Miracle-dz/UniFAR-FTUs huggingface dataset:
Can automated program repair refine fault localization? a unified debugging approach

A large body of research efforts have been dedicated to automated software debugging, including both automated fault localization and program repair. However, existing fault localization techniques have limited effectiveness on real-world software systems while even the most advanced program repair techniques can only fix a small ratio of real-world bugs. Although fault localization and program repair are inherently connected, their only existing connection in the literature is that program repair techniques usually use off-the-shelf fault localization techniques (e.g., Ochiai) to determine the potential candidate statements/elements for patching. In this work, we propose the unified debugging approach to unify the two areas in the other direction for the first time, i.e., can program repair in turn help with fault localization? In this way, we not only open a new dimension for more powerful fault localization, but also extend the application scope of program repair to all possible bugs (not only the bugs that can be directly automatically fixed). We have designed ProFL to leverage patch-execution results (from program repair) as the feedback information for fault localization. The experimental results on the widely used Defects4J benchmark show that the basic ProFL can already at least localize 37.61% more bugs within Top-1 than state-of-the-art spectrum and mutation based fault localization. Furthermore, ProFL can boost state-of-the-art fault localization via both unsupervised and supervised learning. Meanwhile, we have demonstrated ProFL's effectiveness under different settings and through a case study within Alipay, a popular online payment system with over 1 billion global users.
SURF DESCRIPTOR BASED OPTIMIZED FACE DETECTION USING BOOSTED SVM CASCADE AND SKIN COLOR FILTERING

-An enhanced and optimized face detection system robust to variations in pose and illumination, along with minimum false positive rate has been proposed in this paper. SURF descriptors are used as feature vectors and SVM is used as the base classifier. A number of SVMs are trained using a boosting algorithm and stored as an ensemble of weighted SVMs. A cascade of different stages is built to make the final strong classifier. Optimization is a main criterion in designing this system, as far as false positive rate and processing time are concerned. These two features are achieved by a skin color filtering module integrated to the proposed face detection system, which outputs a skin-color segmented binary image. The current detection window is processed only if there are enough skin color pixels in that window. Further, the detection window is classified using boosted SVM cascade classifier. Typical post processing operations completes the face detection procedure. Testing on FDDB benchmark dataset shows that the proposed system outperforms classic boosted cascade face detection methods on ROC curve evaluation and state-of-the-art detectors on comparison based on detection rate.
THE ROLE OF ORIENTED GESTURES DURING ROBOT’S COMMUNICATION TO A HUMAN 1

The role of oriented gestures is crucial while solving spatial problems. We analyze the influence of a robot, using oriented gestures, on a human. In an experimental situation robot F-2 was helping a human to solve a “tan-gram” puzzle. Robot was indicating in speech, which game element to take and where to place it. In a half of the tasks the robot was using oriented communicative actions (hand gestures, head movements and gaze) to indicate the required game element, and then—the game position to place it in. In the other half of tasks, the robot was using non-oriented gestures. We show, that the use of oriented gestures increases the attractiveness of a robot to human and rises the general satisfaction of the interaction with the robot.
METHIONINE‐ACTIVATING ENZYME IN STARFISH FOLLICLE CELLS *

In starfish follicle cells 1‐methyladenine is produced under the influence of a gonad‐stimulating hormonal peptide (GSS). Since such production of the substance is enhanced by the addition of L‐methionine or S‐adenosylmethionine in vitro, the presence of methionine‐activating enzyme in the follicle cells of the starfish, Asterina pectinifera, was investigated. To detect enzyme activity, the enzyme was partially purified from the supernatant of the follicle‐cell homogenate by precipitation with ammonium sulfate followed by gel‐filtration on a Sephadex G‐150 column. Using such a preparation of the enzyme, the production of S‐adenosylmethionine from L‐methionine and adenosine triphosphate was clearly demonstrated by thin‐layer chromatography. GSS was found to exert no effect on the activity of the methionine‐activating enzyme. The hormonal peptide, GSS, is therefore considered to take part in some reaction other than this step in the formation of 1‐methyladenine.
EVALUATION OF FEATURES FOR VOICE ACTIVITY DETECTION USING DEEP NEURAL NETWORK

