Miracle-dz/UniFAR-FTUs huggingface dataset:
Principle Component Analysis of Function Point Elements

Function point elements are metrics to measure the size of software projects. This article investigates the relationship among function point elements using principle component analysis. Principle component analysis reveals the relationship of different function point elements such that they may be measuring the same attribute of a software project. Therefore, principle component analysis brings out the influence of a function point element over each other. Principle component analysis can help to integrate the function point elements. Function Point elements have attracted much attention in the software research and development industry. Ever since function point were introduced by IBM in 70's their nature, behaviour, impact, distribution and correlation have been studied by the software researchers and the software practitioners. The idea behind function points is to standardize the measurement of the various software functions to estimate the software development effort which is independent of the computer language, development methodology, technology and the capability of the team developed the software. The International Function Point Users Group (IFPUG) was founded in the late 80s and is a membership governed, non-profit organization committed to promoting and supporting function point analysis and other software measurement techniques. There have been various releases of the Function Point by the International Function Point Users Group (IFPUG) which includes release 'Counting Practice Manual - 4.2' release. It is critical to understand the relationship of the function point elements with other components of software projects; for example software quality, software reliability, software defects and testing requirements. Similarly, it is essential to understand the relationship of function point elements with each other. The degree of influence of a function point element over other elements shows that the function point element may be measuring the same attribute of a software project which other function point elements are measuring. Furthermore, based on this relationship, a function point element can be predicted from other function point elements. Previous studies (1-3) discussed the relationships among function point elements. This paper further extends this discussion and use principle component analysis to investigate the relationship of function point elements. The paper is organized in the following way: Section 2 discusses the function point elements, Section 3 describes the dataset used for the principle component analysis, Section 4 presents the principle component analysis of the function point elements and Section 5 draws some conclusions.
SPATIAL ANALYSIS OF ACCIDENTS AT THE SUBURBAN INTERSECTIONS USING KERNEL DENSITY ESTIMATION AND SPATIAL AUTOCORRELATION METHODS

Today, the high number of the rural road accidents has shown that accidents at intersections organize high percentage of the total number of accidents. Meanwhile, the geographical information system (GIS) is considered as an appropriate tool for doing spatial analysis and analysis of accidents at intersections. Also, considering that the accident data are massive and non-homogenized, the methods of spatial autocorrelation and kernel estimation can present connected and more real models than samples of current spots in rural road accidents. The purpose of this research is spatial analysis of rural road accidents based on rural intersection or utilizing spatial autocorrelation methods and estimation of kernel density. In the first stage, it considers appropriate criteria for spatial analysis of accidents in the old roads of Karaj-Qazvin in the 1388-1392 periods and were weighted by use of fuzzy analytic hierarchy process. Then, to identify accident prone intersections and investigation of their characteristics from autocorrelation functions of Getis-Ord Gi*, Anselin Local Moran's I and the kernel density estimation was used in order to investigate the spatial autocorrelation, each of the useable parameters in five successive years used as a Moran's I function. The results have shown that there are 26 accident-prone intersections towards Karaj-Qazvin path and 10 accident-prone intersections for returning, from the total intersections of two way path. Also, for path towards Karaj-Qazvin none of the parameters and for returning path the only parameter of accident type contained spatial autocorrelation in the five successive years.
Improvement of Image Steganography Scheme Based on LSB Value with Two Control Random Parameters and Multi-level Encryption

Recently, steganography has played an important part in the field of communication, especially in image steganography. The major points of image steganography are the image quality (imperceptibility) of the stego image and the security of the system towards stopping the recoverability of the secret data. A new steganography scheme based on two control random parameters and multi-level encryption can address the security challenge while the P_Even/P_Odd classification can ensure the imperceptibility of the stego image. The objectives of study to increase the security and PSNR of the image by using the Huffman coding technique to compress the secret data prior to embedding; this will also ensure an increase in the payload capacity. The proposed scheme takes effect after encrypting and compressing the secret data. It is deployed when matching the secret bits with the LSB during embedding to determine 0 (P_Even) and 1 (P_Odd) while classifying the secret message to track and map each bit in the stego image. The results showed the embedding of the secret message based on P_Even/P_Odd with two control random parameters and multi-level encryption to improve the steganography.
Randomized Algorithm for Virtual Network Mapping Problem Based on Load Balancing

