Effect of Partial Rootzone Drying on Growth, Yield and Biomass Partitioning of a Soilless Tomato Crop

The object of the present research was to assess the effects of partial rootzone drying (PRD) on tomato growth, productivity, biomass allocation and water use efficiency (WUE). Plants were grown under greenhouse, on a sand substrate. Three treatments were applied: a control that was fully and conventionally irrigated, PRD-70 and PRD-50 in which, respectively, 70% and 50% of water requirements were supplied using PRD. Alternation of irrigation between the two root halves took place each three days. The Control produces the highest total yield (252tons/ha). In terms of fruit number, PRD-50 showed 23% and 16% less fruits than PRD-70 and control, respectively. Fruit size was affected by treatment with PRD-50 treatment producing 66% and 53% more class 3 fruits than, control and PRD-70, respectively. For plant growth, the difference was not significant when comparing control to PRD-70 but was significant when comparing PRD-70 and control to PRD-50. No effect was on total biomass but root biomass was higher for stressed plants compared to control. WUE was 66% and 27% higher for PRD-50 and PRD-70 respectively compared to control.

Synthesis and Simulation of Enhanced Buffer Router vs. Virtual Channel Router in NOC ON Cadence

This paper presents a synthesis and simulation of proposed enhanced buffer. The design provides advantages of both buffer and bufferless network for that two cross bar switches are used. The concept of virtual channel (VC) is eliminated from the previous design by using an efficient flow-control scheme that uses the storage already present in pipelined channels in place of explicit input VCBs. This can be addressed by providing enhanced buffers on the bufferless link and creating two virtual networks. With this approach, VCBs act as distributed FIFO buffers. Without VCBs or VCs, deadlock prevention is achieved by duplicating physical channels. An enhanced buffer provides a function of hand shaking by providing a ready valid handshake signal and two bit storage. Through this design the power is reduced to 15.65% and delay is reduced to 97.88% with respect to virtual channel router.

On the Joint Optimization of Performance and Power Consumption in Data Centers

We model the process of a data center as a multi- objective problem of mapping independent tasks onto a set of data center machines that simultaneously minimizes the energy consump¬tion and response time (makespan) subject to the constraints of deadlines and architectural requirements. A simple technique based on multi-objective goal programming is proposed that guarantees Pareto optimal solution with excellence in convergence process. The proposed technique also is compared with other traditional approach. The simulation results show that the proposed technique achieves superior performance compared to the min-min heuristics, and com¬petitive performance relative to the optimal solution implemented in UNDO for small-scale problems.

Vision Based Hand Gesture Recognition Using Generative and Discriminative Stochastic Models

Many approaches to pattern recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the distribution of the image features. Generative and discriminative models have very different characteristics, as well as complementary strengths and weaknesses. In this paper, we study these models to recognize the patterns of alphabet characters (A-Z) and numbers (0-9). To handle isolated pattern, generative model as Hidden Markov Model (HMM) and discriminative models like Conditional Random Field (CRF), Hidden Conditional Random Field (HCRF) and Latent-Dynamic Conditional Random Field (LDCRF) with different number of window size are applied on extracted pattern features. The gesture recognition rate is improved initially as the window size increase, but degrades as window size increase further. Experimental results show that the LDCRF is the best in terms of results than CRF, HCRF and HMM at window size equal 4. Additionally, our results show that; an overall recognition rates are 91.52%, 95.28%, 96.94% and 98.05% for CRF, HCRF, HMM and LDCRF respectively.

Creeping Insulation - Hong Kong Green Wall

Hong Kong is a densely populated city suffering badly from the urban heat island effect. Green wall offers a means of ameliorating the situation but there are doubts over its suitability in Hong Kong’s unique environment. In this paper, we look at the potential for green walls in Hong Kong first by summarizing some of the Chinese green walling systems and associated vegetation in use, then by an introduction to three existing green walls in Hong Kong, and finally through a small experiment aimed at identifying the likely main effects of green walled housing. The results indicate that green walling in Hong Kong is likely to provide enhanced internal house environment in terms of warm weather temperature reduction, stabilization and damping, with direct energy savings in air-conditioning and indirect district benefits of reduced heat island effect and carbon emissions. The green walling insulation properties also suggest the possibility of warmer homes in winter and/or energy savings in mechanical heating provision.

An efficient Activity Network Reduction Algorithm based on the Label Correcting Tracing Algorithm

When faced with stochastic networks with an uncertain duration for their activities, the securing of network completion time becomes problematical, not only because of the non-identical pdf of duration for each node, but also because of the interdependence of network paths. As evidenced by Adlakha & Kulkarni [1], many methods and algorithms have been put forward in attempt to resolve this issue, but most have encountered this same large-size network problem. Therefore, in this research, we focus on network reduction through a Series/Parallel combined mechanism. Our suggested algorithm, named the Activity Network Reduction Algorithm (ANRA), can efficiently transfer a large-size network into an S/P Irreducible Network (SPIN). SPIN can enhance stochastic network analysis, as well as serve as the judgment of symmetry for the Graph Theory.

