An Efficient Spectral Leakage Filtering for IEEE 802.11af in TV White Space

Orthogonal frequency division multiplexing (OFDM) has been widely adopted for modern wireless standards and become a key enabling technology for cognitive radios. However, one of its main drawbacks is significant spectral leakage due to the accumulation of multiple sinc-shaped subcarriers. In this paper, we present a novel pulse shaping scheme for efficient spectral leakage suppression in OFDM based physical layer of IEEE 802.11af standard. With conventional pulse shaping filters such as a raised-cosine filter, vestigial symmetry can be used to reduce spectral leakage very effectively. However, these pulse shaping filters require long guard interval, i.e., cyclic prefix in an OFDM system, to avoid inter-symbol interference (ISI), resulting in a loss of spectral efficiency. The proposed pulse shaping method based on asymmetric pulse shaping achieves better spectral leakage suppression and decreases ISI caused by filtering as compared to conventional pulse shaping filters

A Survey on Some Parameters of Beef and Buffalo Meat Quality

A survey was carried out on 13 Vietnamese Yellow cattle, 14 LaiSind cattle and 18 buffalos in Hanoi to estimate the quality of longissimus dorsi in terms of pH, color, drip loss, cooking loss and tenderness at 6 different postmortem intervals. It was found that the pH value of longissimus dorsi was not significantly different among the 3 breeds (P>0.05), being reduced rapidly during the first 36 hours postmortem, and then stayed stable. The value was in the range that was considered to be normal. Conversely, the color values L*, a* and b* tended to increase and also stable at 36 hours postmortem, except that for LaiSind cattle at 48 hours. According to L* scale, the meat of Yellow and LaiSind cattle met the normal quality but the buffalo meat was considered to be dark cutters. The tenderness of longissimus dorsi was significantly different among the breeds (P<0.05). The value was highest at 48 hours and then decreased for LaiSind and buffalo, but for Yellow cattle the value decreased continuously after slaughtering In terms of tenderness buffalo meat and Yellow cattle meat were classified as “intermediate”, while LaiSind meat was out of this interval and classified as “tough”. Drip loss ratio was increased with the time of preservation (P<0.05). The cooking loss ratio was lowest at 12 hours and higher at the next period, but there was no significant difference among the periods after 36 hours postmotem.Peer reviewe

Bounded Guaranteed Algorithms for Concave Impurity Minimization Via Maximum Likelihood

Partitioning algorithms play a key role in many scientific and engineering disciplines. A partitioning algorithm divides a set into a number of disjoint subsets or partitions. Often, the quality of the resulted partitions is measured by the amount of impurity in each partition, the smaller impurity the higher quality of the partitions. In general, for a given impurity measure specified by a function of the partitions, finding the minimum impurity partitions is an NP-hard problem. Let $M$ be the number of $N$-dimensional elements in a set and $K$ be the number of desired partitions, then an exhaustive search over all the possible partitions to find a minimum partition has the complexity of $O(K^M)$ which quickly becomes impractical for many applications with modest values of $K$ and $M$. Thus, many approximate algorithms with polynomial time complexity have been proposed, but few provide bounded guarantee. In this paper, an upper bound and a lower bound for a class of impurity functions are constructed. Based on these bounds, we propose a low-complexity partitioning algorithm with bounded guarantee based on the maximum likelihood principle. The theoretical analyses on the bounded guarantee of the algorithms are given for two well-known impurity functions Gini index and entropy. When $K \geq N$, the proposed algorithm achieves state-of-the-art results in terms of lowest approximations and polynomial time complexity $O(NM)$. In addition, a heuristic greedy-merge algorithm having the time complexity of $O((N-K)N^2+NM)$ is proposed for $K<N$. Although the greedy-merge algorithm does not provide a bounded guarantee, its performance is comparable to that of the state-of-the-art methods. Our results also generalize some well-known information-theoretic bounds such as Fano's inequality and Boyd-Chiang's bound.Comment: 13 pages, 6 figure