This paper analyzed the existing problems of virtual network mapping(VNM)algorithm based on best-effort service,and pointed out their shortcoming on resource load balancing,and then defined load balancing cost indicator on the physical network,proposed a virtual network mapping randomized algorithm based on load balancing.Experiment shows that the proposed algorithm increases physical network resource load balancing metric and coefficient of utilization,therefore can improve the virtual network construction request acceptance ratio and income profit of physical network service provider.
Comparative profiling of volatile compounds in the grains of rice varieties differing in their aroma

Rice (Oryza sativa L.) is a staple food for more than half of the world’s population. Aromatic rice is highly preferred by most of the rice consumers and the aroma in Pusa Basmati 1 is said to be contributed by the accumulation of 2-acetyl-1-pyrroline (2AP). Our preliminary sensory tests identified that some of the rice genotypes including a traditional genotype of North-Eastern hill regions namely Chakhao Amubiexhibit entirely different aroma. Identifying alternate sources for aroma in rice and understanding its genetic basis will accelerate the development of rice varieties with desirable aroma. This study was aimed at developing a reliable extraction and profiling method for analyzing aromatic compounds in rice. KOH mediated digestion of grain flour followed by trapping of volatile compounds using sample collection tube containing Sorbent: Tenax GR and GC-MS separation of volatiles identified key differences between non-aromatic Improved White Ponni and aromatic Pusa Basmati 1. More than 50 volatile organic compounds (VOCs) were detected. A major aromatic compound 2-acetyl-1-pyrroline (2AP, (C6H9NO)) was detected only in the grains of Pusa basmati 1 but not in Improved White Ponni. Apart from 2AP, several other aromatic hydrocarbons and aldehydes such as hexanal, benzaldehyde, and2-pyrroline were detected in Pusa Basmati 1.Outcomes of this study are identification of several aromatic compounds in rice and also paved way for identifying novel aromatic compounds in rice.
3D Rendering of Magnetic Resonance Images using Visualization Toolkit and Microsoft.NET Framework

In this paper, we proposed new software for 3D rendering of MR images in the medical domain using C# wrapper of Visualization Toolkit (VTK) and Microsoft . NET framework. Our objective in developing this software was to provide medical image segmentation, 3D rendering and visualization of hippocampus for diagnosis of Alzheimer disease patients using DICOM Images. Such three dimensional visualization can play an important role in the diagnosis of Alzheimer disease. Segmented images can be used to reconstruct the 3D volume of the hippocampus, and it can be used for the feature extraction, measure the surface area and volume of hippocampus to assist the diagnosis process. This software has been designed with interactive user interfaces and graphic kernels based on Microsoft.NET framework to get benefited from C# programming techniques, in particular to design pattern and rapid application development nature, a preliminary interactive window is functioning by invoking C#, and the kernel of VTK is simultaneously embedded in to the window, where the graphics resources are then allocated. Representation of visualization is through an interactive window so that the data could be rendered according to user’s preference.
Loss functions for denoising compressed images: a comparative study

This paper faces the problem of denoising compressed images, obtained through a quantization in a known basis. The denoising is formulated as a variational inverse problem regularized by total variation, the emphasis being placed on the data-fidelity term which measures the distance between the noisy observation and the reconstruction. The paper introduces two new loss functions to jointly denoise and dequantize the corrupted image, which fully exploit the knowledge about the compression process, i.e., the transform and the quantization steps. Several numerical experiments demonstrate the effectiveness of the proposed loss functions and compare their performance with two more classical ones.
Efficient method of DOA estimation for coherent signal based on sparse signal reconstruction

