, a simple, cheat-proof, credit-based system for accomplishing this task. The system suppresses cheating behavior and provides incentives for mobile nodes to cooperate and report actions honestly. Simulations and analysis show that mobile nodes can cooperate and forward each other's messages, unless the resources of each node are extremely depleted.
An effective integration of subdivision surfaces in a hybrid computer-aided design system

Our integration approach relies on a CAD system based on an extensible geometric kernel, which means: •Parametrization and evaluation paradigm: any geometric entity, represented in parametric form, can be integrated by simply implementing the related evaluation algorithm, that acts as an interface with the entire system. In this way, all the functionality of the CAD system are automatically inherited by any newly introduced type of representation •Extended boundary representation (B-rep), which allows non-solid model types, so as to integrate surface modeling into a solid modeling environment (hybrid CAD system) •Hybrid description of the geometry in the B-rep, that is allowing for the coexistence of different forms of geometric representation in the same model Integration through the Subd B-rep