Voice activity detection (VAD) is implemented in the preprocessing stage of various speech applications to identify speech and non-speech periods. Recently, deep neural networks (DNNs) have been utilized for VAD given their superior performance over other methods. When used to identify speech and non-speech periods, DNNs depend on the input of different features to discriminate speech from noise. Hence, different features have been used as input for DNN-based VAD. However, the contribution and effectiveness of such features have not been thoroughly evaluated. In this paper, we address these aspects by comparing five features, namely, log power spectra, filter bank, mel-frequency cepstral coefficients, relative spectral perceptual linear predictive analysis, and amplitude modulation spectrogram, which are widely used on speech processing, to evaluate their performance in a DNN-based VAD. Experiments on the TIMIT speech corpus show that the amplitude modulation spectrogram is the feature with the best performance given its high accuracy even when processing speech data with low signal-to-noise ratio. The next feature showing high performance is log power spectra, which can be considered as a raw feature because it does not require as many calculations or processing as the other features. This suggests that raw features may be suitable inputs for DNN-based VAD. Moreover, limiting the number and processing of features for DNNs may foster system performance, real-time application, and portability of VAD by reducing the computational cost, required memory and storage.
Critical Review of Research Paper for Analysis of Multi Leaf Spring

The aim of this review paper is to represent a general study on the design, analysis of multi leaf spring. In passenger vehicles ride comfort and load carrying capacity, rigidity is important considerations. Vehicle ride comfort depends upon the suspension system. Suspension system in automobile significantly affects the behavior of vehicle. Leaf springs are perhaps the simplest and are less expensive compared to other suspension. Leaf spring is therefore an important aspect in the suspension system design. Due to variation of load leaf springs are one of the most dynamically stressed components in automobile therefore quality of vehicle ride depends upon the characteristics of leaf spring used in suspension unit, Performance measures of any leaf springs are its stiffness and fatigue life. This paper present analysis of leaf spring used in light commercial vehicle.
THE RELATIONSHIP BETWEEN SELF-CONCEPTS AND FLAMING BEHAVIOR: POLARITY OF THE ONLINE COMMENTS

This study aims to explore how the sub-factors of self-concepts such as self-identity and self-monitoring are associated with flaming behavior, demonstrate whether polarity of online comments plays the moderating variable and show how flaming behavior affects corporate brands and product purchases. The study was conducted in groups of approximately 1060 subjects. Self-monitoring, self-identity and selfcontrol had a strongly associated with flaming behavior. Therefore, when writing online comments on the internet, self-monitoring, self-identity and self-control seem to play an important role when explain internet users’ flaming behavior in cyberspace. Users with strong self-concepts tended to respond sensitively with comments when looking at online comments than did users with lower self-concepts. In spite of the fact that flaming behavior has been the chief obstacle to internet culture; however, it is true that there has still been a lack of academic interest in flaming. Therefore, this study is significant in arousing academic interest in flaming.
PREDICTING DEPRESSION FROM ESSAYS IN RUSSIAN

The study is focused on the detection of depression by processing and classification of short essays written by 316 volunteers. The set of 93 essays was provided by two different teams of psychologists who asked patients with clinically confirmed depression to write short essays on the neutral topic. The other 223 essays on the same topic were written by volunteers who completed questionnaires, which are designed to reveal depression status and did not demonstrate any signs of mental illnesses. The study describes psycholinguistic and classic text features which were calculated by utilizing natural language processing tools and were used to perform on the classification task. The machine learning classification models achieved up to 73% of f1-score for the task of revealing essays written by people with depression
SURVEILLANCE VIDEO ANALYSIS USING DEEP LEARNING TECHNIQUES FOR TRAFFIC AND CROWD MANAGEMENT

