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The purpose of this paper is to introduce the analysis and performance of a hybrid multiple access scheme which combines interleave division multiple access (IDMA) and code division multiple access (CDMA), referred to as IDMA/CDMA. With experimentations, the scheme can achieve good performance with simple user ends for the system.

IDMA technique is employed as the uplink transmission and CDMA technique as the downlink transmission. The performance comparison of IDMA and IDMA/CDMA downlink is studied with Monte Carlo simulations to investigate the bit error rates. For IDMA/CDMA downlink, the signals are interleaved by random interleavers, spreaded by M‐sequence and orthogonal Gold sequence, respectively, and then transmitted over an AWGN with BPSK modulation. Moreover, a channel estimation approach for IDMA based on expectation maximization (EM) algorithm is also presented.

The multi‐user detection (MUD) algorithm in uplink IDMA systems is much simpler than that used in traditional CDMA systems. It is also well known that the orthogonal spreading codes in CDMA can effectively help suppress the MAI in the synchronized environments. But for the asynchronized application, the performance of CDMA systems will degrade due to the serious multiple user interference. According to traditional IDMA and orthogonal code division multiple access/IDMA signal detection algorithms, every UE has to detect all of the signals of other users for iterative detection. The advantages of IDMA and CDMA technologies can be utilized substantially.

The proposed hybrid multiple access scheme can achieve a very simple chip‐by‐chip iterative MUD strategy at base station, and the simplified receiving operation at UE. On the other hand, this paper also evaluates channel estimation approach for IDMA based on EM algorithm.

Epidemiologists are concerned the next deadly global cognition will be a new kind of deadly flu which humans have no resistance. Since the 1960s, their alarm has been focused on a bird (avian) virus (H5N1). This virus is generally harmless in its host species, but it is extremely deadly when contracted by humans. H5N1 mutates quickly and tends to pick up genes from flu viruses that affect other species. The flu is far more contagious and harder to contain than the SARS (severe acute respiratory syndrome) virus. It is projected that 30‐40 per cent of the population would be infected in a H5N1 flu pandemic, and as many as one‐third would die. The 1918 Spanish flu caused 20 to 50 million deaths world wide. One scientist observed that the 1918 Spanish flu pandemic could have caused civilisation to disappear within a few weeks. Currently, more than 50 million chickens have been slaughtered in eight Asian countries in efforts to curb the spread of avian influenza. This article examines the roots and dangers of the potential avian influenza pandemic, examining the business and social ramifications that could ensue if the worst case scenario occurs.

In the present research work electrochemical grinding (ECG) process is applied to machine Al₂O₃/Al interpenetrating phase composite. The purpose of this paper is to present a new approach to optimize the ECG process parameters while machining alumina-aluminum (Al₂O₃ – Al) interpenetrating phase composites (IPC) used in automotive, aircraft and manufacture of space ships applying Taguchi-based experimental studies and fuzzy multi-criteria decision-making techniques.

The present work identifies the process variables that have significant consequences during ECG of Al₂O₃/Al IPC. The Taguchi L₉ orthogonal array is selected for design of experiments and the analysis is carried out following signal to noise ratio. The analysis of variance is carried out to establish the factors that significantly influence the responses. The present work also investigates the multi objective optimization of ECG process parameters using VIseKriterijumsa Optimizacija I Kompromisno Resenje (VIKOR) and Grey relational analysis (GRA) to establish the reference ranking from a set of alternatives in the presence of conflicting criteria.

Material removal rate, surface finish, overcut and cutting force are shown to depend on the type of electrolyte, supply voltage, depth of cut and electrolyte flow rate. It is found that voltage and electrolyte concentration are important. The optimal machining parameter combination for ECG process is determined using fuzzy set theory, VIKOR and GRA. Substantial improvement in machining performance takes place.

A variety of manufacturing techniques are available for processing of Al₂O₃ – Al metal matrix composites. Generally manufacturers favor low cost modus operandi. Therefore ECG process is the best alternative for processing of MMCs in the present commercial sectors. The experimental investigation approach can act as useful and an efficient guideline for manufacturing.

The characteristic features of the ECG process are reflected through Taguchi design-based experimental studies with various process parametric combinations. Application of multi-response optimization technique for evaluation of best parametric combination for machining Al₂O₃ – Al IPC material using ECG process is a first-of-its-kind approach in literature.

This research outlines the Hong Kong film industry with examination of key actors, directors, films, and production companies within the martial arts genre of Hong Kong Action Cinema. Hong Kong Film Award winners and nominees, core films within genres, and core reference works both general and theoretical from experts in the field of Hong Kong martial arts film research have been highlighted. Web sites are suggested that provide reviews of Hong Kong martial arts films, biographical information on a variety of actors and actresses as well as comprehensive bibliographic information on select films. Also included are commercial Web sites that provide Hong Kong martial arts films.

Most academic libraries provide book recommendation services to enable readers to recommend books to the libraries. To facilitate decision-making in book acquisition, this study aimed to develop a method to determine the ranking of the recommended books based on the recommender network.

