Miracle-dz/UniFAR-FTUs huggingface dataset:
BOUNDING BOX METHOD BASED ACCURATE VEHICLE NUMBER DETECTION AND RECOGNITION FOR HIGH SPEED APPLICATIONS

License plate detection and recognition is the one of the major aspects of applying the image processing techniques towards intelligent transport systems. Detecting the exact location of the license plate from the vehicle image at very high speed is the one of the most crucial step for vehicle plate detection systems. This paper proposes an algorithm to detect license plate region and edge processing both vertically and horizontally to improve the performance of the systems for high speed applications. Throughout the detection and recognition the original images are detected, filtered both vertically and horizontally, and threshold based on bounding box method. The whole system was tested on more than twenty five cars with various license plates in Indian style at different weather conditions. The overall accuracy rate of success recognition is 93% at sunlight conditions, 72% at cloudy, 71% at shaded weather conditions.
Educational integration of prayer in islam using an augmented reality approach

: Recently, the majority of researchers are interested to utilize advanced technology to find several new creative methods so that students are able to understand the lessons easily. Furthermore, AR “Augmented Reality”, a well-known innovative technology, is the most important transformation in education world. AR is, in addition, a new method uniting several aspects, such as social and tangible computing. Besides, this method has been widely used some education levels since it unites the differing world between virtual and physical world. Nevertheless, the execution in early childhood education has not been maximum yet and, especially for moral values that are taught since childhood for instance praying or Muslim often call as Do’a. Furthermore, in Islam Do’a is a very crucial thing although some people assume that it is trivial. This is probably caused by many variations of Do’a, so that Do’a is little tough to be practiced. Accordingly, with growing technology learning through e-learning like AR can solve this problem. This study aimed to delve deeper into AR that has been designed in “Marker-based” namely “Do’a 4D” and installed in mobile. Lastly, this research explains that the Augmented Reality’s approach is particularly suitable to increase and to ease the understanding of children about Do’a.
ANALYZING SYSTEMS FOR POST-QUANTUM CRYPTOGRAPHY

Modern cryptography relies on the intractability of certain problems in mathematics, such as those related to factoring, discrete logarithms, and elliptic curves. Cryptographers have exploited the hardness of such problems to construct the world’s most widely used cryptosystems, which have become critical in matters of electronic privacy, banking, national security, and others. These systems, resting on inefficiencies in classical computing, will likely become obsolete in the presence of a machine with superior computing ability. We assess that the introduction of quantum computing will force cryptographers to reexamine the schemes they once thought to be robust against computationally bounded adversaries. In 2017, 69 research groups from around the world submitted proposals to the United States’ National Institute of Standards and Technology (NIST), suggesting new quantum resistant public-key infrastructures and signature schemes for standardization. We have examined the quantum resistant public-key systems presented to NIST, grouped them based on security assumption, and recommend the most viable option, considering resistance to known quantum attacks, efficiency, and fast implementation under existing classical
Kesavulu Reddy Cryptosystem to Resistance against Simple Power Analysis Attacks in Mobile Devices

Elliptic curve cryptosystems are more efficient and secure than the conventional cryptosystems like RSA cryptosystems. We develop a Secret Key in the EKR Modified Montgomery Inversion Algorithm to avoid leaks the value of function f in Almost Montgomery Inversion Algorithm. The attacker can not guess the Secret key (t) to retrieve the valuable information in smart cards and mobile devices. We want to develop the new cryptosystem based on EKR Modified Montgomery Inversion Algorithm to resistance against Simple Power Analysis Attacks in Sidechannel Attacks in Elliptic Curve Cryptosystems like RSA Cryptosystems.
An autonomous knowledge acquisition system toward the ubiquitous knowledge management

Knowledge management (KM), which pursues dynamic knowledge creation and sharing within and among organizations, had been boomed since the end of the last century. However, because of some technical limitations as well as cultural barriers, the concept of KM has been getting buried alive, nowadays, in spite of its tremendous potentials to organizations. One of the most serious problems that conventional KM has has been pointed out tardy and ineffective acquisition of knowledge, which initiates the tragedy in knowledge revolution. Without knowledge to be managed, naturally the usability of knowledge management must be doubted. Therefore, this paper suggests an amended KM framework, especially focused on the autonomous knowledge acquisition process. The suggested methodology for knowledge acquisition is basically processed in an automated manner, but follows the same pattern of human experts’ activities for acquiring knowledge by deploying the capabilities of ubiquitous computing technologies. Based on the proposed methodology, this paper also clarifies the relationship between context and knowledge, and hence defines the concept of contextual knowledge. To validate the feasibility of the proposed concepts, CKAS (Context-based Knowledge Acquisition System), a prototype system, is implemented.
in Economics : 1983 MEASURING INEFFICIENCY IN INTERNATIONAL ELECTRICITY TRADING

