Nonenzymic browning during storage of white hard grape pekmez (Zile pekmezi)

Effects of storage period on hydroxymethylfurfural, pH and colour were studied in white hard grape pekmez (Zile pekmezi), a Turkish traditional product. Pekmez samples were stored at 20 °C for 8 months. Analysis of variance revealed significant differences in hydroxymethylfurfural, pH, L, a and b values (P<0.01) based on storage time.     

Studying high impact fix-inducing changes

As software systems continue to play an important role in our daily lives, their quality is of paramount importance. Therefore, a plethora of prior research has focused on predicting components of software that are defect-prone. One aspect of this research focuses on predicting software changes that are fix-inducing. Although the prior research on fix-inducing changes has many advantages in terms of highly accurate results, it has one main drawback: It gives the same level of impact to all fix-inducing changes. We argue that treating all fix-inducing changes the same is not ideal, since a small typo in a change is easier to address by a developer than a thread synchronization issue. Therefore, in this paper, we study high impact fix-inducing changes (HIFCs). Since the impact of a change can be measured in different ways, we first propose a measure of impact of the fix-inducing changes, which takes into account the implementation work that needs to be done by developers in later (fixing) changes. Our measure of impact for a fix-inducing change uses the amount of churn, the number of files and the number of subsystems modified by developers during an associated fix of the fix-inducing change. We perform our study using six large open source projects to build specialized models that identify HIFCs, determine the best indicators of HIFCs and examine the benefits of prioritizing HIFCs. Using change factors, we are able to predict 56 % to 77 % of HIFCs with an average false alarm (misclassification) rate of 16 %. We find that the lines of code added, the number of developers who worked on a change, and the number of prior modifications on the files modified during a change are the best indicators of HIFCs. Lastly, we observe that a specialized model for HIFCs can provide inspection effort savings of 4 % over the state-of-the-art models. We believe our results would help practitioners prioritize their efforts towards the most impactful fix-inducing changes and save inspection effort.     

The modeling of mode choices of intercity freight transportation with the artificial neural networks and adaptive neuro-fuzzy inference system

Mode choice modeling is probably the most important element of transportation planning. It affects the general efficiency of travel and the allocation of resources. The development of mode choice models has recently witnessed significant advances in many fields, such as passenger and freight transport. A large number of mathematical models have been used to model the traveler’s choice of mode and destination and the shipper’s choice of mode, shipment size and supply market, among others. Such models are not only becoming almost intractable but also data intensive, difficult to calibrate and update, and intransferable. These models cover a wide range of mathematical complexity and accuracy. This paper describes a new approach to mode choice of intercity freight transport modeling using artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) models. The new approach combines the learning ability of artificial neural networks and the transparent nature of fuzzy logic. The approach is found to be highly adaptive and efficient in investigating non-linear relationships among different variables. The adaptive neuro-fuzzy inference system model is tested on the freight transport market in Turkey, Germany, France and Austria by using information on the freight flows and their attributes. The ANNs and ANFIS models are more successful in the representation of the non-linear behavior of mode choice of intercity freight transport compared to the classical models.     

An industry experiment on the effects of test-driven development on external quality and productivity

Existing empirical studies on test-driven development (TDD) report different conclusions about its effects on quality and productivity. Very few of those studies are experiments conducted with software professionals in industry. We aim to analyse the effects of TDD on the external quality of the work done and the productivity of developers in an industrial setting. We conducted an experiment with 24 professionals from three different sites of a software organization. We chose a repeated-measures design, and asked subjects to implement TDD and incremental test last development (ITLD) in two simple tasks and a realistic application close to real-life complexity. To analyse our findings, we applied a repeated-measures general linear model procedure and a linear mixed effects procedure. We did not observe a statistical difference between the quality of the work done by subjects in both treatments. We observed that the subjects are more productive when they implement TDD on a simple task compared to ITLD, but the productivity drops significantly when applying TDD to a complex brownfield task. So, the task complexity significantly obscured the effect of TDD. Further evidence is necessary to conclude whether TDD is better or worse than ITLD in terms of external quality and productivity in an industrial setting. We found that experimental factors such as selection of tasks could dominate the findings in TDD studies.     

