Understanding the effects of changes on the cost‐effectiveness of regression testing techniques

Regression testing is an expensive testing process used to validate modified software. Regression test selection and test‐case prioritization can reduce the costs of regression testing by selecting a subset of test cases for execution, or scheduling test cases to meet testing objectives better. The cost‐effectiveness of these techniques can vary widely, however, and one cause of this variance is the type and magnitude of changes made in producing a new software version. Engineers unaware of the causes and effects of this variance can make poor choices in designing change integration processes, selecting inappropriate regression testing techniques, designing excessively expensive regression test suites and making unnecessarily costly changes. Engineers aware of causal factors can perform regression testing more cost‐effectively. This article reports the results of an embedded multiple case study investigating the modifications made in the evolution of four software systems and their impact on regression testing techniques. The results of this study expose tradeoffs and constraints that affect the success of techniques and provide guidelines for designing and managing regression testing processes. Copyright © 2003 John Wiley & Sons, Ltd.     

Synthesis of Embedded Software from Synchronous Dataflow Specifications

The implementation of software for embedded digital signal processing (DSP) applications is an extremely complex process. The complexity arises from escalating functionality in the applications; intense time-to-market pressures; and stringent cost, power and speed constraints. To help cope with such complexity, DSP system designers have increasingly been employing high-level, graphical design environments in which system specification is based on hierarchical dataflow graphs. Consequently, a significant industry has emerged for the development of data-flow-based DSP design environments. Leading products in this industry include SPW from Cadence, COSSAP from Synopsys, ADS from Hewlett Packard, and DSP Station from Mentor Graphics. This paper reviews a set of algorithms for compiling dataflow programs for embedded DSP applications into efficient implementations on programmable digital signal processors. The algorithms focus primarily on the minimization of code size, and the minimization of the memory required for the buffers that implement the communication channels in the input dataflow graph. These are critical problems because programmable digital signal processors have very limited amounts of on-chip memory, and the speed, power, and cost penalties for using off-chip memory are often prohibitively high for embedded applications. Furthermore, memory demands of applications are increasing at a significantly higher rate than the rate of increase in on-chip memory capacity offered by improved integrated circuit technology.     

Effect of Field Strength and Electronegativity of CaO and MgO on Structural and Optical Properties of SiO<Subscript>2</Subscript>–K<Subscript>2</Subscript>O-CaO-MgO Glasses

The glass composition 55 SiO₂-10 K₂O-(35-x) CaO-(x) MgO (0 ≤ x ≤ 30) is prepared by the melt quenched technique. The as prepared samples are characterized by X-ray diffraction, Fourier Transform-Infrared Spectroscopy (FT-IR) and UV-Visible reflectance spectroscopy. The MgO containing glasses show better polymerization (cross-linking) and have a compact glass network as compared to CaO containing glass. Interestingly, some weak bonds are observed around 1393, 1461 and 1530 cm^-1 in FT-IR spectra related to Ca/Mg-O-H. The optical band gap of the series varies from 3.42 eV to 3.72 eV, indicating wide-band gap materials that could be used in non-linear optical applications.     

Essential oils of Lavandula bipinnata and their antimicrobial activities

The essential oils from dried leaves of Lavandula bipinnata (Roth) Kuntze (Lamiaceae), obtained by soxhlet extraction was analysed by gas chromatography–mass spectrometry (GC–MS) and was evaluated for in vitro antimicrobial activity. The most common components usually found in lavender essential oils were present in the oil samples analysed, out of 43 peaks, 29 components, which constitute 72.38%, were identified in the essential oil. The major constituents were transcarveol (18.93%), pulegone (8.45%), camphor (7.09%) and menthol (5.89%). Other constituents present in fairly good amounts are pipertone (4.65%), caryophyllene oxide (3.68%), linalyl acetate (3.37%) and bicyclogermacrene (3.09%). The essential oil was screened for antimicrobial activity by disc diffusion assay and minimum inhibitory concentration (MIC) against bacteria and fungus. Results reveal that L. bipinnata essential oils are inhibitory against the tested bacteria and fungal strains.     

A Novel Computationally Efficient Approach to Identify Visually Interpretable Medical Conditions from 2D Skeletal Data

Timely identification and treatment of medical conditions could facilitate faster recovery and better health. Existing systems address this issue using custom-built sensors, which are invasive and difficult to generalize. A low-complexity scalable process is proposed to detect and identify medical conditions from 2D skeletal movements on video feed data. Minimal set of features relevant to distinguish medical conditions: AMF, PVF and GDF are derived from skeletal data on sampled frames across the entire action. The AMF (angular motion features) are derived to capture the angular motion of limbs during a specific action. The relative position of joints is represented by PVF (positional variation features). GDF (global displacement features) identifies the direction of overall skeletal movement. The discriminative capability of these features is illustrated by their variance across time for different actions. The classification of medical conditions is approached in two stages. In the first stage, a low-complexity binary LSTM classifier is trained to distinguish visual medical conditions from general human actions. As part of stage 2, a multi-class LSTM classifier is trained to identify the exact medical condition from a given set of visually interpretable medical conditions. The proposed features are extracted from the 2D skeletal data of NTU RGB + D and then used to train the binary and multi-class LSTM classifiers. The binary and multi-class classifiers observed average F1 scores of 77% and 73%, respectively, while the overall system produced an average F1 score of 69% and a weighted average F1 score of 80%. The multi-class classifier is found to utilize 10 to 100 times fewer parameters than existing 2D CNN-based models while producing similar levels of accuracy.     