-In this digital age, the availability of massive amounts of video data have been exploited by deep learning techniques to gain useful insights. Applying deep learning algorithms on surveillance video data can help in the areas of traffic and crowd management. The model proposed for achieving these objectives is Single Shot MultiBox Detector (SSD) with a line of counting approach to count the objects of interest from a surveillance video. The proposed model has been used for analyzing traffic surveillance videos for counting of vehicles on different lanes and make intelligent traffic decisions to prioritize traffic signals based on the traffic densities. As a subcase of traffic management, a Tesseract OCR model is run on surveillance videos to capture the license plate of vehicles violating any traffic regulations. Another use case proposed in this paper involves studying and analyzing the crowd statistics from publicly accessible surveillance video cameras, to handle crowd management in cases of emergencies and huge public gatherings for safety and security. The need for accuracy along with robustness makes deep learning a suitable choice for the use cases enlisted.
Estimating Dependence Among Lumber Strength Properties With Copula Models

A copula-based approach is used to estimate the dependence among three lumber strength properties: modulus of elasticity (MOE), modulus of rupture (MOR), and ultimate tensile strength (UTS). MOR and UTS are destructive measurements so they cannot be obtained simultaneously for lumber specimens. The dependence modeling is possible under an appropriate experimental design with i) a shoulder group for rupture, ii) a shoulder group for tension, and iii) other groups proof loaded in either the rupture or tension mode with survivors tested to failure in the mode that was not initially tested. With a fitted copula model based on an assumption of no damage due to the proof loading procedure, we conclude that there is a strong dependence between MOR and UTS conditioning on MOE. To assess the “no damage assumption,” a graphical method with simulated data from the fitted copula model is used. It suggests that there may be some damage to the lumber specimens due to proof loading, especially for weaker lumber specimens. Information from the dependence model can potentially help reduce monitoring costs in the lumber industry.
PEDAL POWERED WATER PURIFICATION-A Survey

1Asst. Professor, Dept. of Mechanical Engineering, PVP Siddhartha Institute of Technology Kanuru, Vijayawada, AP. INDIA 2,3,4,5UG Student , Dept. of Mechanical Engineering, PVP Siddhartha Institute of Technology, Kanuru, Vijayawada, AP. INDIA ---------------------------------------------------------------------***---------------------------------------------------------------------Abstract An Most of the earth is covered by Water, but it needs to be purified before it can be consumed. Generally water purification needs electricity or fuel along with large systems making purified water more costly. But there are several water purification methods which needs no electricity with less cost. One of the purification method is pedal powered water purification (PPWF). In this purification process mainly basic Bernoulli's principle is used which states that an increase in the speed of a fluid occurs simultaneously with a decrease in pressure or a decrease in the fluid's potential energy. Many people worked on this type of water purification system and came up with different designs. So here we are reviewing different pedal powered water purification (PPWF) methods proposed by several authors.
The consequences of the variance-mean rescaling effect on effective population size

The effective population size (N-e), and the ratio between N-e and census population size (N) are often used as measures of population viability. We show that using the harmonic mean of population sizes over time - a common proxy for N-e- has some important evolutionary consequences and implications for conservation management. This stems from the fact that there is no unambiguous relationship between the arithmetic and harmonic means for populations fluctuating in size. As long as the variance of population size increases moderately with increasing arithmetic mean population size, the harmonic mean also increases. However, if the variance of population size increases more rapidly, which existing data often suggest, then the harmonic mean may actually decrease with increasing arithmetic mean. Thus maximizing N may not maximize N-e,N- but could instead lower the adaptive potential and hence limit the evolutionary response to environmental change. Large census size has the clear advantage of lowering demographic stochasticity, and hence extinction risk, and under certain conditions large census size also minimizes the loss of genetic variation. Consequently, maximising census size has served as a useful dogma in ecology, genetics and conservation. Nonetheless, due to the intricate relationships among N-e, population viability and the properties of population fluctuations, we suggest that this dogma should be taken only as a rule of thumb. (Less)
A study on sleep parameters in Parkinson's Disease patients