We proposed an efficient method of direction of arrival (DOA) estimation for coherent signal based on sparse signal reconstruction. For the inter-atom interference of redundant dictionary affecting the feasibility of sparse signal reconstruction, in this paper, our method for the DOA estimation of coherent signal is based on regularized orthogonal matching pursuit (ROMP) algorithm by designing adaptive sensing dictionary to mitigate the inter-atom interference (AMIAI). Simulated results demonstrate effectiveness of the method by plotting spatial spectrum, by comparing the rootmean-square error (RMSE) of some methods and Cramér-Rao Lower Bound (CRLB) and by comparing the running time of some methods. Our approach makes effort to improve the estimation performance of algorithm and has overload capability.
Cloud Stratus: uma plataforma de middleware para desenvolvimento de aplicações em nuvem

Cloud Computing is a paradigm that enables the access, in a simple and pervasive way, through the network, to shared and configurable computing resources. Such resources can be offered on demand to users in a pay-per-use model. With the advance of this paradigm, a single service offered by a cloud platform might not be enough to meet all the requirements of clients. Ergo, it is needed to compose services provided by different cloud platforms. However, current cloud platforms are not implemented using common standards, each one has its own APIs and development tools, which is a barrier for composing different services. In this context, the Cloud Integrator, a service-oriented middleware platform, provides an environment to facilitate the development and execution of multi-cloud applications. The applications are compositions of services, from different cloud platforms and, represented by abstract workflows. However, Cloud Integrator has some limitations, such as: (i) applications are locally executed; (ii) users cannot specify the application in terms of its inputs and outputs, and; (iii) experienced users cannot directly determine the concrete Web services that will perform the workflow. In order to deal with such limitations, this work proposes Cloud Stratus, a middleware platform that extends Cloud Integrator and offers different ways to specify an application: as an abstract workflow or a complete/partial execution flow. The platform enables the application deployment in cloud virtual machines, so that several users can access it through the Internet. It also supports the access and management of virtual machines in different cloud platforms and provides services monitoring mechanisms and assessment of QoS parameters. Cloud Stratus was validated through a case study that consists of an application that uses different services provided by different cloud platforms. Cloud Stratus was also evaluated through computing experiments that analyze the performance of its processes.
Organisatorische, regulatorische und technische Katalysatoren und Hemmnisse zur Erreichung des intelligenten Energieversorgungssystems – eine empirische Analyse

Ziel des Artikels ist es, die grundlegenden Fakten uber die Wirkungszusammenhange der Technologieadoption aufzuzeigen, die eine erfolgreiche Umsetzung der Vision eines zukunftigen Intelligenten Energieversorgungssystems ermoglichen konnen. Von besonderem Interesse hierbei ist die Frage, ob das Technology-Organization-Environment Framework ein dafur geeignetes Model ist. In diesem Zusammenhang wird untersucht, welche Rolle regulatorische, organisationale und technische Faktoren spielen und ob und in welchem Ausmas diese moglicherweise eine hemmende bzw. fordernde Wirkung haben. Um diese Fragen zu beantworten, wurde eine empirische Untersuchung durchgefuhrt, an der sich uber 180 Netzbetreiber in Deutschland beteiligt haben.
Property Oriented Relational-To-Graph Database Conversion

Analysis of data stored in a graph enables the discovery of certain information that could be hard to see if the data were stored using some other model (e.g. relational). However, the vast majority of data in information systems today is stored in relational databases, which dominate the data management field over the last decades. In spite of the rise of NoSQL technologies, the development of new information systems is still mostly based on relational databases. Given the increasing awareness about the benefits of data analysis as well as current research interest in graph mining techniques, we aim to enable the usage of those techniques on relational data. In that regard, we propose a universal relational-to-graph data conversion algorithm which can be used in preparation of data to perform a graph mining analysis. Our approach leverages the property graph model which is mainly used by the graph databases, while maintaining the level of relational data clarity.
Dynamic Analyses for Understanding and Optimization of Enterprise Java Applications

