A comparative study on the intensity and harmfulness of late propagation in near-miss code clones

Exact or nearly similar code fragments in a software system’s source code are referred to as code clones. It is often the case that updates (i.e., changes) to a code clone will need to be propagated to its related code clones to preserve their similarity and to maintain source code consistency. When there is a delay in propagating the changes (possibly because the developer is unaware of the related cloned code), the system might behave incorrectly. A delay in propagating a change is referred to as ‘late propagation,’ and a number of studies have investigated this phenomenon. However, these studies did not investigate the intensity of late propagation nor how late propagation differs by clone type. In this research, we investigate late propagation separately for each of the three clone types (Type 1, Type 2, and Type 3). According to our experimental results on thousands of revisions of eight diverse subject systems written in two programming languages, late propagation occurs more frequently in Type 3 clones compared with the other two clone types. More importantly, there is a higher probability that Type 3 clones will experience buggy late propagations compared with the other two clone types. Also, we discovered that block clones are more involved in late propagation than method clones. Refactoring and tracking of Similarity Preserving Change Pattern (SPCP) clones (i.e., the clone fragments that evolve following a SPCP) can help us minimize the occurrences of late propagation in clones.     

Deep structured residual encoder-decoder network with a novel loss function for nuclei segmentation of kidney and breast histopathology images

To improve the process of diagnosis and treatment of cancer disease, automatic segmentation of haematoxylin and eosin (H & E) stained cell nuclei from histopathology images is the first step in digital pathology. The proposed deep structured residual encoder-decoder network (DSREDN) focuses on two aspects: first, it effectively utilized residual connections throughout the network and provides a wide and deep encoder-decoder path, which results to capture relevant context and more localized features. Second, vanished boundary of detected nuclei is addressed by proposing an efficient loss function that better train our proposed model and reduces the false prediction which is undesirable especially in healthcare applications. The proposed architecture experimented on three different publicly available H&E stained histopathological datasets namely: (I) Kidney (RCC) (II) Triple Negative Breast Cancer (TNBC) (III) MoNuSeg-2018. We have considered F1-score, Aggregated Jaccard Index (AJI), the total number of parameters, and FLOPs (Floating point operations), which are mostly preferred performance measure metrics for comparison of nuclei segmentation. The evaluated score of nuclei segmentation indicated that the proposed architecture achieved a considerable margin over five state-of-the-art deep learning models on three different histopathology datasets. Visual segmentation results show that the proposed DSREDN model accurately segment the nuclear regions than those of the state-of-the-art methods.

     

A framework for development and evaluation of a dynamic subchannel allocation scheme in an OFDMA system

This paper presents a framework for allocating radio resources to the Access Points (APs) introducing an Access Point Controller (APC). Radio resources can be either time slots or subchannels. The APC assigns subchannels to the APs using a dynamic subchannel allocation scheme. The developed framework evaluates the dynamic subchannel allocation scheme for a downlink multicellular Orthogonal Frequency Division Multiple Access (OFDMA) system. In the considered system, each AP and the associated Mobile Terminals (MTs) are not operating on a frequency channel with fixed bandwidth, rather the channel bandwidth for each AP is dynamically adapted according to the traffic load. The subchannels assignment procedure is based on quality estimations due to the interference measurements and the current traffic load. The traffic load estimation is realized with the measurement of the utilization of the assigned radio resources. The reuse partitioning for the radio resources is done by estimating mutual Signal to Interference Ratio (SIR) of the APs. The developed dynamic subchannel allocation ensures Quality of Service (QoS), better traffic adaptability, and higher spectrum efficiency with less computational complexity.

Numerical investigation of gas-particle hydrodynamics in a vortex chamber fluidized bed

Gas-particle hydrodynamic behaviour inside a vortex chamber fluidized bed is studied numerically with respect to different design and operating conditions. A three-dimensional computational fluid dynamics (CFD) model of a cylindrical vortex chamber is developed. Simulations are carried out with particles and without particles. In order to understand the gas-particle flow behavior velocity distribution, particle volume fraction distribution, radial pressure distribution and axial pressure distribution inside the vortex chamber are analyzed in detail. Particles of different diameters are used and its effect on the gas-particle flow behaviour is studied. Design parameters like the number of gas inlet slots and slot width are varied and their impact on the hydrodynamics of the vortex chamber is investigated. The numerical model is validated by comparing the numerical results with experimental results reported in literature.     

Characterizing Li in partially lithiated layer materials using atomic-resolution imaging,modeling, and simulation

Understanding of phase-stability and nanoscale structural modulation during lithiation of layer materials demand comprehensive analysis of the Li-containing phases in the solid-state reaction products. Conventional chemical analysis methods in the transmission electron microscope (TEM) are not ideal to detect Li in partially intercalated nanodomains because Li atoms do not remain stationary under the focused electron beam. An alternate approach combining density functional theory (DFT) modeling and multislice image simulation has been explored in the present study to analyze the intercalated structures and to detect and quantify Li from the recorded high-resolution TEM (HRTEM) micrographs of partially intercalated phases. HRTEM micrographs from partially lithiated graphite and MoS₂ show variations in the interlayer spacings, but are not usually directly interpretable. Hypothetical intercalated microstructures of graphite and MoS₂ supercells have been generated using atomic-scale simulations with systematically varying Li concentrations. The measured interplanar spacings are compared with those of experimentally recorded HRTEM micrographs from lithiated graphite and MoS₂. The results confirm the coexistence of different lithiated phases at localized domains. This understanding of phase transformation and the lithium quantification provides a basis for understanding the structural accommodation of layered materials during intercalation.     

