Is cloned code really stable?

Clone has emerged as a controversial term in software engineering research and practice. The impact of clones is of great importance from software maintenance perspectives. Stability is a well investigated term in assessing the impacts of clones on software maintenance. If code clones appear to exhibit a higher instability (i.e., higher change-proneness) than non-cloned code, then we can expect that code clones require higher maintenance effort and cost than non-cloned code. A number of studies have been done on the comparative stability of cloned and non-cloned code. However, these studies could not come to a consensus. While some studies show that code clones are more stable than non-cloned code, the other studies provide empirical evidence of higher instability of code clones. The possible reasons behind these contradictory findings are that different studies investigated different aspects of stability using different clone detection tools on different subject systems using different experimental setups. Also, the subject systems were not of wide varieties. Emphasizing these issues (with several others mentioned in the motivation) we have conducted a comprehensive empirical study where we have - (i) implemented and investigated seven existing methodologies that explored different aspects of stability, (ii) used two clone detection tools (NiCad and CCFinderX) to implement each of these seven methodologies, and (iii) investigated the stability of three types (Type-1, Type-2, Type-3) of clones. Our investigation on 12 diverse subject systems covering three programming languages (Java, C, C#) with a list of 8 stability assessment metrics suggest that (i) cloned code is often more unstable (change-prone) than non-cloned code in the maintenance phase, (ii) both Type 1 and Type 3 clones appear to exhibit higher instability than Type 2 clones, (iii) clones in Java and C programming languages are more change-prone than the clones in C#, and (iv) changes to the clones in procedural programming languages seem to be more dispersed than the changes to the clones in object oriented languages. We also systematically replicated the original studies with their original settings and found mostly equivalent results as of the original studies. We believe that our findings are important for prioritizing code clones from management perspectives.     

Kitkaite NiTeSe,an Ambient-Stable Layered Dirac Semimetal with Low-Energy Type-II Fermions with Application Capabilities in Spintronics and Optoelectronics

The emergence of Dirac semimetals has stimulated growing attention, owing to the considerable technological potential arising from their peculiar exotic quantum transport related to their nontrivial topological states. Especially, materials showing type-II Dirac fermions afford novel device functionalities enabled by anisotropic optical and magnetotransport properties. Nevertheless, real technological implementation has remained elusive so far. Definitely, in most Dirac semimetals, the Dirac point lies deep below the Fermi level, limiting technological exploitation. Here, it is shown that kitkaite (NiTeSe) represents an ideal platform for type-II Dirac fermiology based on spin-resolved angle-resolved photoemission spectroscopy and density functional theory. Precisely, the existence of type-II bulk Dirac fermions is discovered in NiTeSe around the Fermi level and the presence of topological surface states with strong (≈50%) spin polarization. By means of surface-science experiments in near-ambient pressure conditions, chemical inertness towards ambient gases (oxygen and water) is also demonstrated. Correspondingly, NiTeSe-based devices without encapsulation afford long-term efficiency, as demonstrated by the direct implementation of a NiTeSe-based microwave receiver with a room-temperature photocurrent of 2.8 µA at 28 GHz and more than two orders of magnitude linear dynamic range. The findings are essential to bringing to fruition type-II Dirac fermions in photonics, spintronics, and optoelectronics.     

Rare‐earth‐doped SiO2‐CaF2 glass ceramic nano‐particle with upconversion properties

Rare‐earth‐doped upconversion nano‐phosphor shows new possibilities in the field of bioimaging because of its unique properties like higher penetration depth, low signal to noise ratio (SNR), good photo stability, and zero auto fluorescence. The oxyfluoride glass system is the combination of both fluoride and oxide where fluoride host offers high optical transparency due to low phonon energy and oxide network offers high physical stability. Thus, in the present work, an attempt has been made to synthesize 1 mol% Er³⁺ doped SiO₂‐CaF₂ glass ceramic nano‐particles through sol‐gel route. The synthesized glass ceramic particles were heat treated at 4 different temperatures starting from 600°C to 900°C.The X‐ray diffraction (XRD) analysis and Transmission electron microscopy (TEM) analysis confirmed the formation of CaF₂ nano‐crystals in the matrix which is 20‐30 nm in size. The vibrational spectroscopic analysis of the glass ceramics sample has been investigated by Fourier transform infrared (FTIR) spectroscopy. The UV‐Visible‐NIR spectroscopy analysis was carried out to analyze the absorption intensity in the near infrared region. Upon 980 nm excitation, the sample shows red emission corresponds to ⁴F_9/2→⁴I_15/2 energy level transition. The prepared nano‐particles showed excellent biocompatibility when tasted on MG‐63 osteoblast cells.     

Tuning of an optimal fuzzy PID controller with stochastic algorithms for networked control systems with random time delay

An optimal PID and an optimal fuzzy PID have been tuned by minimizing the Integral of Time multiplied Absolute Error (ITAE) and squared controller output for a networked control system (NCS). The tuning is attempted for a higher order and a time delay system using two stochastic algorithms viz. the Genetic Algorithm (GA) and two variants of Particle Swarm Optimization (PSO) and the closed loop performances are compared. The paper shows that random variation in network delay can be handled efficiently with fuzzy logic based PID controllers over conventional PID controllers.     