Interconnectors reduce the cost of electricity supply if they are operated efficiently. We show that established metrics used to monitor electricity trading inefficiency become increasingly inaccurate in several trading conditions. We devise the Unweighted and Price-Weighted Inefficient Interconnector Utilisation indices to address these deficiencies. These metrics are substantially more accurate than existing ones and perform equally well whether or not markets are coupled. Our results show a substantial decrease in inefficient trading between Great Britain and both France and the Netherlands after the European Union’s market coupling regulations were introduced in 2014. In view of Great Britain’s likely withdrawal from the European Union, the paper also evaluates how market uncoupling would affect cross-border trade. We find that uncoupling would lead to inefficiencies in trade, the electricity price differential between GB and France (Netherlands) rising by 3% (2%), net imports into GB decreasing by 26% (13%), congestion income decreasing by 10% (5%), and inframarginal surplus decreasing by 1.6% (1.6%) of coupled congestion income. We also show that, should the EU decide to implement an equivalent carbon tax to GB’s Carbon Price Floor, uncoupling impacts would be slightly magnified due to electricity prices converging (by about 1% of coupled congestion income).
THE DETERMINATES OF TRANSFORMATIONAL LEADERSHIP IN KOSOVO SMEs

In this paper will be conducted a closer look at leadership styles that affect transformations of different organizations to focus on transformational leadership that will play a key role in determining determinants that directly influence transformations in small and medium enterprises (SMEs), in Kosovo. This research aims to identify all those factors that are of great importance to the changes that affect the organization, including the structure, people, culture, and various processes that are of great importance to local companies in identifying these key elements which are essential. This research will also be extended to the different leadership styles of leadership in organizations, looking closely at different governance models that our managers apply to. This research will be organized through a research methodology and redundant instruments to evaluate indicators that point to transformations and towards a fair and loyal competitor. Transformations that are highlighted in this paper are mostly focusing on people and culture, where through employee changes we see new horizons in improving skills and developing new experiences by expanding the organization's benchmarking, as well as changes in culture are essential because through it we create a good image of the company, prestige and representativeness. Therefore through these elements we will see transformation as a process and how organizations are flexible in the adaptability of this process as a positive and progressive change.
Optimal weighting models based on linear uncertain constraints in intuitionistic fuzzy preference relations

Abstract The priority weight vectors of an intuitionistic fuzzy preference relation (IFPR) with linear uncertainty distribution characteristics in group decision making (GDM) are determined in this study. On the basis of an IFPR, the assumptions of additive consistency and decision-making preference variables obeying the uncertainty distribution are defined. Afterward, a priority model is constructed with a chance constraint, and the ranking relations of the membership and non-membership matrices are analysed. The change in the confidence level of the chance constraint controls the flexibility of realising additive consistency. Moreover, it is proven that if the individual decision makers’ IFPR has a linear distribution, the group IFPR aggregated by the weighted methodology still obeys this distribution. Finally, an uncertain linear ranking consensus model of the IFPR is developed, and a numerical example is used to verify its feasibility.
New integral properties for Potential Vorticity and applications to the ocean dynamics

Since the work of Ertel (1942), Potential Vorticity (PV) is a recognized as a key quantity to study the circulation and in particular to understand geophysical turbulence. Many processes can indeed be explained by combining PV conservation properties and the PV inversion principle. Diabatic processes transform PV but this transformation is subject to constraints that allows to use "PV thinking" even when there exists mixing.
Uncertainty Quantication in Structural Dynamics Using Non-central Wishart Distribution

Uncertainties need to be taken into account for credible predictions of the dynamic response of structural systems. Such uncertainties include uncertainties in the system parameters (parametric uncertainty) and those arising due to the modelling of a complex system (nonparametric uncertainty). Over the past four decades distinct methods have been developed to quantify these two types of uncertainties separately. In this paper we proposed a hybrid approach to model both parametric and nonparametric uncertainties simultaneously. The proposed approach is based on a noncentral Wishart distribution. Its parameters are obtained such that the covariance matrices of the elements of the mass, sti.ness and damping matrices, arising due to parametric uncertainties, are satis.ed in a least-square sense. The existing nonparametric distribution (a central Wishart distribution) can be obtained as a special case of the proposed noncentral Wishart distribution. A simple simulation algorithm is developed to implement the noncentral Wishart random matrix model in conjunction with the finite element method. The method is applied to the vibration of a cantilever plate with uncertainties. The dynamic response obtained using the noncentral Wishart random matrix model agrees well with the results obtained from the stochastic finite element method.
Scientific Report for COST-STSM-TD1207 from 1st October – 31st October 2016 Objective: Analysis on Demand Response Concepts under Uncertainty for Demand Side Flexibility Employment within City Districts