A comparative study to estimate daily diffuse solar radiation over India

A detailed study of monthly average daily diffuse solar radiation for selected Indian locations have been performed using five years (2001–2005) measured data. The data of four prominent locations (Jodhpur, Calcutta, Bombay and Pune), representing varying weather conditions of the entire country, have been taken for the present study. The correlations between the diffuse fraction (H_d/H) and the sunshine fraction (S/S₀) have been developed using regression analysis method for each selected location as well as for all Indian locations, we call it All India Correlation (AIC). The results obtained from present AIC are well compared with the measured data along with the estimates of Liu and Jordan, Gopinathan and Iqbal for different locations. The comparisons between various data conclude that AIC can be used to estimate diffuse fraction for any location in India. For further validation and to show the accuracy of present correlations, statistical tests of root mean square error (RMSE), mean bias error (MBE) and mean percentage error (MPE) are also performed.     

Preparation of novel biomass humate flame retardants and their flame retardancy in epoxy resin

Humic acid (HA), a biomass material with plentiful oxygen-containing functional groups, showed huge potential to be considered as a promising charring agent in flame retardancy. In this study, this HA was modified with four different metal ions like Fe²⁺, Mn²⁺, Al³⁺, and Cu²⁺ and finally, introduced into the epoxy resin (EP) to enhance the flame retardancy of the EP and the dispersion of these flame retardants into the EP matrix. When 10 wt% of HA-Fe and HA-Mn were incorporated into EP matrix, the limiting oxygen index (LOI) was increased from 21.2% for EP to 26.6 and 25.3% for the EP composites and the peak heat release rate (pHRR) was reduced by 36 and 35.5%, respectively. Such a significant improvement in flame retardancy was attributed to the catalytic charring of HA in the presence of metal ions, which ultimately increased the residual char formation and produced compact char layers during the combustion process to retard the transfer of heat and combustible gases between the EP composites and the flame zone. Finally, this kind of application provided a feasible way for the development of an environmentally friendly flame retardant with high efficiency, which improved the fire safety of EP matrix.     

Online Social Network Security: A Comparative Review Using Machine Learning and Deep Learning

Neural Processing Letters - In the present era, Online Social Networking has become an important phenomenon in human society. However, a large section of users are not aware of the security and...     

An improved auto-tuning scheme for PID controllers

An improved auto-tuning scheme is proposed for Ziegler–Nichols (ZN) tuned PID controllers (ZNPIDs), which usually provide excessively large overshoots, not tolerable in most of the situations, for high-order and nonlinear processes. To overcome this limitation ZNPIDs are upgraded by some easily interpretable heuristic rules through an online gain modifying factor defined on the instantaneous process states. This study is an extension of our earlier work [Mudi RK., Dey C. Lee TT. An improved auto-tuning scheme for PI controllers. ISA Trans 2008; 47: 45–52] to ZNPIDs, thereby making the scheme suitable for a wide range of processes and more generalized too. The proposed augmented ZNPID (AZNPID) is tested on various high-order linear and nonlinear dead-time processes with improved performance over ZNPID, refined ZNPID (RZNPID), and other schemes reported in the literature. Stability issues are addressed for linear processes. Robust performance of AZNPID is observed while changing its tunable parameters as well as the process dead-time. The proposed scheme is also implemented on a real time servo-based position control system.     

A Novel Devolatilization Technique of Pre-reduction of Iron Ore Using Lean Grade Coal

The problem of properly utilizing non-coking coals in alternative iron making processes dates back to long ago. Lean grade coals with higher ash and volatile matter content (e.g. boiler grade coals) have always challenged the metallurgists to develop a suitable process for their utilization. The aim of this work is to achieve an energy efficient method for the reduction of briquetted iron ore fines using ‘SYNGAS’—which is the gaseous product (enriched with reducing agents) generated by pyrolysis of coal along with fine sized carbon particles produced during pyrolysis. A laboratory scale reduction furnace with pyrolysis facility has been designed and fabricated after in depth thermo-gravimetric analysis (TGA), differential thermal analysis (DTA), and gas chromatograph (GC) studies. A particular temperature profile has been maintained inside the furnace to achieve the optimum reduction temperature. The briquettes are reduced in the pyrolysis furnace and the extent of reduction has been calculated from the weight loss. The reduced specimens are characterized using X-ray diffractometer (XRD), scanning electron microscope (SEM), energy dispersive X-ray spectrometer (EDX), field emission scanning electron microscope (FESEM), and chemical analysis method. It is observed that iron ore can be significantly reduced to metallic iron by using the devolatilization product of lean grade coal.