Efficient retrieval of replicated data

Declustering is a common technique used to reduce query response times. Data is declustered over multiple disks and query retrieval can be parallelized. Most of the research on declustering is targeted at spatial range queries and investigates schemes with low additive error. Recently, declustering using replication has been proposed to reduce the additive overhead. Replication significantly reduces retrieval cost of arbitrary queries. In this paper, we propose a disk allocation and retrieval mechanism for arbitrary queries based on design theory. Using the proposed c-copy replicated declustering scheme, buckets can be retrieved using at most k disk accesses. Retrieval algorithm is very efficient and is asymptotically optimal with complexity for a query Q. In addition to the deterministic worst-case bound and efficient retrieval, proposed algorithm handles nonuniform data, high dimensions, supports incremental declustering and has good fault-tolerance property. Experimental results show the feasibility of the algorithm. Recommended by: Sunil Prabhakar     

Thread vulnerability in parallel applications

Continuously reducing transistor sizes and aggressive low power operating modes employed by modern architectures tend to increase transient error rates. Concurrently, multicore machines are dominating the architectural spectrum today in various application domains. These two trends require a fresh look at resiliency of multithreaded applications against transient errors from a software perspective. In this paper, we propose and evaluate a new metric called the Thread Vulnerability Factor (TVF$TVF$). A distinguishing characteristic of TVF$TVF$ is that its calculation for a given thread (which is typically one of the threads of a multithreaded application) does not depend on its code alone, but also on the codes of the threads that share resources and data with that thread. As a result, we decompose TVF$TVF$ of a thread into two complementary parts: local and remote. While the former captures the TVF$TVF$ induced by the code of the target thread, the latter represents the vulnerability impact of the threads that interact with the target thread. We quantify the local and remote TVF$TVF$ values for three architectural components (register file, ALUs, and caches) using a set of ten multithreaded applications from the Parsec and Splash-2 benchmark suites. Our experimental evaluation shows that TVF$TVF$ values tend to increase as the number of cores increases, which means the system becomes more vulnerable as the core count rises. We further discuss how TVF$TVF$ metric can be employed to explore performance–reliability tradeoffs in multicores. Reliability-based analysis of compiler optimizations and redundancy-based fault tolerance are also mentioned as potential usages of our TVF$TVF$ metric.     

Energy- and reliability-aware task scheduling onto heterogeneous MPSoC architectures

Scheduling periodic tasks onto a multiprocessor architecture under several constraints such as performance, cost, energy, and reliability is a major challenge in embedded systems. In this paper, we present an Integer Linear Programming (ILP) based framework that maps a given task set onto an Heterogeneous Multiprocessor System-on-Chip (HMPSoC) architecture. Our framework can be used with several objective functions; minimizing energy consumption, minimizing cost (i.e., the number of heterogeneous processors), and maximizing reliability of the system under performance constraints. We use Dynamic Voltage Scaling (DVS) for reducing energy consumption while we employ task duplication to maximize reliability. We illustrate the effectiveness of our approach through several experiments, each with a different number of tasks to be scheduled. We also propose two heuristics based on Earliest Deadline First (EDF) algorithm for minimizing energy under performance and cost constraints. Our experiments on generated task sets show that ILP-based method reduces the energy consumption up to 62% percent against a method that does not apply DVS. Heuristic methods obtain promising results when compared to optimal results generated by our ILP-based method.     

Reusable water oxidation catalyst with dual active center for enhanced water oxidation: Iridium oxide nanoparticles immobilized on monodisperse-porous Mn5O8 microspheres

A reusable catalyst with dual active center for chemical water oxidation is synthesized for the first time by immobilization of iridium oxide nanoparticles (IrO₂ NPs) on monodisperse-porous manganese oxide microspheres acting both catalytic active center and support. Individual catalytic activity of manganese oxide microspheres is explained by multiple oxidation states of manganese which are capable of forming oxidative oxygen species. Monodisperse-porous microspheres in the form of Mn₅O₈, MnO₂ and Mn₂O₃ are used for synthesis of different catalysts and the highest activity in water oxidation is observed with the catalyst synthesized using Mn₅O₈ microspheres. The catalytic activity is correlated with the total Mn(II) and Mn(III) percentage of manganese oxide type selected for composite catalyst. The oxygen evolution up to 244 μmol is achieved in 30 min with the catalyst synthesized using Mn₅O₈ microspheres. Maximum TON and TOF numbers are obtained as 298 and 557 h^?1 with excellent reusability.