Neural Network and Classification Approach in Identifying Customer Behavior in the Banking Sector: A Case Study of an International Bank

The customer relationship focus for banks is in development of main competencies and strategies of building strong profitable customer relationships through considering and managing the customer impression, influence on the culture of the bank, satisfactory treatment, and assessment of valued relationship building. Artificial neural networks (ANNs) are used after data segmentation and classification, where the designed model register records into two class sets, that is, the training and testing sets. ANN predicts new customer behavior from previously observed customer behavior after executing the process of learning from existing data. This article proposes an ANN model, which is developed using a six‐step procedure. The back‐propagation algorithm is used to train the ANN by adjusting its weights to minimize the difference between the current ANN output and the desired output. An evaluation process is conducted to determine whether the ANN has learned how to perform. The training process is halted periodically, and its performance is tested until an acceptable result is obtained. The principles underlying detection software are grounded in classical statistical decision theory.     

Confirmation Bias in Online Searches: Impacts of Selective Exposure Before an Election on Political Attitude Strength and Shifts

Impacts of Internet use on political information seeking and subsequent processes have been subject to much debate. A 2‐session online field study presented online search results on political topics to examine selective exposure and its attitudinal impacts. Session 1 captured attitudes, including their accessibility. Session 2 tracked what online search results participants selected and how long they read them; participants then reported attitudes again. The study represented a 4x8x2x2 within‐subjects design: 4 topics, 8 browsing intervals each, with articles presenting opposing stances, with low versus high source credibility. Attitude‐consistent messages and messages from high‐credibility sources were preferred. Exposure to attitude‐consistent search results increased attitude accessibility and reinforced attitudes, whereas exposure to attitude‐discrepant content had opposite effects, regardless of messages' source credibility.     

A User‐Centric Evaluation Procedure for the Design of Child‐Resistant Medicine Bottles

Recently, people have begun to realize the importance of child‐resistant (CR) medicine packaging. However, most manufacturers and designers have not been able to effectively provide prevention strategies or design criteria to protect consumers. This research proposes a systematic approach to analyze CR packaging design problems and experiments to evaluate the identified design parameters and to generate the most suitable CR medicine packaging design. The design of a CR packaging bottle is used as an example to help explain the development procedure. During the development procedure, user trials, questionnaires, and children's anthropometric data on bottle opening and hand operations are analyzed. Five design parameters, specifically the cap diameter, cap height, bottle height, bottle diameter, and torsion, are identified and used to perform a Taguchi orthogonal array experimental analysis. A computer‐aided design system is also built to help generate the most suitable design alternatives. The results should assist designers in determining the most important CR design parameters and their most suitable combinations for bottle and related CR medicine packaging design.     

Is It Possible to Retain Customer Loyalty When a Service Has Failed?

This article aims to analyze the impact of recovery on loyalty in the context of a service chain characterized by the e‐quality–perceived value–loyalty relationship. A sample of 91 out of 1,201 respondents claimed to have had service problems with an online travel agency website. A causal model to test relationships was performed using structural equations modeling, and it was found that data fit with the proposed model. The really important point to retaining customers is quality. It is not so clear that the recovery effort might affect loyalty. Our findings underpin some previous stream of literature confirming that recovery does not always affect loyalty. Although the literature has not reached a consensus in this topic, we add new elements in this debate.     

Design of a printed log‐periodic dipole array antenna with high gain for millimeter‐wave applications

In this article, a V‐band printed log‐periodic dipole array (PLPDA) antenna with high gain is proposed. The antenna prototype is designed, simulated, fabricated, and tested. Simulation results show that this antenna can operate from 42 to 82 GHz with a fractional impedance bandwidth of 64.5% covering the whole V‐band (50–75 GHz). The antenna has a measured impedance matching bandwidth that starts from 42 to beyond 65 GHz with good agreement between the experimental and simulated results. At 50 and 65 GHz, the antenna has a measured gain of 10.45 and 10.28 dBi, respectively, with a gain variation of 2.6 dBi across the measured frequency range. The antenna prototype exhibits also stable radiation patterns over the operating band. It achieves side‐lobe suppression better than 17.26 dB in the H‐plane and better than 8.95 dB in the E‐plane, respectively. In addition, the cross‐polarization component is 18.5 dB lower than the copolarization with front‐to‐back ratio lower than 24.1 dB in both E‐ and H‐planes across the desired frequency range. Based on a comparison of performance among the reported work in the literature, we can say that the proposed PLPDA antenna is a proper candidate to be used in many applications at V‐band frequency. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:185–193, 2015.     