Isolation of High Oleate Recombinants in Peanut by Near Infra‐Red Spectroscopy and Confirmation With Allele Specific Polymerase Chain Reaction Marker

Near infrared (NIR) spectrophotometer offers rapid, noninvasive, nondestructive, and high‐throughput phenotyping of seed samples for use in agriculture and industry. In this study, a reflectance‐based NIR spectrophotometer was calibrated and used for the isolation of desirable higher‐oleic‐acid peanut recombinants from single‐seed‐derived segregating populations at F₇ and F₈ generations. A calibration model was developed through partial least‐square regression using wet chemistry data from 158 peanut genotypes. Desirable prediction for oil, palmitic acid, oleic acid, and linoleic acid in intact seed was obtained based on this calibration. It detected significant high correlations (r) and coefficient of determination (R²) between the actual gas chromatography values and NIR predicted values of fatty acid profile in another 123 peanut genotypes that were generated from crosses involving a high‐oleate mutant and Spanish bunch varieties with early maturity. From this recombinant single‐seed‐derived progenies, 15 higher‐oleate recombinants were isolated and later genotyped through an in‐house developed polymerase chain reaction‐based allele specific marker. The present study has generated high‐oleate peanut recombinants with early maturity in Spanish bunch background. The breeding materials generated here will be evaluated for yield attributing traits at different locations in future.     

High stress abrasive wear behaviour of aluminium hard particle composites: Effect of experimental parameters, particle size and volume fraction

High stress abrasive wear behaviour of aluminium alloy (ADC-12)–SiC particle reinforced composites has been studied as a function of applied load, reinforcement size and volume fraction, and has been compared with that of the matrix alloy. Two different size ranges (25–50 and 50–80 μm) of SiC particles have been used for synthesizing ADC-12–SiC composite. The volume fraction of SiC particles has been varied in the ranges from 5 to 15 wt%. It has been noted that the abrasive wear rate of the alloy reduced considerably due to addition of SiC particle and the wear rate of composite decreases linearly with increase in SiC content. It has also been noted that the wear resistance of composite varies inversely with square of the reinforcement size. The wear rate of the alloy and composite has been found to be a linear function of applied load but invariant to the abrasive size; at critical abrasive size, transition in wear behaviour is noted. This has been explained through analytically derived equations and wear–surface examination.     

Cluster-Based RF Fingerprint Positioning Using LTE and WLAN Signal Strengths

Wireless Local Area Network (WLAN) positioning has become a popular localization system due to its low-cost installation and widespread availability of WLAN access points. Traditional grid-based radio frequency (RF) fingerprinting (GRFF) suffers from two drawbacks. First it requires costly and non-efficient data collection and updating procedure; secondly the method goes through time-consuming data pre-processing before it outputs user position. This paper proposes Cluster-based RF Fingerprinting (CRFF) to overcome these limitations by using modified Minimization of Drive Tests data which can be autonomously collected by cellular operators from their subscribers. The effect of environmental changes and device variation on positioning accuracy has been carried out. Experimental results show that even under these variations CRFF can improve positioning accuracy by 15.46 and 22.30% in 95 percentile of positioning error as compared to that of GRFF and K-nearest neighbour methods respectively.     

Memory effect in a junction-like CdS nanocomposite/conducting polymer poly[2-methoxy-5-(2-ethylhexyloxy)1,4-phenylene-vinylene] heterostructure

The operation of a nonvolatile memory device is demonstrated using junction-like CdS nanocomposites embedded in a polymer matrix. The capacitance-voltage characteristics of Al/conducting polymer poly[2-methoxy-5-(2-ethylhexyloxy)-1,4-phenylene-vinylene]/CdS nanocomposites in a polyvinyl alcohol matrix/indium tin oxide device exhibit hysteresis, which is attributed to the trapping, storage, and emission of holes in the quantized valence band energy levels of isolated CdS nanoneedles. The characteristics at different operating frequencies show that the hysteresis is due to trapping of charge carriers in CdS nanocomposites rather than in the interfacial states. The memory behavior in the inorganic/organic heterostructure is explained on the basis of a simple energy band diagram.     

Investigation of mechanical factor of soil reinforced with four types of fibers: An integrated experimental and extreme learning machine approach

ABSTRACT

This study investigates and compares mechanical factor (a dimensionless parameter and defined as the ratio of the compressive strength of fiber reinforced soil to that of unreinforced soil) for soils reinforced with four different fibers (three natural fibers and one synthetic fiber). An integrated methodology was utilized, including 351 laboratory experiments for obtaining data and Extreme Learning Machine (ELM) technique for developing functional relationships between mechanical factor and soil and fiber parameters. Soils reinforced with synthetic fiber (Polypropylene) and with natural fibers exhibited different characteristics when subjected to the same variation in soil parameters. This phenomenon can be attributed to the differences in surface morphology and water absorption capability of Polypropylene comparative to other natural fibers. Polypropylene–soil composite shows the maximum sensitivity to the soil moisture. It also shows the least sensitivity toward soil density and fiber content among all tested fiber–soil composites.