Parametric Study of Two-Body Floating-Point Wave Absorber

In this paper, we present a comprehensive numerical simulation of a point wave absorber in deep water. Analyses are performed in both the frequency and time domains. The converter is a two-body floating-point absorber （FPA） with one degree of freedom in the heave direction. Its two parts are connected by a linear mass-spring-damper system. The commercial ANSYS-AQWA software used in this study performs well in considering validations. The velocity potential is obtained by assuming incompressible and irrotational flow. As such, we investigated the effects of wave characteristics on energy conversion and device efficiency, including wave height and wave period, as well as the device diameter, draft, geometry, and damping coefficient. To validate the model, we compared our numerical results with those from similar experiments. Our study results can clearly help to maximize the converter＇s efficiency when considering specific conditions.

ASIC Design of Floating-Point FFT Processor

An application specific integrated circuit (ASIC) design of a 1024 points floating-point fast Fourier transform(FFT) processor is presented. It can satisfy the requirement of high accuracy FFT result in related fields. Several novel design techniques for floating-point adder and multiplier are introduced in detail to enhance the speed of the system. At the same time, the power consumption is decreased. The hardware area is effectively reduced as an improved butterfly processor is developed. There is a substantial increase in the performance of the design since a pipelined architecture is adopted, and very large scale integrated (VLSI) is easy to realize due to the regularity. A result of validation using field programmable gate array (FPGA) is shown at the end. When the system clock is set to 50 MHz, 204.8 μs is needed to complete the operation of FFT computation.

PHUI-GA: GPU-based efficiency evolutionary algorithm for mining high utility itemsets

Evolutionary algorithms(EAs)have been used in high utility itemset mining(HUIM)to address the problem of discover-ing high utility itemsets(HUIs)in the exponential search space.EAs have good running and mining performance,but they still require huge computational resource and may miss many HUIs.Due to the good combination of EA and graphics processing unit(GPU),we propose a parallel genetic algorithm(GA)based on the platform of GPU for mining HUIM(PHUI-GA).The evolution steps with improvements are performed in central processing unit(CPU)and the CPU intensive steps are sent to GPU to eva-luate with multi-threaded processors.Experiments show that the mining performance of PHUI-GA outperforms the existing EAs.When mining 90%HUIs,the PHUI-GA is up to 188 times better than the existing EAs and up to 36 times better than the CPU parallel approach.

Performance analysis on a novel water chiller using liquid desiccant

A new type of liquid desiccant water chiller for applications on air-conditioning and refrigeration is introduced.The system can be driven by low-grade heat sources with temperatures of 60 to 80 ℃,which can be easily obtained by a flat plat solar collector,waste heat,etc.A numerical model is developed to study the system performance.The effects of different parameters on performance are discussed,including evaporating temperature,regenerating temperature,ambient condition,and mass flow rates of closed moist air and regenerating air.The results show that an acceptable performance of a cooling capacity of 2.5 kW and a coefficient of performance of 0.37 can be achieved in a reference case.The regenerating temperature and the humidity ratios of ambient air are two main factors affecting system performance,while the temperature of ambient air functions less.In addition,the mass flow rate of regenerating air and closed moist air should be carefully determined for economical operation.

Design of area and power efficient Radix-4 DIT FFT butterfly unit using floating point fused arithmetic

In this work, power efficient butterfly unit based FFT architecture is presented. The butterfly unit is designed using floating-point fused arithmetic units. The fused arithmetic units include two-term dot product unit and add-subtract unit. In these arithmetic units, operations are performed over complex data values. A modified fused floating-point two-term dot product and an enhanced model for the Radix-4 FFT butterfly unit are proposed. The modified fused two-term dot product is designed using Radix-16 booth multiplier. Radix-16 booth multiplier will reduce the switching activities compared to Radix-8 booth multiplier in existing system and also will reduce the area required. The proposed architecture is implemented efficiently for Radix-4 decimation in time(DIT) FFT butterfly with the two floating-point fused arithmetic units. The proposed enhanced architecture is synthesized, implemented, placed and routed on a FPGA device using Xilinx ISE tool. It is observed that the Radix-4 DIT fused floating-point FFT butterfly requires 50.17% less space and 12.16% reduced power compared to the existing methods and the proposed enhanced model requires 49.82% less space on the FPGA device compared to the proposed design. Also, reduced power consumption is addressed by utilizing the reusability technique, which results in 11.42% of power reduction of the enhanced model compared to the proposed design.