Novel neural network modeling method and applications

Neural networks play an important role for designing the parametric model of electromagnetic structures. The current neural network methods are unfit for a circuit model with many input variables because it is costly to extract a large number of the training data and test data to complete the highly nonlinear mapping approximation. This article proposes a new neural network modeling method—the multidimensional neural network model, which can be used to solve the issue of multivariable radiofrequency and microwave passive device modeling. The entire multidimensional neural network modeling problem is simplified into a set of neural network submodels through decomposition method. Then the submodels are combined into an equivalent model, and the final entire model is produced through the neural‐network mapping model developed with the submodels and equivalent model. A microstrip hairpin filter model is developed using the proposed method. The simulation results show the correctness and the effectivity of the proposed method. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:769–779, 2015.     

Design of a compact dual‐band folded‐waveguide bandpass filter using multilayer waveguide resonators

A novel compact dual‐band bandpass filter based on multilayer folded‐waveguide (FWG) structure is presented in this article.In this design, slots are used to realize direct coupling between adjacent resonators and apertures are adopted to implement cross coupling between non‐adjacent resonators.A new technique of external quality factor of FWG resonator and coupling coefficients between different resonators are studied using full‐wave simulator. In order to demonstrate the proposed technique, a four‐pole dual‐band bandpass filter is designed, fabricated and measured using vector network analyzer. Measurement results which are well agreed with simulation results are presented. Moreover, four‐pole substrate integrated folded waveguide SIFW dual‐band bandpass filter, using two layers of slotted folded waveguide resonators, is demonstrated. The proposed filter has a compact size and it is excellent candidate for the application of wireless communication systems. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:780–788, 2015.     

Novel ultra‐compact two‐dimensional waveguide‐based metasurface for electromagnetic coupling reduction of microstrip antenna array

A novel ultracompact two‐dimensional (2D) waveguide‐based metasurface is proposed herein and applied for the first time to reduce mutual coupling in antenna array for multiple‐input multiple‐output applications. The unit cell of the proposed 2D waveguide‐based metasurface is ultracompact (8.6 mm × 4.8 mm, equal to λ₀/14.2 × λ₀/25.5) mainly due to the symmetrical spiral lines etched on the ground. The metasurface exhibits a bandgap with two transmission zeros attributing to the negative permeability in the vicinity of magnetic resonance and the negative permittivity in the vicinity of electric resonance. Taking advantage of these two features, a microstrip antenna array is then designed, fabricated, and measured by embedding an 8 × 1 array of the well‐engineered 2D waveguide‐based metasurface elements between two closely spaced (9.2 mm, equal to λ₀/13.3) H‐plane coupled rectangular patches. There is good agreement between the simulated and measured results, indicating that the metasurface effectively reduces antenna mutual coupling by more than 11.18 dB and improves forward gain. The proposed compact structure has one of the highest reported decoupling efficiencies among similar periodic structures with comparable dimensions. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:789–794, 2015.     

Exploring the Relationship Between Green Consumption Value,Satisfaction, and Loyalty to Hybrid Car in Elderly Consumers

The study aimed to examine the relationship between green consumption value, satisfaction, and loyalty of driving hybrid cars among elderly consumers. Data were collected from a cross‐sectional survey of 314 elderly consumers who purchased hybrid cars in the United States. A partial least squares analysis revealed that elderly consumers’ social, price, and quality values positively influenced the satisfaction of their hybrid car experience, and their satisfaction significantly influenced their loyalty of hybrid car. The relationship between green consumption value, satisfaction, and loyalty toward driving hybrid cars among elderly consumers revealed insight into their value orientations toward the hybrid car. Special efforts are suggested in promoting hybrid car use to elderly consumer groups. Marketers should pay attention to changing beliefs and increasing perceived values of driving a hybrid car for consumers to encourage them to use green products.     

Recurrent neural network technique for behavioral modeling of power amplifier with memory effects

A new technique for behavioral modeling of power amplifier (PA) with short‐ and long‐term memory effects is presented here using recurrent neural networks (RNNs). RNN can be trained directly with only the input–output data without having to know the internal details of the circuit. The trained models can reflect the behavior of nonlinear circuits. In our proposed technique, we extract slow‐changing signals from the inputs and outputs of the PA and use these signals as extra inputs of RNN model to effectively represent long‐term memory effects. The methodology using the proposed RNN for modeling short‐term and long‐term memory effects is discussed. Examples of behavioral modeling of PAs with short‐ and long‐term memory using both the existing dynamic neural networks and the proposed RNNs techniques are shown. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:289–298, 2015.