Primary Evaluation on Growth Performances of Stress Negative Piétrain Pigs Raised in Hai Phong Province of Vietnam

peer reviewedThe present study was carried out on 19 stress negative Piétrain pigs (Pietrain ReHal), consisting of 13 gilts and 6 young boars imported from Belgium, raised in the livestock farm of Dong Hiep (Hai Phong) in order to evaluate growth performances and their adaptability in the North of Vietnam. Results showed that the average body weight of the whole herd at 2, 4, 5.5, and 8.5 months old was 19.05, 51.05, 85.82, and 119.47 kg, respectively. During the growing periods, except the first stage, the male grew faster than the female and the pigs of the CT genotype grew faster than those of CC genotype although the difference was not significant (P>0.05). The average daily gain (ADG) was 528.56 grams for the whole herd. The ADG was higher for the male (546.48 grams) than for the female (520.29 grams), and its was higher for the CT than the CC, but the difference was not statistically significant (P>0.05). The feed conversion ratio (FCR) was 2.69 kg. The estimated lean percentage at 8.5 months old was 64.08%. The results indicate that Piétrain stress negative pigs could develop well on the farm conditions in Hai Phong, Vietnam

Selecting lubricating oil for two-stroke gasoline engines: a multi-criteria decision-making approach

The two-stroke engine boasts advantages in terms of simpler manufacturing and a smaller size when compared to the four-stroke engine. Vehicles powered by two-stroke engines can thus effortlessly overcome road obstacles compared to their four-stroke counterparts. However, the use of a two-stroke engine results in higher carbon monoxide and hydrocarbon emissions than that of a four-stroke engine. This discrepancy places greater demands on the selection of lubricating oil for two-stroke engines compared to four-stroke engines. In market, there exists a multitude of lubricating oil options tailored for two-stroke engines, each characterized by varying technical parameters. These disparities are expressed through factors such as density, viscosity index, viscosity, and combustion temperature, among others. Consequently, the task of choosing the optimal lubricant becomes a complex endeavor for consumers. In this study, an examination of lubricant selection is presented using a Multi-Criteria Decision-Making (MCDM) approach. The MCDM method employed in this article is the Combined Compromise Solution (COCOSO) method. The selection of the best lubricant is based on an evaluation of four distinct types. Each type of oil is described by four key parameters (criteria): density, viscosity index, viscosity at 100&nbsp;°C, and viscosity at 40&nbsp;°C. The weights for these four criteria are determined through three different methods, including the Entropy method, Criteria Importance Through Intercriteria Correlation (CRITIC) method, and Standard Deviation (SD) method. Thus, the ranking of lubricants is conducted three times, corresponding to these three weighting methods. The results indicate that the best oil choice remains consistent regardless of the weighting method applie

Comparison of two methods in multi-criteria decision-making: application in transmission rod material selection

Transmission rod is an indispensable part in diesel and gasoline engines. Its job is to convert rotation into translational motion or vice versa. The transmission rod material selection plays a very important role, affecting its working function and durability. This study was conducted to compare two Multi Criteria Decision Making (MCDM) methods in transmission rod material selection. They are PIV (Proximity Indexed Value) method, and FUCA (Faire Un Choi Adéquat) method. Seven types of steel commonly used in transmission rods were reviewed for ranking, inclusive of: 20&nbsp;steel, 40&nbsp;steel, 45&nbsp;steel, 18Cr2Ni4WA steel, 30 CrMoA steel, 45Mn2 steel and 40CrNi steel. Nine parameters were used as criteria to evaluate each steel including minimum yield strength, ultimate tensile strength, minimum elongation ratio, contraction ratio, modulus of elasticity, mean coefficient of thermal expansion, thermal conductivity, specific thermal capacity, and density. The weights of the criteria were calculated using three methods inclusive of MEAN weight method, Entropy weight method and MEREC weight method (Method based on the Removal Effects of Criteria). Each MCDM method was combined with the three weight methods mentioned above to rank the alternatives. The obtained results show that when using both PIV and FUCA methods to rank the alternatives, the best and worst alternatives are found regardless of the weight of the criteria. The best alternative determined using the PIV method is also the best alternative determined using the FUCA method. It means that the two PIV and FUCA methods have been shown to be equally effective. Among the seven transmission rod materials reviewed, 20&nbsp;steel was identified as the best, and 40CrNi steel was identified as the wors