Joint TDOA and AOA location algorithm

For the joint time difference of arrival（TDOA） and angle of arrival（AOA） location scene,two methods are proposed based on the rectangular coordinates and the polar coordinates,respectively.The problem is solved perfectly by calculating the target position with the joint TDOA and AOA location.On the condition of rectangular coordinates,first of all,it figures out the radial range between target and reference stations,then calculates the location of the target.In the case of polar coordinates,first of all,it figures out the azimuth between target and reference stations,then figures out the radial range between target and reference stations,finally obtains the location of the target.Simultaneously,simulation analyses show that the theoretical analysis is correct,and the proposed methods also provide the application of the joint TDOA and AOA location algorithm with the theoretical basis.

An improved boundary element method for modelling a self-reacting point absorber wave energy converter

A numerical model based on a boundary element method (BEM) is developed to predict the performance of two-body selfreacting floating-point absorber (SRFPA) wave energy systems that operate predominantly in heave.The key numerical issues in applying the BEM are systematically discussed.In particular,some improvements and simplifications in the numerical scheme are developed to evaluate the free surface Green's function,which is a main element of difficulty in the BEM.For a locked SRFPA system,the present method is compared with the existing experiment and the Reynolds-averaged NavierStokes (RANS)-based method,where it is shown that the inviscid assumption leads to substantial over-prediction of the heave response.For the unlocked SRFPA model we study in this paper,the additional viscous damping primarily induced by flow separation and vortex shedding,is modelled as a quadratic drag force,which is proportional to the square of body velocity.The inclusion of viscous drag in present method significantly improves the prediction of the heave responses and the power absorption performance of the SRFPA system,obtaining results excellent agreement with experimental data and the RANS simulation results over a broad range of incident wave periods,except near resonance in larger wave height scenarios.It is found that the wave overtopping and the re-entering impact of out-of-water floating body are observed more frequently in larger waves,where these non-linear effects are the dominant damping sources and could significantly reduce the power output and the motion responses of the SRFPA system.

Signalized Corridor Timing Plan Change Assessment Using Connected Vehicle Data

Updates to traffic signal timing plans are expected to either improve operations or mitigate the effects of increased volumes. Longitudinal before-after studies are important when validating changes to traffic signal systems, but they have historically required field data collection as well as deployment of extensive detection and communication equipment. These infrastructure-based techniques are costly and hard to scale. This study utilizes commercially available connected vehicle (CV) trajectory data to assess the change in performance between August 2020 and August 2021 on a 22-intersection corridor associated with the implementation of a semi-automated adaptive control system. Approximately 1 million trajectories and 13.5 million GPS points are analyzed for weekdays in August 2020 and August 2021. The vehicle trajectory data is used to compute corridor travel times and linear referenced relative to the far side of each intersection to generate Purdue Probe Diagrams (PPD). Using the PPDs, operational measurements such as arrivals on green (AOG), split failures (SF), and downstream blockage (DSB) are calculated. Additionally, traditional Highway Capacity Manual (HCM) level of service (LOS) is estimated. Even though there was a 35% increase in annual average daily traffic (AADT), the weighted average vehicle delay only increased by two seconds, LOS did not change, AOG improved by 1%, and SF and DSB remained the same. Based on the small changes in operational performance and considering the increase in traffic volume it is concluded that the implementation of the semi-automated adaptive control system had a significant positive impact in the corridor. The presented framework can be utilized by agencies to use CV data to perform before-after studies to evaluate the impact of signal timing plan changes. The presented methodology can be applied to any location where CV trajectory data is available.

Entangled quantum heat engine based on two-qubit Heisenberg XY model

Based on a two-qubit isotropic Heisenberg XY model under a constant external magnetic field,we construct a four-level entangled quantum heat engine（QHE）.The expressions for the heat transferred,the work,and the efficiency are derived.Moreover,the influence of the entanglement on the thermodynamic quantities is investigated analytically and numerically.Several interesting features of the variations of the heat transferred,the work,and the efficiency with the concurrences of the thermal entanglement of two different thermal equilibrium states in zero and nonzero magnetic fields are obtained.

WEAR PERFORMANCE AND MECHANISM OF ZINC-ALUMINUM（ZA27）ALLOY

ZA27 alloy has the best performance and the widest applications in high aluminum zinc based die casting alloy series. One of its main applica-tions is used as abrasion resistant alloy,instead of nonferrous alloys such as copper alloy.The frictional wear p

A Short-Term Stock Exchange Prediction Model Using Box-Jenkins Approach

This paper developed a short-term stock exchange prediction model using the Box-Jenkins approach. In this study, monthly data from Ghana Stock Exchange market report that spans from March 2013 to February 2018 were used to develop the model. ARIMA (0, 2, 1) model was fitted to the data based on the Bayesian Information Criterion (BIC) for model selection. Diagnostic checks showed that the residuals of the fitted model were uncorrelated. The developed model was used for forecasting for a period of six months. The trend of the forecasted values showed a significant increase in the Ghana Stock Exchange performance for the next six months.