Enterprise Java (J2EE) applications present significant challenges for horizontal scaling due to their large code and dataset sizes, as well as the clustering models of application servers. Our work targets a potential reimplementation of the way Enterprise Java applications are clustered. We propose three dynamic analyses, motivated by a new design for a clustered enterprise application framework, which allow better understanding of existing applications and provide support for migrating such applications to a possible future implementation of this design. The first dynamic analysis traces the flow of primary keys, which uniquely identify certain objects within the business tier of a J2EE application. It identifies the entry points of such data to the business tier, which provides crucial information for the migration of the application towards the new clustered design. We propose an algorithm to achieve this identification and implement the approach through bytecode instrumentation. Our experimental results indicate that the analysis has practical overhead and achieves excellent precision. The second dynamic analysis identifies the entry points of query parameters to the business tier of a J2EE application, as well as certain relationships in which this data participates. This is achieved through a number of enhancements to the algorithm for the first dynamic analysis. The analysis implementation exhibits reasonable overhead and achieves high-precision identification of the entry points of
Analysis of Biased Competition and Cooperation for Attention in the Cerebral Cortex

A new approach to understanding the interaction between cortical areas is provided by a mathematical analysis of biased competition, which describes many interactions between cortical areas, including those involved in top-down attention. The analysis helps to elucidate the principles of operation of such cortical systems, and in particular the parameter values within which biased competition operates. The analytic results are supported by simulations that illustrate the operation of the system with parameters selected from the analysis. The findings provide a detailed mathematical analysis of the operation of these neural systems with nodes connected by feedforward (bottom-up) and feedback (top-down) connections. The analysis provides the critical value of the top-down attentional bias that enables biased competition to operate for a range of input values to the network, and derives this as a function of all the parameters in the model. The critical value of the top-down bias depends linearly on the value of the other inputs, but the coefficients in the function reveal non-linear relations between the remaining parameters. The results provide reasons why the backprojections should not be very much weaker than the forward connections between two cortical areas. The major advantage of the analytical approach is that it discloses relations between all the parameters of the model.
Integration Testing Approach using Usage Patterns of Global Variables

Global variables can be read or modified by any part of the program, making it difficult to remember or reason about every possible use. Sometime it has tight couplings between some of other variables, and couplings between variables and functions. The main focus of this paper is to use call graph and the control flow analysis to design a model from where we generate the test cases for testing global variables.
DIGESTIBLE LYSINE LEVELS FOR GROWER PHASE BROWN EGG LAYERS

The objective was to determine the level of digestible lysine in the grower diet of brown egg layers at two weight categories, and assess the residual effect of the grower diet on the laying phase. A total of 400 13-week-old brown egg layers were used, in a randomized blocks design with a 2 x 4 factorial arrangement (two weight categories x four digestible lysine levels: 5.29, 6.29, 7.29 and 8.29 g/kg), with five replications and 10 birds per experimental unit. A metabolism assay was carried out during the 17th week of age. Body weight, feed intake, feed conversion and weight gain were evaluated between 23 and 35 weeks; and egg quality was assessed during three 28-day periods. Data were subjected to analysis of variance and polynomial regression. No link was found between layer weight categories and lysine levels in grower diet for all studied variables. Nitrogen balance increased as digestible lysine was added to diets. There was no effect of digestible lysine on weight gain and precocity of production. Birds in the standard weight category were more precocious and had higher egg production and weight during the laying phase. Digestible lysine levels in diet did not influence performance and egg quality during the laying phase. A level of 5.2 g/kg of digestible lysine is recommended in grower diet (13 to 20 weeks of age) for brown egg layers, which corresponds to an intake of 550 mg/bird/day.
3D visual-inertial odometry and autonomous mobile robot exploration with learned map prediction

