Miracle-dz/UniFAR-FTUs huggingface dataset:
Design Pattern Detection and Software Architecture Reconstruction: an Integrated Approach based on Software Micro-structures

In this chapter we present some of the main works related to the activities of design pattern detection and software architecture reconstruction, giving also an overview of the major types of approaches. 2.1. Related works on design pattern detection Many different approaches and tools for design pattern detection (DPD) have been presented in the literature. The approaches differ in the kind of analysis pursued on the subject systems, in the algorithms adopted for pattern detection, in the set of patterns they are able to recognize, and in the analysis results, which may differ from one tool to another even while considering the same subject system. Section 2.1. 1 considers and discusses different possible approaches and methodologies for DPD, while in Section 2.1. 2 we introduce some of the major approaches and tools reported in the literature, giving an organic overview of them. 2.1. 1. Categorizations of approaches and methodologies for design pattern detection The detection of design patterns in software systems requires the extraction of meaningful information from these systems and the recognition of patterns starting from this information. Various classifications for design pattern detection solutions and approaches have been presented in the literature, considering various points of view. One major classification consists in categorizing design pattern detection approaches as static, dynamic
Hyperspectral Data Acquisition and Its Application for Face Recognition

Current face recognition systems are rife with serious challenges in uncontrolled conditions: e.g., unrestrained lighting, pose variations, accessories, etc. Hyperspectral imaging (HI) is typically employed to counter many of those challenges, by incorporating the spectral information within different bands. Although numerous methods based on hyperspectral imaging have been developed for face recognition with promising results, three fundamental challenges remain: 1) low signal to noise ratios and low intensity values in the bands of the hyperspectral image specifically near blue bands; 2) high dimensionality of hyperspectral data; and 3) inter-band misalignment (IBM) correlated with subject motion during data acquisition. This dissertation concentrates mainly on addressing the aforementioned challenges in HI. First, to address low quality of the bands of the hyperspectral image, we utilize a custom light source that has more radiant power at shorter wavelengths and properly adjust camera exposure time corresponding to lower transmittance of the filter and lower radiant power of our light source. Second, the high dimensionality of spectral data imposes limitations on numerical analysis. As such, there is an emerging demand for robust data compression techniques with loss of less relevant information to manage real spectral data. To cope with these challenging problems, we describe a reduced-order data modeling technique based on local proper orthogonal decomposition in order to compute low-dimensional models by projecting highdimensional clusters onto subspaces spanned by local reduced-order bases. Third, we investigate 11 leading alignment approaches to address IBM correlated with subject motion during data acquisition. To overcome the limitations of the considered alignment approaches, we propose an accurate alignment approach (A3) by incorporating the strengths of point correspondence and a low-rank model. In addition, we develop two qualitative prediction models to assess the alignment quality of hyperspectral images in determining improved alignment among the conducted alignment approaches. Finally, we show that the proposed alignment approach leads to promising improvement on face recognition performance of a probabilistic linear discriminant analysis approach.
Scheduling jobs to consider physiological factors

We studied scheduling jobs and breaks for a single worker. The processing time of jobs increases as the worker tires. In this study, we assume that conventional machine scheduling models do not always work for humans. So, while determining the break time, we consider the workers' physiological factors. The two objectives considered are the total flow time and makespan. An exact mathematical model and heuristic algorithm are developed to solve large problems. Numerical examples are presented for understanding and analyzing the performance of the mathematical model and the heuristic. © 2011 Wiley Periodicals, Inc.
Symbol rate and modulation level-controlled adaptive modulation/TDMA/TDD system for high-bit-rate wireless data transmission

This paper proposes a time-division multiple-access/time-division duplex (TDMA/TDD)-based symbol rate and modulation level-controlled adaptive modulation system for high-bit-rate data transmission. The proposed system controls both the symbol rate and modulation level for the next transmission time slot according to the estimated carrier power to noise spectral density ratio (C/N/sub 0/) and delay spread for the time slot to achieve higher bit rate and higher transmission quality as well as higher delay-spread immunity. It is demonstrated by computer simulation and laboratory experiments that the proposed system can achieve a higher average bit rate with higher transmission quality in comparison with the fixed-rate quaternary phase-shift keying (QPSK) system and modulation level-controlled adaptive modulation system in both flat Rayleigh and frequency-selective fading environments. The simulated and experimental results also show that the proposed adaptive modulation techniques can be applied to 1-2-Mb/s indoor and outdoor microcellular systems with its delay spread of up to 250 ns and its terminal mobility of up to pedestrian speed without employing any special antifrequency-selective fading techniques, such as the adaptive equalizer and space diversity.
SOCIOPART:Hopping Based Partitions