A blind modulation recognition algorithm based on cyclic spectral correlation

Cyclic spectral correlation above the bifrequency plane for the received signal was calculated by the strip spectral correlation algorithm （SSCA）and then was normalized. The result was expressed by matrix. The sum of error-square was computed between corresponding elements for the theoretical sampling matrix of all kinds of modulated signals and calculated matrix. The modulation type was recognized by exploiting the minimum value of the sum of error-square. No extracted characteristic parameter and prior information are needed for identifying the modulation type compared to the conventional methods. In addition, the new method extends the recognition scope and has high recognition probability at low SNR. The simulation results obtained by means of Monter-Carlo method proved the presented algorithm.

A Novel Statistical Power Model for Integrated GPU with Optimization

GPUs are of increasing interests in the multi-core era due to their high computing power. However, the power consumption caused by the rising performance of GPUs has been a general concern. As a consequence, it is becoming an imperative demand to optimize the GPU power consumption, among which the power consumption estimation is one of the important and useful solutions. In this work, we present a novel statistical model that is capable of dynamically estimating the power consumption of the AMD's integrated GPU (iGPU). Precisely, we adopt the linear regression for power consumption modeling and propose a mechanism called kernel extension to lengthen the kernel execution time so that we can sample system data for model evaluation. The results show that the median absolute error of our model is less than 3%. Furthermore,to reduce the latency of power consumption estimation, we conduct a study to explore the possibility to simplify our statistical model. The results suggest that the accuracy and stability is still acceptable in the simplified model. This provides a desirable option to reduce our model latency when it is applied to the iGPU power consumption optimization in the real world.

Effect of Sleep Deprivation on Eye Movement Behavior in Flight Simulation

To examine the effect of sleep deprivation （SD） on eye movement be- havior in flight task, four subjects who were skilled in flight simulator participated in the experiment, which were asked to perform a level flight task in a flight simulator. Eye movement data and flight performance data were measured at the following hours： 11：00, 15：00, 04：00, 11：00, 15：00. The subjects workload and fatigue were assessed with the method of national aeronautics and space administration-task load index （NASA-TLX） and rating of perceived exertion （RPE）. Eye movement indices of average pupil area, av- erage saceade amplitude and average saccade velocity decreased during the 32 h of SD and they all showed significantly change in the final SD while the index of average fixa- tion time increased in the final SD. Flight performance deteriorated during the 32 h of SD, but not significantly. The feeling of fatigue and workload reported by subjects both increased during the 32 h of SD. Daily rhythm effects on the measured indices were also found, there were a obviously change at the hour of 04：00. 32 h of SD has obvious effect on eye movement behaviors which have close relation to fatigue because of SD. The eye movement measurement can be served as a tool to continually monitor fatigue online.

A nonlinear triboelectric nanogenerator with a broadened band-width for effective harvesting of vibration energy

A narrow resonance bandwidth of an energy harvesters limits its response to the wide frequency spectrum in ambient environ-ments.This work proposes an addition of a nonlinear restoring force applied to a triboelectric nanogenerator(TENG)to tune and broaden the resonance bandwidth.This restoring force is applied by permanent magnets at both sides of the slider and two external magnets.The noncontact strategy is adopted between the slider and the grating electrodes to avoid the wear of electrodes and energy loss caused by friction.The results show that compared with the linear system,the nonlinear noncontact TENG(NN-TENG)can increase the peak current from 6.3μA to 7.89μA,with an increment of about 25%,increase the peak power from 650μW to 977μW,increasing by about 50%,and increase the bandwidth from 0.5 Hz to 7.75 Hz,increasing by about1400%.This work may enable a new strategy to boost the bandwidth and output power of TENG through nonlinear oscillators.

Progress in research on ice accretions on overhead transmission lines and its influence on mechanical and insulating performance

Atmospheric ice accretion on transmission lines is of great danger to the security of service of electrical power system. This paper reviews the progress in research dealing with the formation of ice accretions on transmission lines and the effects of ice on the mechanical and electrical performance of transmission lines. The results show that ice accretions on transmission lines can be categorized into five types： glaze, hard rime, soft rime, hoar frost, and snow and sleet. In all types of ice accretions, glaze grown in a wet regime is of the greatest danger to the transmission lines. Meteorological conditions, terrain and geographic conditions, and some other factors significantly influence the ice accumulation speed and the ice amount. Drastic decrease of mechanical property and electric property as a result of severe icing is the main reason for ice accidents. The amount of ice, the asymmetrical ice accretion, and the asynchronous ice shedding can considerably change the conductor strain, conductor sag, variation amount of the span, displacement of the insulator string, and the tension difference. The amount and type of ice, the uniformity of ice accumulation, and the con- ductivity of freezing water have significant influence on the flashover voltage of ice-covered insulators.

