Theoretical and practical investigations of copper ion selective electrode with polymeric membrane based on N,N′-(2,2-dimethylpropane-1,3-diyl)-bis(dihydroxyacetophenone)

A novel ion-selective poly(vinyl chloride) (PVC) membrane sensor for Cu²⁺ ions based on N,N′-(2,2-dimethylpropane-1,3-diyl)-bis(dihydroxyacetophenone) (NDHA) as a new ionophore was prepared and studied. The best performance was observed for the membrane composition, including 30:65:1:4 (wt%) = PVC:DBP:KTpClPB:NDHA. The electrode showed a good Nernstian slope of 30.0 ± 0.5 mV/decade in a wide linear range activity of 3.0 × 10⁻⁷ to 1.0 × 10⁻² mol dm⁻³ Cu(NO₃)₂ with limit of detection 2.5 × 10⁻⁷. Sensor exhibited a fast response time (t_95% < 10 s) and could be used for about 4 months in the pH range of 3.0–7.4. The proposed potentiometric sensor was found to work satisfactorily in partially non-aqueous media up to 30 (vol%) content of methanol, ethanol and acetone. Applications of this electrode for the determination of copper in real samples, and as an indicator electrode for potentiometric titration of Cu²⁺ ion using EDTA, were reported. In order to predict the extraction ability of NDHA for different metallic ions, the complexes [M(NDHA)] and [M(H₂O)₆] (where M = Cu²⁺, Co²⁺, Hg²⁺, Pb²⁺, Ag⁺, Mg²⁺, Ca²⁺, Mn²⁺, Zn²⁺, Cd²⁺, K⁺ and Al³⁺) were investigated using ab initio theoretical calculations. The metal binding capability was evaluated using the binding energy. Results of our study could be useful for prediction of the extraction power of this Schiff base and could play a guiding role in planning experiments.     

Controller design for a wind farm, considering both power and load aspects

In this paper, a wind farm controller is developed that distributes power references among wind turbines while it reduces their structural loads. The proposed controller is based on a spatially discrete model of the farm, which delivers an approximation of wind speed in the vicinity of each wind turbine. The control algorithm determines the reference signals for each individual wind turbine controller in two scenarios based on low and high wind speed. In low wind speed, the reference signals for rotor speed are adjusted, taking the trade-off between power maximization and load minimization into account. In high wind speed, the power and pitch reference signals are determined while structural loads are minimized. To the best of authors’ knowledge, the proposed dynamical model is a suitable framework for control, since it provides a dynamic structure for behavior of the flow in wind farms. Moreover, the controller has been proven exceptionally useful in solving the problem of both power and load optimization on the basis of this model.     

Empirical evaluation of river basin sustainability affected by inter‐basin water transfer using composite indicators

In this study, a practical approach to evaluate the sustainability of river basins subjected to an inter‐basin water transfer project is developed. Selection of appropriate evaluation indicators is pivotal to such approach. To make use of huge amount of data, composite indicators of sustainability (CIS) should be utilised. The proposed approach relies on 15 sustainability indicators (SI) that cover three major criteria namely (economic, social and environmental), and aggregates them into eight different types of sustainability indices for a more robust outcome. Two scenarios were considered within the source and recipient basins. Furthermore, multivariate principal component analysis (PCA) was applied to determine principal and non‐principal indicators for the two river basins. The ability of CIS and PCA methods were verified via correlation and simple regression methods respectively. The results demonstrated that inter‐basin water transfer may improve sustainability, provided that a proper water resource management is enforced.     

An analytical framework for event mining in video data

With the high availability of digital video contents on the internet, users need more assistance to access digital videos. Various researches have been done about video summarization and semantic video analysis to help to satisfy these needs. These works are developing condensed versions of a full length video stream through the identification of the most important and pertinent content within the stream. Most of the existing works in these areas are mainly focused on event mining. Event mining from video streams improves the accessibility and reusability of large media collections, and it has been an active area of research with notable recent progress. Event mining includes a wide range of multimedia domains such as surveillance, meetings, broadcast, news, sports, documentary, and films, as well as personal and online media collections. Due to the variety and plenty of Event mining techniques, in this paper we suggest an analytical framework to classify event mining techniques and to evaluate them based on important functional measures. This framework could lead to empirical and technical comparison of event mining methods and development of more efficient structures at future.     

Hierarchy-Debug: a scalable statistical technique for fault localization

Considering the fact that faults may be revealed as undesired mutual effect of program predicates on each other, a new approach for localizing latent bugs, namely Hierarchy-Debug, is presented in this paper. To analyze the vertical effect of predicates on each other and on program termination status, the predicates are fitted into a logistic lasso model. To support scalability, a hierarchical clustering algorithm is applied to cluster the predicates according to their presence in different executions. Considering each cluster as a pseudo-predicate, a distinct lasso model is built for intermediate levels of the hierarchy. Then, we apply a majority voting technique to score the predicates according to their lasso coefficients at different levels of the hierarchy. The predicates with relatively higher scores are ranked as fault relevant predicates. To provide the context of failure, faulty sub-paths are identified as sequences of fault relevant predicates. The grouping effect of Hierarchy-Debug helps programmers to detect multiple bugs. Four case studies have been designed to evaluate the proposed approach on three well-known test suites, Space, Siemens, and Bash. The evaluations show that Hierarchy-Debug produces more precise results compared with prior fault localization techniques on the subject programs.     