Evaluation of the protective nature of GO–BCP nanocomposite coatings on 316L SS in artificial body fluid

This work reports on a novel approach to deposit composite coatings based on biphasic calcium phosphate (BCP) incorporating graphene oxide (GO) on 316L stainless steel (316L SS) and on its protective nature against corrosion in the simulated body fluid (SBF). For this purpose, 2-dimensional GO was successfully incorporated in 1% and 3% weight ratios as mechanical strength enhancer and pore size reducer for the prepared coatings. It was observed that upon increasing the GO content, the corrosion rate was drastically decreased when compared to pristine BCP coating. The corrosion resistance polarization results are in good agreement with the test results obtained for SBF immersion study. The size of the particles has significantly decreased, as shown by transmission electron microscopy (from 190 to 27 nm). The experimental results indicate that the composite hydroxyapatite–β-tricalcium phosphate–GO (HAp–β-TCP–GO) coatings enhanced the corrosion resistance of the surgical grade 316L SS, turning it a better implanting option for orthopedic applications.     

Crucial Role of the Chaperonin GroES/EL for Heterologous Production of the Soluble Methane Monooxygenase from Methylomonas methanica MC09

Methane is a widespread energy source and can serve as an attractive C1 building block for a future bioeconomy. The soluble methane monooxygenase (sMMO) is able to break the strong C−H bond of methane and convert it to methanol. The high structural complexity, multiplex cofactors, and unfamiliar folding or maturation procedures of sMMO have hampered the heterologous production and thus biotechnological applications. Here, we demonstrate the heterologous production of active sMMO from the marine Methylomonas methanica MC09 in Escherichia coli by co-synthesizing the GroES/EL chaperonin. Iron determination, electron paramagnetic resonance spectroscopy, and native gel immunoblots revealed the incorporation of the non-heme diiron centre and homodimer formation of active sMMO. The production of recombinant sMMO will enable the expansion of the possibilities of detailed studies, allowing for a variety of novel biotechnological applications.     

Compaction and relaxation characteristics of single compacts produced from distiller’s spent grain

Compaction and relaxation characteristics of densified distiller’s spent grain compacts produced at different levels of compressive pressure (60.3–135.7 MPa), initial moisture content (15%, 20% and 25% wb) and soluble content (15% and 30%) were analyzed during the study. The compaction levels used in this study caused up to a 4% wb reduction in the moisture of compacts in comparison to their initial moisture. The density of compacts was analyzed to determine the compaction characteristics of distiller’s spent grain using Jones model. Analysis of the Jones model showed that there was a significant (P = 0.004) decrease in compressibility with an increase in soluble content from 0% to 30%. The distiller’s spent grain compacts were subjected to relaxation tests and the relaxation data obtained were normalized and analyzed to determine the asymptotic modulus (E_A) of the compacts. The asymptotic modulus was used as a measure of rigidity of the compacts. Distiller’s spent grain compact produced with a compressive force of 135.7 MPa and initial moisture of 25% wb possessed the highest E_A value.     

Thermal modeling of a dual-purposed snap biopsy acquisition procedure in a suspected cancerous lesion

The needle-based biopsy procedure is common in cancer detection and patient-specific targeted therapy, wherein a tissue sample from the potential diseased site is acquired and frozen instantly with the help of a coolant medium. While liquid nitrogen (LN₂) is the most widely used coolant for preserving the acquired sample and performing biopsy tests on the same at a later time, cold ischemia leads to inevitable cell degradation beyond a threshold time. In an effort to circumvent this challenge, here we aim to put forward the concept of an integrated biopsy sample acquisition and cryotherapy procedure, by incorporating an exclusively designed cooling circuit in a conventional biopsy-needle for freezing the sample in vivo as soon as it is acquired, while causing cryoablation in the surrounding tissues simultaneously. An enthalpy-based approach is employed to develop a bioheat transfer model for the cryotherapy design, with illustrative simulation data presented for breast cancer. Our model is demonstrated by considering a constant LN₂ cooling temperature of 77.15 K, and cooling powers ranging from 2 to 10 W. The model results elucidate procedure-specific insights such as the thermal penetration depth and the cooling time on being subjected to the cryoablation. The cooling rates thus obtained are further assessed from the simultaneous considerations of cryopreservation and cryosurgery, deriving critical insights on tissue survival and damage for acting as a precursor to patient-specific treatment planning.