Parkinson's Disease (PD) is a neurodegenerative disorder that affects a considerable number of people all over the world. Symptoms are the results of the dopaminergic neurons death in the substantia nigra pars compacta and the dopamine lack leads to the classical parkinsonian movements such as tremor, irregular gait, paralysis and a low muscular strength. Actually the disease is associated also to other symptoms that are not specifically involved in the motor system and can precede the movements disorder. Non-motor features are: olfactory dysfunction, fatigue, pain, psychiatric and sleep disorders; they have an high impact on the quality of life. This study is focused on the analysis of the electroencephalogram signals (EEG) and the inertial signals, both of them collected during the night. Regarding EEG, three algorithms are implemented: one for distinguishing the REM phases from the others, and two for distinguishing all the sleep stages. Features extraction and machine learning techniques are employed, reaching an accuracy of 98.7%, regarding the REM-NREM differentiation, and an accuracy of 93.1% for all the stages recognition. Wavelet transform is used in the last algorithm for all stages identification; an accuracy of 93.5% is obtained. The second part is centred on the comparison between PD patient's and healthy subjects' inertial signals. The effect of PD on sleep is undeniable: the patient performs less and slower movements with respect to controls. For evaluating these differences an activity index is calculated; moreover other parameters are extracted: the number of turning in bed, the angular velocity and the turning duration. Since the EEG data come from an existing on-line database, the future implementation of this work is to associate EEG and inertial data from the same patient, in order to make an evaluation about his quantity of motion in relation to the disease status. Finally, two user interfaces are proposed for assuring an easier employment of this work.
DNA Polymorphism of DRB 3.2 Locus and its Association with Serum Lysozyme in Rathi Cattle (Bos indicus)

Abstract Sharma, A.K. , Bhushan, B. , Kumar, P., Sharma, D. , Saxena, V.K. , Sharma, A. and Kumar, S. 2005. DNA polymorphism of DRB 3.2 locus and its association with serum lysozyme in Rathi cattle (Bos indicus). J. Appl. Anim. Res., 28: 61–64. Genetic polymorphism study of DRB 3.2 alleles was conducted in Rathi cattle to find out its association with serum lysozyme using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR- RFLP). The digestion of 284 bp fragment with HaeIII resolved three restriction sites, resulting into three restriction patterns with major fragment of sizes as 135, 104, 45; 142 and 142; 180 and 104 bp with frequencies of 0.79, 0.15 and 0.07, respectively. The genotype HaeIII-aa had the highest frequency (0.57) followed by HaeIII-ab (0.29) and HaeIII-ac (0.14). Serum lysozyme level ranged from 0.33 to 6.62 μg/ml with young and adult age groups showing higher levels. Mean serum lysozyme levels in the animals belonged to the HaeIII-aa, HaeIII-ab and HaeIII-ac genotypes were 3.21, 3.92 and 4.91 μg/ml, respectively. The mean serum lysozyme level was also found comparatively higher in the animals belonging to heterozygote genotypes (HaeIII-ab and HaeIII-ac) as compared to the homozygote genotype (HaeIII-aa).
Hydroxyl Radical-scavenging Effects of Spices and Scavengers from Brown Mustard (Brassica nigra)

The effects of methanol extracts of 51 spices on ·OH scavenging were studied in detail. 2-Deoxyribose oxidation and sodium benzoic acid hydroxylation methods were used for detecting the scavenging activity of ·OH. Mustard varieties, thyme, oregano, clove, and allspice all exhibited strong ·OH-scavenging activity. In particular, 3 varieties of mustard had above 90% ·OH-scavenging activity with a 1 μg/ml concentration of their extracts. The ·OH scavenger of Brassica nigra (brown mustard) was isolated and purified by XAD-2 column chromatography and preparative HPLC, and was identified as a 3,5-dimethoxy-4-hydroxycinnamic acid methyl ester by MS, ‘H-NMR, and 13C-NMR. The 3,5-dimethoxy-4-hydroxycinnamic acid methyl ester was prepared by methylating of sinapic acid with diazomethane.
Comparative analysis of the diets of smaller odontocete cetaceans along the coast of southern Africa