2D and 3D scene reconstruction are important topics in the field of robotics and computer vision. Mobile robots require a model of the environment to perform navigational tasks, and model acquisition is a useful application in itself . This thesis presents a) A 3D odometry and mapping system producing metric scale map and pose estimates using a minimal sensor-suite b) An autonomous ground robot for 2D mapping of an unknown environment using learned map prediction. The first application proposes a direct visual-inertial odometry method working with a monocular camera. This system builds upon the state-of-the-art in direct vision-only odometry. It demonstrates superior system robustness and camera tracking accuracy compared to the original method. Furthermore, the system is able to produce a 3D map in metric scale, addressing the well known scale ambiguity inherent in monocular SLAM systems. The second application demonstrates an autonomous ground robot capable of exploring unknown indoor environments for reconstructing their 2D maps. This method combines the strengths of traditional information-theoretic approaches towards solving this problem and more recent deep learning techniques. Specifically, it employs a state-of-the-art generative neural network to predict unknown regions of a partially explored map, and uses the prediction to enhance the exploration in an information-theoretic manner. The system is evaluated against traditional methods in simulation using floor plans of real buildings and demonstrates advantage in terms of exploration efficiency. We retain an advantage over end-to-end learned exploration methods in that the robot’s behavior is easily explicable in terms of the predicted map.
The Effect of the Second Language on the First Language The Dual Language Approach

ريثأتلا ةعيبط فصيو ،ملأا ةغللا يـف ةيناثلا ةغللا ريثأتل رهاظم ثحبلا اذــه مدقي :صــخــلــم ةغللا يف ةيناثلا ةغللا ريثأت نأ ثحبلا رهظأ دقو . ةلثمأب كلذ ىلع لِّ لديو ،نيتغللا نيب لدابتملا نيبناجلا يف حُضوأ ةيناثلا ةغللا ريثأتف ؛ةيناثلا ةغللا يف ملأا ةغللا ريثأت نع ارًهاظ فلتخم ملأا رمثملا رـيـثأـتـلا نأ ثـحـبـلا رــهــظأو . يـمـجـعـمـلاو يبيكرتلا نيبناجلا يــف هـنـم يــلوادــتــلاو يّـــــكاردلإا ،كــلذ عــم . ةرورــــض ســيــلو مــئاــق لاـمـتـحا وــه ىــــلولأا ةـغـلـلا تاـياـفـك وـمـن يــف ةـيـناـثـلا ةـغـلـلا ملعتل ةيناثلا ةغللا ةـساردـف ؛ةددعتملا ةيافكلا ققحت ىــلإ يدؤــت ةيناثلا تاغللا م ُّ لعت عاوـــنأ لـك تسيل ،ىوـتـحـمـلا ةـــيّرـــثو ةفثكم باــســتــكلاا ةيلمع تــناــك اذإ ةـغـلــلا يداــــحأ ماــظــن يــف تارـيـيـغـت ثدِـــحْـــتُ . ملعتملا عفاودب ةلصتمو
Self-organization in parcel distribution - SOLiD's first results

Abstract: To bridge the gap between the long(er) term Physical Internet vision and the short term daily logistics operations, the Dutch Topsector Logistics (TKI Dinalog and NWO) requested a research project that would provide an impulse for self-organizing logistics. This contribution discusses the development of the research project SOLiD, Self-Organizing Logistics in Distribution, that answers to that request. First of all, we describe the design and developments of SOLiD by discussing the challenges in the parcel industry and how these could benefit from implementing solutions that relate to a more self-organizing logistics system. Next, the first results of SOLiD’s experiments are presented. The experiments under consideration focus on dynamic planning and adding local intelligence to reduce handling activities. Lastly, we describe how autonomous sorting robots can be a means to achieve a more self-organizing logistics system. This paper provides new insights with respect to the considerations of designing, and the execution of practical experiments for implementing SOL as a step towards realizing the Physical Internet and make it more concrete for logistics industry.