Online social networking has become a phenomenon in the last few years. The growing usage of social networks has put the vendors under a lot of pressure to efficiently process the users queries. In social networks like orkut, most of the queries access the immediate neighbors of the current node and neighbors of its neighbors. Existing graph partitioning approaches focus on reducing the number of inter server links, neglecting the query patterns. Our algorithm focuses on partitioning the graph so as to minimize the number of servers to be accessed in order to process a query. Our results show that the proposed algorithm gives useful partitioning of social networks, thereby reducing inter server accesses.
Improved option pricing using bootstrap methods

A "hybrid" neural network is used to predict the difference between the conventionally accepted modified Black option pricing model and observed intraday option prices for stock index option futures. Confidence intervals derived with bootstrap methods are used in a trading strategy which allows only trades outside the estimated range of spurious model fits to be executed. Furthermore, "hybrid" neural network option pricing models can improve predictions but have bias which can be reduced with bootstrap methods. A modified bootstrap predictor is indexed by a parameter which allows the predictor to range from a pure bootstrap predictor, to a hybrid predictor, and finally the bagging predictor. Our results show that a modified bootstrap predictor outperforms the hybrid and bagging predictors. Greatly improved performance was observed in particular regions of the input space, namely out of the money options.
Use of mixed radix FFT in electric power system studies

Radix-2 based fast Fourier transform (FFT) routines have been the main stream FFT that are commonly applied to the measurement and analysis of electric power system data. Because of the rigid sampling rates offered by most of the instrument manufacturers and the mathematical limitation imposed by the algorithm of radix-2 FFT, artificial post sampling data windows have been introduced to improve the utility of the radix-2 FFT. The 60 Hz and the 50 Hz based electrical power system frequencies are incompatible with the radix-2 FFT. There has been an ongoing search to adapt the FFT routine to the special requirements of electric power systems. Advances in the personal computer hardware has opened a new approach to perform the FFT via mixed radix routines. It offers greatly improved flexibility in the selection of a practical data size. This leads to the elimination of the need of the post sampling software windows. It also allows one to relax or eliminate the requirement of anti-aliasing measures for power system harmonic measurements. >
COMPARATIVE STUDY OF THE METHODS USING HAAR-LIKE FEATURES

Object detection is a topic which takes a great extent in the field of computer vision. Is the first step in many visual processing systems like face recognition, encoding recognition and lip reading. The detection of an object passes through three stages: The first is the extraction of information that characterize the object, the second is the processing of this information and the last step is to construct the final detector. We will focus on the first stage. Various approaches have been utilized such as Haar-Like features, color information, texture, edge orientation, etc. While numerous methods have been proposed to extract information using Haar-like feature, we are unaware of any surveys on this particular topic. For this reason this paper present a comparative study of different research on HaarLike features.
DAMAGE DETECTION FOR UHPFRC COMMUNICATION TOWER BASED ON FREQUENCY DATA AND PARTICLE SWARM OPTIMIZATION

Advances in the telecommunication and broadcasting sectors have increased the need for networking equipment of communication towers. Slender structures, such as towers, are sensitive to dynamic loads, such as vibration forces. Therefore, the stability and reliability performance of towers can be maintained effectively through the prompt detection, localization, and quantification of structural damages by obtaining the dynamic frequency response of towers. However, frequency analysis for damaged structures requires long computational procedures and is difficult to perform because of the damages in real structures, particularly in towers. Therefore, this study proposed a correlation factor that can identify the relationship between frequenciesunderhealthy and damaged conditions of ultra high performance fiber-reinforced concrete (UHPFRC) communication towers using particle swarm optimization. The finite element method was implemented to simulate three UHPFRC communication towers, and an experimental test was conducted to validate and verify the developed correlation factor
The formation of nitro-aromatic compounds under high NOx and anthropogenic VOC conditions in urban Beijing, China