The diets of 20 species of smaller Odontoceti were investigated. The material was collected along the southern African coast between 1966 and 1990 and included 158 strandings, 29 animals killed incidentally and 49 animals caught under permit. In total, 57 species in 34 families of fish and 89 species in 24 families of cephalopods were identified from remains in the 236 stomachs investigated. Most Odontoceti fed on commercially unexploited cephalopods and fish, or on fish below commercially utilized sizes. However, the average sizes of anchovy and pilchard eaten by Delphinus delphis and Lagenorhynchus obscurus were larger than the sizes most frequently taken commercially. The species composition of the prey items reflected the onshore-offshore distribution (and possibly the foraging depths) of different Odontoceti. Tursiops truncatus and Cephalorhynchus heavisidii were closest to shore and D. delphis and L. obscurus over the continental shelf. The rest were distributed around the shelf-edge and just off th.
The possible role of trehalose in the mycorrhiza helper bacterium effect

The main objective of the study was to explore the biological pathway that could explain the stimulating effect of mycorrhiza helper bacteria (MHB) on ectomycorrhizal symbiosis. It has been suggested that the ability of MHBs to stimulate mycelial growth is strongly correlated with their effect on ectomycorrhizal establishment; therefore, the role of organic substrates known to be involved in the hyphosphere and mycorrhizosphere effects of this fungal growth promotion were investigated. Therefore, the bacterial influence on fungal growth was tested using two-compartment dishes. One com- partment was filled with a minimal medium (M9 medium) amended with different organic compounds (D-glucosamine, ox- alic acid, trehalose, malonic acid, citric acid, carboxy-methyl cellulose, starch, or chitin) and inoculated with a MHB isolate (Pseudomonas monteilii strain HR13). The other compartment contained fungal plugs of Pisolithus albus isolate IR100. Fungal radial growth was stimulated only when Pseudomonas monteilii was grown on M9 medium + trehalose. This result suggests that trehalose has a role in such bacteria-fungus interactions. However, further research, using other biological models, must be undertaken to identify the role of trehalose in the interactions between MHBs and the fungal symbionts at trophic and genetic levels. Resume´ : Le principal objectif de cette etude etait d'elucider les mecanismes biologiques susceptibles d'expliquer l'impact des bacteries auxiliaires de la mycorhization (BAM) sur la symbiose ectomycorhizienne. Sachant que l'un des effets des BAM le plus frequemment citeest de stimuler la croissance saprophytique des champignons ectomycorhiziens, nous avons evaluel'impact dans ces interactions trophiques de differents substrats carbones( D-glucosamine, acide oxalique, trehalose, acide malonique, acide citrique, carboxy-methyl cellulose, amidon et chitine) caracteristiques des compartiments hyphos- pherique ou mycorhizospherique. Les experiences ont eterealisees en utilisant des booˆtes bi-compartimentees dont un des compartiments etait occupepar une souche de BAM (Pseudomonas monteilii souche HR13) avec un milieu de culture M9, amendeou non, par les substrats carbones et l'autre occupepar des implants fongiques de Pisolithus albus isolat IR100. Les resultats montrent que, lorsque la souche Pseudomonas monteilii HR13 se developpe que le milieu M9 + trehalose, elle stimule la croissance du champignon. Ce resultat montre que le trehalose est un element important dans l'effet BAM. Cependant, d'autres recherches doivent etre realisees afin de preciser le role de ce substrat carboneau niveau trophique et genetique. Mots cles : Pisolithus, Pseudomonas, mycorrhizosphere, bacterie auxiliaire.
Hybrid feature extraction of multimodal images for face recognition

Recently technological advancements have allowed visible, infrared and thermal imaging systems to be readily available for security and access control. Increasing applications of facial recognition for security and access control leads to emerging spoofing methodologies. To overcome these challenges of occlusion, replay attack and disguise, researches have proposed using multiple imaging modalities. Using infrared and thermal modalities alongside visible imaging helps to overcome the shortcomings of visible imaging. In this paper we review and propose hybrid feature extraction methods to combine data from multiple imaging systems simultaneously.