Printed dual-band base station antenna for GSM/DCS/PCS/UMTS and LTE applications with dual polarization

A new design of the dual-band and dual-polarized base station antennas for supporting the mobile communication systems operating at the GSM/DCS/PCS/UMTS and LTE frequency bands is presented. A wide input impedance matching bandwidth is achieved due to a trident-shaped feeding technique. Two printed dipoles, which are located perpendicularly to each other and fed by stepped-microstrip lines, establish the proposed antenna. In addition, by locating a low-profile cavity-backed structure, as a metal reflector under the antenna, bidirectional radiations of the dipoles are switched to unidirectional radiations with an increase in the gain of the antenna. Measurement results indicate that the proposed antenna is suitable for base station applications at the operating frequencies of 800/900/1800/1900/2300 MHz. The isolation is better than 20 dB, and peak gains of 10.08 and 9.96 dBi are attained at port-1 and port-2, respectively. Furthermore, the HPBWs of the antenna in H-plane is more than 61° for each port. The overall dimension of the antenna is 168 × 168 mm², which is mounted upon a 222 × 222 mm² cavity-backed structure with a depth of 42 mm.     

Fault diagnosis of an automobile cylinder head using low frequency vibrational data

This paper proposes a vibration-based fault-diagnosis method for mechanical parts. This method, after algorithm development, only requires a single inexpensive test to inspect the part which could take as short as half a second. The algorithm is developed in three major stages, (i) exciting specimens without or with known faults using a controlled force and recording acceleration of a single point for a short time (ii) finding a signature for each faulty specimen, using Fourier transform and statistical analysis. (iii) Developing a multi-layer perceptron, as a mathematical model, using the results of stage (ii). The elements of a part signature are the inputs to the model. The location (and possibly size and shape factor) of the fault is model output. Stage (i) can be performed experimentally or alternatively with a validated FEM, one experiment or simulation per specimen. The proposed technique was examined to locate (isolate) a fault on an automobile cylinder head. The presented accuracy is considerable, and the data collected at fairly low frequency range (below 1200 Hz) were found to be sufficient for this technique. In the case study of this paper, possible fault locations are on a line; as a result, fault location has one dimension. It is shown that the technique can be extended to higher dimensions.     

Highly selective optical nitrite sensor for food analysis based on Lauth’s violet-triacetyl cellulose membrane film

A new sensor has been developed for the determination of nitrite based on the immobilisation of Lauth’s violet on triacetyl cellulose membrane using absorption spectrophotometry. The optical sensor signal is based on the reaction of Lauth’s violet with bromate as an oxidant in the presence of nitrite to produce a colourless product. Nitrite has a strong catalytic effect on the oxidation of Lauth’s violet with bromate in acidic media. The difference in the absorbance of the optode at 617 nm between uncatalysed and catalysed reactions (ΔA) was directly proportional to the concentration of nitrite in sample solution. A linear calibration curve (r² = 0.985) was observed in the nitrite concentration range of 10.12-1012 ng mL⁻¹ and a detection limit of 8.3 ng mL⁻¹ was found.     

Comparative study of conductometric glucose biosensor based on gold and on magnetic nanoparticles

The aim of this study was to show the feasibility and the performances of nanoparticle biosensing. A glucose conductometric biosensor was developed using two types of nanoparticles (gold and magnetic), glucose oxidase (GOD) being adsorbed on PAH (poly(allylamine hydrochloride)) modified nanoparticles, deposited on a planar interdigitated electrode (IDEs). The best sensitivities for glucose detection were obtained with magnetic nanoparticles (70 μM/mM and 3 μM of detection limit) compared to 45 μM/mM and 9 μM with gold nanoparticles and 30 μM/mM and 50 μM with GOD directly cross-linked on IDEs. When stored in phosphate buffer (20 mM, pH 7.3) at 4 °C, the biosensor showed good stability for more than 12 days.     

Developing a method to generate semi-distributed layouts by genetic algorithm

Recent research in industries shows that existing layout configurations do not satisfy the needs of multi-product enterprises in turbulent environments but within new layout strategies, distributed layouts have deserved more attention in most manufacturing environments and have a promising potential to cope with demand disturbances. This study is an attempt to design weighted distributed layouts via considering machine independent capabilities by a resource elements (REs) approach, which has caused generation of a new type of distributed layout named semi-distributed layout. REs are used to define processing requirements of parts and processing capabilities of machines. Another contribution of this paper is applying genetic algorithms (GAs) to distribute REs to find the optimal assignment of machines to available locations in such a way the travelled distances of parts are minimised and the accessibility of them to the required machines are maximised. The methodology of this paper is illustrated using a two-phase procedure. First, all machining facilities are divided into a set of REs based on their capabilities and second, the weighted connections among REs are considered to distribute them over the floor through implementing the developed GA. To evaluate the methodology, the proposed algorithm is tested with three illustrative examples obtained from the literature, in which two of them are comparable with outputs of simulated annealing (SA). The comparison between the outputs of the GA and the SA on the same cases presents that for large size problems, the GA significantly outperforms the SA.