Abstract. Nitro-aromatic compounds (NACs), as important contributors to the light absorption by brown carbon, have been widely observed in various ambient atmospheres; however, their formation in the urban atmosphere was little studied. In this work, we report an intensive field study of NACs in summer 2016 at an urban Beijing site, characterized by both high-NOx and anthropogenic VOC dominated conditions. We investigated the factors that influence NAC formation (e.g., NO2, VOC precursors, RH and photolysis) through quantification of eight NACs, along with major components in fine particulate matter, selected volatile organic compounds, and gases. The average total concentration of the quantified NACs was 6.63 ng m−3, higher than those reported in other summertime studies (0.14–6.44 ng m−3). 4-Nitrophenol (4NP, 32.4 %) and 4-nitrocatechol (4NC, 28.5 %) were the top two most abundant NACs, followed by methyl-nitrocatechol (MNC), methyl-nitrophenol (MNP), and dimethyl-nitrophenol (DMNP). The oxidation of toluene and benzene in the presence of NOx was found to be a more dominant source of NACs than primary biomass burning emissions. The NO2 concentration level was found to be an important factor influencing the secondary formation of NACs. A transition from low- to high-NOx regimes coincided with a shift from organic- to inorganic-dominated oxidation products. The transition thresholds were NO2 ∼ 20 ppb for daytime and NO2∼25 ppb for nighttime conditions. Under low-NOx conditions, NACs increased with NO2, while the NO3- concentrations and (NO3-)/NACs ratios were lower, implying organic-dominated products. Under high-NOx conditions, NAC concentrations did not further increase with NO2, while the NO3- concentrations and (NO3-)/NACs ratios showed increasing trends, signaling a shift from organic- to inorganic-dominated products. Nighttime enhancements were observed for 3M4NC and 4M5NC, while daytime enhancements were noted for 4NP, 2M4NP, and DMNP, indicating different formation pathways for these two groups of NACs. Our analysis suggested that the aqueous-phase oxidation was likely the major formation pathway of 4M5NC and 3M5NC, while photo-oxidation of toluene and benzene in the presence of NO2 could be more important for the formation of nitrophenol and its derivatives. Using the (3M4NC+4M5NC) ∕ 4NP ratios as an indicator of the relative contribution of aqueous-phase and gas-phase oxidation pathways to NAC formation, we observed that the relative contribution of aqueous-phase pathways increased at elevated ambient RH and remained constant at RH > 30 %. We also found that the concentrations of VOC precursors (e.g., toluene and benzene) and aerosol surface area acted as important factors in promoting NAC formation, and photolysis as an important loss pathway for nitrophenols.
A scalable flexible and dynamic reconfigurable architecture for high performance embedded computing. (Une architecture évolutive flexible et reconfigurable dynamiquement pour les systèmes embarqués haute performance)

Dans cette these, nous proposons une architecture reconfigurable scalable et flexible, avec un reseau de communication parallele « full-duplex switched » ainsi que le modele d’execution approprie ce qui nous a permis de redefinir les paradigmes de calcul, de communication et de reconfiguration dans les systemes embarques a haute performance (HPEC). Ces systemes sont devenus tres sophistiques et consommant des ressources pour trois raisons. Premierement, ils doivent capturer et traiter des donnees en temps reel a partir de plusieurs sources d’E/S paralleles. Deuxiemement, ils devraient adapter leurs fonctionnalites selon l’application ou l’environnement. Troisiemement, a cause du parallelisme potentiel des applications, multiples instances de calcul reparties sur plusieurs nœuds sont necessaires, ce qui rend ces systemes massivement paralleles. Grace au parallelisme materiel offert par les FPGAs, la logique d’une fonction peut etre reproduite plusieurs fois pour traiter des E/S paralleles, faisant du modele d’execution « Single Program Multiple Data » (SPMD) un modele prefere pour les concepteurs d’architectures paralleles sur FPGA. En plus, la fonctionnalite de reconfiguration dynamique est un autre attrait des composants FPGA permettant la reutilisation efficace des ressources materielles limitees. Le defi avec les systemes HPEC actuels est qu’ils sont generalement concus pour repondre a des besoins specifiques d’une application engendrant l’obsolescence rapide du materiel. Dans cette these, nous proposons une architecture qui permet la personnalisation des nœuds de calcul (FPGA), la diffusion des donnees (E/S, bitstreams) et la reconfiguration de plusieurs nœuds de calcul en parallele. L’environnement logiciel exploite les attraits du reseau de communication pour implementer le modele d’execution SPMD.Enfin, afin de demontrer les avantages de notre architecture, nous avons mis en place une application d’encodage H.264 securise distribue evolutif avec plusieurs protocoles de communication avioniques pour les donnees et le controle. Nous avons utilise le protocole « serial Front Panel Data Port (sFPDP) » d’acquisition de donnees a haute vitesse base sur le standard FMC pour capturer, encoder et de crypter le flux video. Le systeme mis en œuvre s’appuie sur 3 FPGA differents, en respectant le modele d’execution SPMD. En outre, nous avons egalement mis en place un systeme d’E/S modulaire en echangeant des protocoles dynamiquement selon les besoins du systeme. Nous avons ainsi concu une architecture evolutive et flexible et un modele d’execution parallele afin de gerer plusieurs sources video d’entree paralleles.
Design and analysis of modified Rotman type multiple beam forming lens

A modified approach to design Rotman (1963) type multiple beam forming lens has been proposed. The path length error at the wavefront has been calculated. The error obtained by the proposed approach and by the conventional approach has been compared. Two-dimensional electromagnetic field analysis of the lens obtained by the modified approach and by the conventional approach lens has been carried out using the contour integral method. The results obtained for both the lenses have been compared.
A 1.5-ns 32-b CMOS ALU in double pass-transistor logic