Molecular cloning and characterization of the putative Halloween gene Phantom from the small brown planthopper Laodelphax striatellus

Ecdysteroid hormone 20-hydroxyecdysone plays fundamental roles in in- sect postembryonic development and reproduction. Several cytochrome P450 mono- oxygenases （CYPs）, encoded by the Halloween genes, have been documented to be involved in ecdysteroidogenesis in representative insects in Diptera, Lepidoptera and Orthoptera. Here the putative Halloween gene Phantom （Phm, cyp306al） from a hemipteran insect species, the small brown planthopper Laodelphax striatellus, was cloned. LsPHM shows five insect conserved P450 motifs, that is, Helix-C, Helix-I, Helix-K, PERF and heme- binding motifs. Temporal and spatial expression patterns of LsPhm were evaluated by quantitative polymerase chain reaction. Through the fourth-instar and the early fifth-instar stages, LsPhm showed two expression peaks in day 2 and days 4-5 fourth-instar nymphs, and three troughs in day 1 and 3 fourth instars and day 1 fifth instars. On day 5 of the fourth-instar nymphs, LsPhm clearly had a high transcript level in the thorax where the prothoracic glands were located. Dietary introduction of double-stranded RNA （dsRNA） of LsPhm at the nymph stage successfully knocked down the target gene, decreased expres- sion level ofecdysone receptor （LsEcR） gene and caused a higher nymphal mortality rate and delayed development. Ingestion of 20-hydroxyecdysone on LsPhm-dsRNA-exposed nymphs did not increase LsPhm expression level, but almost completely rescued the LsEcR mRNA level, and relieved the negative effects on survival and development. Thus, our data suggest that the putative LsPhm encodes a ftmctional 25-hydroxylase that catalyzes the biosynthesis of ecdysteroids in L. striatellus.

Entry qualifications and academic performance of architecture students in Nigerian Polytechnics： Are the admission requirements still relevant？

The competence of fresh graduates of architecture has been continuously criticized by the industry for inadequate knowledge. This is often blamed on the poor standard of education evidenced by poor performances in professional and degree/diploma examinations conducted by various schools of architecture in the country. Although, factors responsible for the scenario are wetl documented in the literature, most of these works are based on testimonial and circumstantial evidences relating to management of architectural education only. The aim of this paper is to investigate the relationship between entry qualifications and the performance of architecture students in Nigerian Polytechnics with a view to determining the relevance of current admission policy to architectural education in Nigeria. Data were obtained from official records in the Department of Architecture in four randomly selected polytechnics in the southwestern part of Nigeria. Pearson Product Moment Corretation （r） was used to test the hypotheses. Findings reveal weak relationship between the two variables （physics and mathematics）. This is contrary to the expectations of most schotars and policy makers who opine that studentst proficiency in these subjects would enhance their performance at higher LeveLs. The paper traces the contradiction to the poor handling of public examinations and misconception of architecture as being pure science. It holds that if these requirements are still relied upon for the admission of students into schools of architecture, wrong candidates wouldcontinue to gain entry into the profession. The paper concludes by recommending certain measures that are capable of reversing the trend.

Model adjointization and its cost

In this article, the least program behavior decomposition method (LPBD) is put forward from a program structure point of view. This method can be extensively used both in algorithms of automatic differentiation (AD) and in tools design, and does not require programs to be evenly separable but the cost in terms of operations count and memory is similar to methods using checkpointing. This article starts by summarizing the rules of adjointization and then presents the implementation of LPBD. Next, the definition of the separable program space, based on the fundamental assumptions (FA) of automatic differentiation, is given and the differentiation cost functions are derived. Also, two constants of fundamental importance in AD, s and m, are derived under FA. Under the assumption of even separability, the adjoint cost of simple and deep decomposition is subsequently discussed quantitatively using checkpointing. Finally, the adjoint costs in terms of operations count and memory through the LPBD method are shown to be uniformly dependent on the depth of structure or decomposition.

Parallel Error Detection for Leading Zero Anticipation

The algorithm and its implementation of the leading zero anticipation （LZA） are very vital for the performance of a high-speed floating-point adder in today＇s state of art microprocessor design. Unfortunately, in predicting ＂shift amount＂ by a conventional LZA design, the result could be off by one position. This paper presents a novel parallel error detection algorithm for a general-case LZA. The proposed approach enables parallel execution of conventional LZA and its error detection, so that the error-indicatlon signal can be generated earlier in the stage of normalization, thus reducing the critical path and improving overall performance. The circuit implementation of this algorithm also shows its advantages of area and power compared with other previous work.