The electrical energy grid currently changes significantly from a demand-side driven to a supply-side driven system due to an increasing amount of distributed energy resources. A promising approach for the integration of distributed energy resources, such as photovoltaic systems or wind turbines within the low and medium voltage network can be an efficient and robust demand side response management. The demand side flexibility is used to shift the energy consumption of flexible devices into times of, e.g. renewable energy supply for optimal balancing demand and supply. Flexibility on the demand side is achieved by the coordination of the operation of e.g. electro-thermal heating units or electric-vehicles. For the deployment of demand side flexibility through the operation of energy units on the demand side, the uncertainty, e.g. within the electrical or thermal energy demand or introduced through weather uncertainty, is in many cases not considered within the optimization problem.
Gradient‐Guided Local Disparity Editing

Stereoscopic 3D technology gives visual content creators a new dimension of design when creating images and movies. While useful for conveying emotion, laying emphasis on certain parts of the scene, or guiding the viewer's attention, editing stereo content is a challenging task. Not respecting comfort zones or adding incorrect depth cues, for example depth inversion, leads to a poor viewing experience. In this paper, we present a solution for editing stereoscopic content that allows an artist to impose disparity constraints and removes resulting depth conflicts using an optimization scheme. Using our approach, an artist only needs to focus on important high‐level indications that are automatically made consistent with the entire scene while avoiding contradictory depth cues and respecting viewer comfort.
Simple CBIR using Color Histogram Comparison

I developed my solution from scratch using both the . net framework and python (2.7). For the GUI framework, I chose to use WPF, which is the successor to Windows Forms. I did so because of the power and flexibility of WPF while still providing an easy design process. I chose to use python for the core code because it was easy to prototype with and provided essential libraries for efficient data manipulation (numpy) and image deserialization (SimpleCV).
Examining the topology and dryness of the stratum corneum with a standard SIAscope

When the skin is viewed in close up the surface is composed of fine lines and wrinkles. Detailed measurements of these structures are of great interest in both the research of products designed to reduce the appearance of wrinkles and also in the education of consumers. Standard techniques to measure the topology of skin range from making physical silicon replicas of the skin which are than traced to stereo and fringe projection[3]. All of these techniques produce excellent results but are limited to laboratory analysis due to costs and acquisition times. This paper explores the use of a standard SIAscope to assess 3D surface information in a fast and effective manner suitable for wide deployment within clinical trials and investigations. In particular it develops a method for measuring both the topology of skin and also its level of hydration.
Huawei Report : A Survey of Turbo MIMO Receivers for LTE / LTE-A Students :

Since their emergence, turbo multiple-input multiple-output (MIMO) systems experienced many advancements on both the transmitter and receiver sides. In this report, we review the major contributions in the field of iterative MIMO receivers. Sections II, III, IV, and V provide an extensive review on current hard and soft detectors, channel decoders, and iterative receivers for MIMO systems. The presented algorithms are compared from a computational complexity versus performance perspective. In section VI, we propose a set of research directions for the Huawei/UIUC turbo MIMO receivers project. These research directions include turbo scheduling, receiver algorithm development, and implementations of turbo MIMO receivers. I. MIMO SYSTEM MODEL A MIMO system has MT transmit antennas that transmit a MT ×1 symbol vector s each channel use. Each element of s is transmitted on one antenna and is chosen from a constellation of size 2 . Thus, a total of qMT bits are transmitted per channel use. The set of constellation points are denoted as F and the transmit vector s ∈ FMT . The channel is modeled as a flat Rayleigh fading channel such that the received vector is y = Hs + n. Denoting MR as the number of received antennas, y is a MR×1 vector, H is the channel matrix of size MR×MT with channel coefficients typically modeled as independent and identically distributed (i.i.d.) complex Gaussian random variables, and n is spatially white Gaussian noise, a MR × 1 complex Gaussian vector with zero mean and variance chosen for a specific SNR. This model is shown in Fig. 1. Note: the i.i. d. assumption on H is a baseline assumption. In practice, we will employ both i.i. d. and correlated channel models in our study. Nevertheless, it should be noted that the MIMO capacity will be reduced in the presence of correlated channel entries. Finally, MIMO gains could be enhanced via several techniques such as spatial multiplexing and transmit diversity, in addition to others. Actually, Long Term Evolution Advanced (LTE-A) systems, the focus of this project, provides the designer the choice of using either transmit diversity or spatial multiplexing (or both). Hence, we will consider both modes of operation. When appropriate, we will describe how the transmitted vector x is chosen to satisfy one or both modes of operation.
An adaptive image denoising method based on Deep Rectified Denoising Auto-Encoder