Calculation of axial mode separation of a semiconductor laser from reflectance spectrum

It is reported that the axial mode separation of a semiconductor laser can be computed from the reflectance spectrum of a narrow spectral range near the lasing frequency. The Kramers-Kronig dispersion relation is used in this computation. GaAs semiconductor laser is taken as an example. The computed values of the normalized frequency separation for GaAs at lasing photon energy of 1.38 eV range from 0.107 to 0.111 for various widths of the reflectance spectrum. These results are in good agreement with the measured ones

Enhancement of the Tracking Performance for Robot Manipulator by Using the Feed-forward Scheme and Reasonable Switching Mechanism

Robot manipulator has become an exciting topic for many researchers during several decades. They have investigated the advanced algorithms such as sliding mode control, neural network, or genetic scheme to implement these developments. However, they lacked the integration of these algorithms to explore many potential expansions. Simultaneously, the complicated system requires a lot of computational costs, which is not always supported. Therefore, this paper presents a novel design of switching mechanisms to control the robot manipulator. This investigation is expected to achieve superior performance by flexibly adjusting various strategies for better selection. The Proportional-Integral-Derivative (PID) scheme is well-known, easy to implement, and ensures rapid computation while it might not have much control effect. The advanced interval type-2 fuzzy sliding mode control properly deals with nonlinear factors and disturbances. Consequently, the PID scheme is switched when the tracking error is less than the threshold or is far from the target. Otherwise, the interval type-2 fuzzy sliding mode control scheme is activated to cope with unknown factors. The main contributions of this paper are (i) the recommendation of a suitable switching mechanism to drive the robot manipulator, (ii) the successful integration of the interval type-2 fuzzy sliding mode control to track the desired trajectory, and (iii) the launching of several tests to validate the proposed controller with robot model. From these achievements, it would be stated that the proposed approach is effective in tracking performance, robust in disturbance-rejection, and feasible in practical implementation

Towards enhanced surface roughness modeling in machining: an analysis of data transformation techniques

Data transformation methods are utilized to convert datasets into non-integer formats, potentially altering their distribution patterns. This implies that the variance and standard deviation of the dataset may be altered after the dataset undergoes data transformation operations. Improving model accuracy is a primary application of these methods. This study compares the efficacy of three data transformation techniques: square root transformation, logarithmic transformation, and inverse transformation. The comparison is conducted within the context of developing a surface roughness model for a turning process. Eighteen experiments are performed using the Box-Behnken method, with surface roughness chosen as the response variable. The surface roughness dataset undergoes transformation using the mentioned methods. Four surface roughness regression models are then built: one without transformation, one with square root transformation, one with logarithmic transformation, and one with inverse transformation. Evaluation metrics include coefficient of determination (R-Sq), adjusted coefficient of determination (R-Sq(adj)), Mean Absolute Error (%MAE), and Mean Squared Error (%MSE). Results indicate logarithmic transformation as the most effective, followed by square root transformation, in enhancing model accuracy. The surface roughness model utilizing data transformation exhibits high R-Sq and R-Sq(adj) values, at 0.8792 and 0.7434&nbsp;respectively. On the other hand, this model has&nbsp;%MAE and %MSE values of only 10.33 and 2.05&nbsp;respectively. Conversely, inverse transformation exhibits the least effectiveness among the three method