The recommender network was conducted to establish relationships among book recommenders and their similar readers by using circulation records. Furthermore, social computing techniques were used to evaluate the degree of representativeness of the recommenders and subsequently applied as a criterion to rank the recommended books. Empirical studies were performed to demonstrate the effectiveness of the proposed ranking system. The Spearman’s correlation coefficients between the proposed ranking system and the ranking obtained using reader circulation statistics were used as performance measure.

The ranking calculated using the proposed ranking mechanism was highly and moderately correlated to the ranking obtained using reader circulation statistics. The ranking of recommended books by the librarians was moderately and poorly correlated to the ranking calculated using reader circulation statistics.

The book recommender can be used to improve the accuracy of book recommendations.

This study is the first that considers the recommender network on library book acquisition. The results also show that the proposed ranking mechanism can facilitate effective book-acquisition decisions in libraries.

Engineering system design and optimization problems are usually multi-objective and constrained and have uncertainties in the inputs. These uncertainties might significantly degrade the overall performance of engineering systems and change the feasibility of the obtained solutions. This paper aims to propose a multi-objective robust optimization approach based on Kriging metamodel (K-MORO) to obtain the robust Pareto set under the interval uncertainty.

In K-MORO, the nested optimization structure is reduced into a single loop optimization structure to ease the computational burden. Considering the interpolation uncertainty from the Kriging metamodel may affect the robustness of the Pareto optima, an objective switching and sequential updating strategy is introduced in K-MORO to determine (1) whether the robust analysis or the Kriging metamodel should be used to evaluate the robustness of design alternatives, and (2) which design alternatives are selected to improve the prediction accuracy of the Kriging metamodel during the robust optimization process.

Five numerical and engineering cases are used to demonstrate the applicability of the proposed approach. The results illustrate that K-MORO is able to obtain robust Pareto frontier, while significantly reducing computational cost.

The proposed approach exhibits great capability for practical engineering design optimization problems that are multi-objective and constrained and have uncertainties.

A K-MORO approach is proposed, which can obtain the robust Pareto set under the interval uncertainty and ease the computational burden of the robust optimization process.

This paper aims to perform experimental test on fatigue characteristics of package on package (POP) stacked chip assembly under thermal cycling load. Some suggestions for design to prolong fatigue life of POP stacked chip assembly are provided.

The POP stacked chip assembly which contains different package structure mode and chip position was manufactured. The fatigue characteristics of POP stacked chip assembly under thermal cycling load were tested. The fatigue load spectrum of POP stacked chip assembly under thermal cycling load was given. The fatigue life of chips can be estimated by using the creep–fatigue life prediction model based on different stress conditions.

The solder joint stress of top package is significantly less than that of bottom solder joints, and the maximum value occurs in the middle part of the solder joints inner ring.

This paper fulfils useful information about the thermal reliability of POP stacked chip assembly with different structure characteristics and materials parameters.

Feature selection is an essential step in data mining. The core of it is to analyze and quantize the relevancy and redundancy between the features and the classes. In CFR feature selection method, they rarely consider which feature to choose if two or more features have the same value using evaluation criterion. In order to address this problem, the standard deviation is employed to adjust the importance between relevancy and redundancy. Based on this idea, a novel feature selection method named as Feature Selection Based on Weighted Conditional Mutual Information (WCFR) is introduced. Experimental results on ten datasets show that our proposed method has higher classification accuracy.

Individuals tend to simplify a complex portfolio decision problem into several manageable dimensions, each of which can frame their perception of risk.We check this view by studying the effect of investment horizons on households’ portfolio decisions. Using the Survey of Consumer Finances (SCF) data, we find that households allocate more of their wealth in stocks if they report longer planning horizons. The existence of foreseeable expenditure significantly changes the dependence of risky stock investment on the planning horizon.We decompose the reported planning horizon into an objective part and a subjective mental accounting part, and find that the mental accounting part has a greater effect on household portfolio choice. This is consistent with the argument that individuals make investment decisions based on the horizon at which the risk is perceived rather than the horizon at which the investment reward or cash is needed.

Engineering design optimization involving computational simulations is usually a time-consuming, even computationally prohibitive process. To relieve the computational burden, the adaptive metamodel-based design optimization (AMBDO) approaches have been widely used. This paper aims to develop an AMBDO approach, a lower confidence bounding approach based on the coefficient of variation (CV-LCB) approach, to balance the exploration and exploitation objectively for obtaining a global optimum under limited computational budget.

In the proposed CV-LCB approach, the coefficient of variation (CV) of predicted values is introduced to indicate the degree of dispersion of objective function values, while the CV of predicting errors is introduced to represent the accuracy of the established metamodel. Then, a weighted formula, which takes the degree of dispersion and the prediction accuracy into consideration, is defined based on the already-acquired CV information to adaptively update the metamodel during the optimization process.

Ten numerical examples with different degrees of complexity and an AIAA aerodynamic design optimization problem are used to demonstrate the effectiveness of the proposed CV-LCB approach. The comparisons between the proposed approach and four existing approaches regarding the computational efficiency and robustness are made. Results illustrate the merits of the proposed CV-LCB approach in computational efficiency and robustness.

The proposed approach exhibits high efficiency and robustness in engineering design optimization involving computational simulations.

CV-LCB approach can balance the exploration and exploitation objectively.