Describes circuit techniques for fabricating a high-speed adder using pass-transistor logic. Double pass-transistor logic (DPL) is shown to improve circuit performance at reduced supply voltage. Its symmetrical arrangement and double-transmission characteristics improve the gate speed without increasing the input capacitance. A carry propagation circuit technique called conditional carry selection (CCS) is shown to resolve the problem of series-connected pass transistors in the carry propagation path. By combining these techniques, the addition time of a 32-b ALU can be reduced by 30% from that of an ordinary CMOS ALU. A 32-b ALU test chip is fabricated in 0.25- mu m CMOS technology using these circuit techniques and is capable of an addition time of 1.5 ns at a supply voltage of 2.5 V. >
On The Link Between Mobile App Quality And User Reviews

Mobile app stores contain millions of apps which users can download and install on their smart phones. Each app has a page in the mobile app store that includes app’s description, a download link for the app, and a space for users to review the app. Each review has a 1-5 star rating and a review-comment. Unlike desktop and server side-software where direct user feedback about software quality was difficult to acquire, app developers now have access to the user’s perspective of their apps via the reviews. Since apps with high-rating reviews are downloaded statistically significantly more than apps with low-rating reviews, the insights from studying these reviews are very important. Thus in this thesis, we analyze hundreds of thousands of reviews of Android and iOS apps to help developers understand the relationship between app quality, and the feedback in reviews. In this thesis, we find that low-rated reviews of apps contain 12 different complaint types which have varying impact and frequencies. The most frequent complaints are about functional errors, feature requests, and app crashes; complaints about privacy, ethical and hidden cost issues receive the worst star ratings. For Android developers struggling with device fragmentation, we find that different Android devices give varying star ratings. However, we show that device info from reviews can also be used to identify a subset of Android devices that should be prioritized for testing.
On ontologies for high-level information fusion

It is now commonly accepted that on- tologies will facilitate the information fusion activity. However, it is not clear what should be the exact form of this facilitation process. It is relatively well under- stood what information fusion is; the question of what ontologies are has also been extensively mplored. How- ever, it is not clear what ontology-based information fusion is. This paper indicates crucial aspects of on- tologies, and attempts to provide some links between ontologies and infomation fusion.
Speech recognition techniques using RBF networks

This paper presents a pattern recognition approach, based on whole word patterns, to speaker independent automatic speech recognition of isolated digits. We use the decomposition of the spoken word into subacoustic words to ensure time alignment of the significant portions of the input's acoustic characteristics and those of the reference patterns. The Isodata clustering algorithm is used by the radial basis function (RBF) network to create reference templates and classification of the speech samples.
Color Image Enhancement using Edge Based Histogram Equalization

Image enhancement is one of the major research areas in the field of digital image processing. The sole objective of this domain is to enhance the quality of a poor contrast image. As a result, the final processed image becomes much more understandable than the original one. A new edge based histogram equalization method is proposed in this study. A high pass filter is used to detect edges with a help of an appropriate gradient operator. In general, a convolution mask is used for this kind of area processes like filtering. This proposed method increases the quality of the poor contrast area. This method does not create an impact on brighter area in the given input image. A few portion of the poor contrast is raised and few others contrast are being reduced. The simulation results of this study are compared with the conventional histogram equalization. Our experimental results show that the Peak Signal-to-Noise Ratio (PSNR) is better than the regular Histogram Equalization (HE) method. All simulation results are obtained using Matlab simulation software tool with standard color test images. Color image enhancement methods are applicable in the areas such as iris recognition, digital photography, remote sensing, biology, medicine, geophysics and microarray techniques, etc.
Identifying Fake News and Tweets using Anomaly Detection

The wide use of social media has tremendous impact on culture, business, and politics on the world at large with potentially positive and negative effects. For example, social media coverage of crisis events may be used by authorities for effective disaster management or by malicious entities to spread rumors and fake news for financial or political benefit. Considering the harmful consequences of fake news in social media, there is a profound need to detect false information, control and/or prevent it from spreading. In this paper, we propose an advanced framework to identify tweets with fake news contents using techniques including statistical analysis of Twitter user account, cross verification of fake news sources, and data mining. Experimental results on a large miscellaneous events dataset demonstrate the effectiveness of our proposed approach in identifying fake tweets.
SOFTWARE ARCHITECTURE RECOVERY WITH ERROR TOLERANCE AND PENALTY COST IN GRAPH MINING

In the vast literature Software architecture has been recovered through graphs. During Software Architecture recovery generally matching will takes place between Source graph and Query graph. Graph matching is one of the phase in which we will find the same sub graph which is present in source graph and query graph. In most of the papers, it was stated that graph matching is complete. But in reality matching between the graphs is not appropriately complete. We call this an error in matching. In this paper we investigate the applicability of error correcting graph matching algorithm, Graph Isomorphism by Decision Tree to compensate the Software Architecture Recovery.