Stacked Sparse Denoising Auto-Encoder(SSDA) has been successfully applied to image denoising, which is superior to the most of the traditional image denoising algorithms. However, the algorithm has low training convergence speed and poor universality. To address these limitations, we present an adaptive image denoising method based on Deep Rectified Denoising Auto-Encoder. To reduce training difficulty and speed up convergence, the rectified linear units (ReLu) is used as activation function of the network, and batch normalization(BN) is used to normalizes the input data of the middle layer in network. Different from the previous image denoising model, the proposed model is trained to learn the mapping relationship between noisy image and noise by residual learning. To overcome the problem that the new model cannot effectively deal with noise not seen in training, we perform adaptive training of multiple channels on the improved model to obtain the optimal channel weights and jointly output the denoised image. The experimental results show that the proposed algorithm can not only outperform SSDA in the convergence speed, but also adaptively remove the noise that is not seen in training.
Application of the Profinity eXact TM Fusion-Tag System to Eukaryotic Expression Systems

Introduction Protein overexpression and affinity purification are used in various biological research fields and play an important role in the postgenomic era. While expression of recombinant proteins in bacteria is often the preferred method, eukaryotic expression systems, especially those using insect and mammalian cells, are indispensable for producing proteins that are difficult to express in bacteria or that have specific required posttranslational modifications. Currently, different purification tags, like 6xHis and GST, are used with eukaryotic expression systems, but they have serious drawbacks. For example, insect and mammalian cells contain a higher percentage of His residues in their proteins than E. coli, which can lead to significant background binding to immobilized metal ions (Kimple and Sondek 2004). Furthermore, current affinity purification systems require a tag-removal step, which is necessary if the tag interferes with the function of the protein.
A Hybrid Concept for Numerical Applications in Java

Java is widely recognized as a good object-oriented programming language. However, it is often considered as too slow for numerically intensive applications. This paper presents a hybrid software package that brings the computational efficiency of numerical Fortran libraries to Java. The package is organized in two layers. In the first layer, Java wrappers provide access to numerical libraries like BLAS, LAPACK or NAG. The second layer comprises vector and matrix classes as well as classes for common linear algebra tasks. Numerical experiments show that this strategy can substantially improve the performance of Java based numerical applications.
Space Cube: a 3D Puzzle for Study Model

In the process of architecture design, the manufacture of study model acts a procedure of swift transformation from concept to a visible model. Since the era of CAD/CAM approaches, the tool of constructing the model evolves from the traditional physical model to digital model in the mode of the manufacture of study model. The virtual model, which is utilized in the incipient concept discussion by the designer, has become a new intermediary material. However, the virtual model or physical model respectively acts its role that may not be substituted now. TUIS (Tangible User Interfaces) is the intuitional interface system of discussion on striding these two intermediary materials. By the information interchange between the physical model and virtual model, a designer can dedicate to the procedure of design development rather than be restricted to the operation and usage of these interfaces. However, there are many problems existing in applying such a system to the solid geometry model stack. This essay will discuss that a designer explores the incipient design application by manipulating physical model and virtual model.
A Data Adjustment Method of Low-priced Data-glove based on Hand Motion Pattern

A data glove is one of the major interfaces used in the field of virtual reality. In order to get detailed data about the finger joint angles, we must use a data glove with many sensors. However, a data glove with many sensors is expensive and a low-priced data glove does not have enough sensors to capture all the hand data correctly. In our previous work, we propose a method to obtain all finger joint angles by estimating the pattern of hand motion from the low-priced data glove sensor values. In our experiment system, we assumed some representative hand motion patterns as grasping behavior. We also assumed that other hand motions can be represented by synthetic motion of the representative patterns. In our previous work, we used the data glove with sensors covering two joints of each finger. In this paper, we estimate the finger joint angles when using the data glove whose sensors cover only the middle angle of each finger. Keywords–Data-glove; Hand motion estimation; Finger joint angles estimation.
Deep Automatic Licence Plate Recognition system

Automatic License Plate Recognition (ALPR.) has important applications in traffic surveillance. It is a challenging problem especially in countries like in India where the license plates have varying sizes, number of lines, fonts etc. The difficulty is all the more accentuated in traffic videos as the cameras are placed high and most plates appear skewed. This work aims to address ALPR. using Deep CNN methods for real-time traffic videos. We first extract license plate candidates from each frame using edge information and geometrical properties, ensuring high recall. These proposals are fed to a CNN classifier for License Plate detection obtaining high precision. We then use a CNN classifier trained for individual characters along with a spatial transformer network (STN) for character recognition. Our system is evaluated on several traffic videos with vehicles having different license plate formats in terms of tilt, distances, colors, illumination, character size, thickness etc. Results demonstrate robustness to such variations and impressive performance in both the localization and recognition. We also make available the dataset for further research on this topic.