Study on the Effect of Volume Fraction of Dual Phase Steel to Corrosion Behaviour and Hardness

The objective of this project is to study the corrosion behaviour and hardness based on the presence of martensite in dual phase steel. This study was conducted on six samples of dual phase steel which have different percentage of martensite. A total of 9 specimens were prepared by intercritical annealing process to study the effect of temperature to the formation of martensite. The low carbon steels specimens were heated for 25 minutes in a specified temperature ranging from 7250C to 8250C followed by rapid cooling in water. The measurement of corrosion rate was done by using extrapolation tafel method, while potentiostat was used to control and measured the current produced. This measurement is performed through a system named CMS105. The result shows that a specimen with higher percentage of martensite is likely to corrode faster. Hardness test for each specimen was conducted to compare its hardness with low carbon steel. The results obtained indicate that the specimen hardness is proportional to the amount of martensite in dual phase steel.

Flagging Critical Components to Prevent Transient Faults in Real-Time Systems

This paper proposes the use of metrics in design space exploration that highlight where in the structure of the model and at what point in the behaviour, prevention is needed against transient faults. Previous approaches to tackle transient faults focused on recovery after detection. Almost no research has been directed towards preventive measures. But in real-time systems, hard deadlines are performance requirements that absolutely must be met and a missed deadline constitutes an erroneous action and a possible system failure. This paper proposes the use of metrics to assess the system design to flag where transient faults may have significant impact. These tools then allow the design to be changed to minimize that impact, and they also flag where particular design techniques – such as coding of communications or memories – need to be applied in later stages of design.

Incorporating Semantic Similarity Measure in Genetic Algorithm : An Approach for Searching the Gene Ontology Terms

The most important property of the Gene Ontology is the terms. These control vocabularies are defined to provide consistent descriptions of gene products that are shareable and computationally accessible by humans, software agent, or other machine-readable meta-data. Each term is associated with information such as definition, synonyms, database references, amino acid sequences, and relationships to other terms. This information has made the Gene Ontology broadly applied in microarray and proteomic analysis. However, the process of searching the terms is still carried out using traditional approach which is based on keyword matching. The weaknesses of this approach are: ignoring semantic relationships between terms, and highly depending on a specialist to find similar terms. Therefore, this study combines semantic similarity measure and genetic algorithm to perform a better retrieval process for searching semantically similar terms. The semantic similarity measure is used to compute similitude strength between two terms. Then, the genetic algorithm is employed to perform batch retrievals and to handle the situation of the large search space of the Gene Ontology graph. The computational results are presented to show the effectiveness of the proposed algorithm.

Heat-treated or Raw Sunflower Seeds in Lactating Dairy Cows Diets: Effects on Milk Fatty Acids Profile and Milk Production

The objective of this study was to investigate the effects of dietary supplementation with raw or heat-treated sunflower oil seed with two levels of 7.5% or 15% on unsaturated fatty acids in milk fat and performances of high-yielding lactating cows. Twenty early lactating Holstein cows were used in a complete randomized design. Treatments included: 1) CON, control (without sunflower oil seed). 2) LS-UT, 7.5% raw sunflower oil seed. 3) LS-HT, 7.5% heat-treated sunflower oil seed. 4) HS-UT, 15% raw sunflower oil seed. 5) HS-HT, 15% heat-treated sunflower oil seed. Experimental period lasted for 4 wk, with first 2 wk used for adaptation to the diets. Supplementation with 7.5% raw sunflower seed (LS-UT) tended to decrease milk yield, with 28.37 kg/d compared with the control (34.75 kg/d). Milk fat percentage was increased with the HS-UT treatment that obtained 3.71% compared with CON that was 3.39% and without significant different. Milk protein percent was decreased high level sunflower oil seed treatments (15%) with 3.18% whereas CON treatment is caused 3.40% protein. The cows fed added low sunflower heat-treated (LS-HT) produced milk with the highest content of total unsaturated fatty acid with 32.59 g/100g of milk fat compared with the HS-UT with 23.59 g/100g of milk fat. Content of C18 unsaturated fatty acids in milk fat increased from 21.68 g/100g of fat in the HS-UT to 22.50, 23.98, 27.39 and 30.30 g/100g of fat from the cow fed HS-HT, CON, LS-UT and LS-HT treatments, respectively. C18:2 isomers of fatty acid in milk were greater by LSHT supplementation with significant effect (P < 0.05). Total of C18 unsaturated fatty acids content was significantly higher in milk of animal fed added low heat-treated sunflower (7.5%) than those fed with high sunflower. In all, results of this study showed that diet cow's supplementation with sunflower oil seed tended to reduce milk production of lactating cows but can improve C18 UFA (Unsaturated Fatty Acid) content in milk fat. 7.5% level of sunflower oil seed that heated seemed to be the optimal source to increase UFA production.

A Mapping Approach of Code Generation for Arinc653-Based Avionics Software

Avionic software architecture has transit from a federated avionics architecture to an integrated modular avionics (IMA) .ARINC 653 (Avionics Application Standard Software Interface) is a software specification for space and time partitioning in Safety-critical avionics Real-time operating systems. Methods to transform the abstract avionics application logic function to the executable model have been brought up, however with less consideration about the code generating input and output model specific for ARINC 653 platform and inner-task synchronous dynamic interaction order sequence. In this paper, we proposed an AADL-based model-driven design methodology to fulfill the purpose to automatically generating Cµ executable model on ARINC 653 platform from the ARINC653 architecture which defined as AADL653 in order to facilitate the development of the avionics software constructed on ARINC653 OS. This paper presents the mapping rules between the AADL653 elements and the elements in Cµ language, and define the code generating rules , designs an automatic C µ code generator .Then, we use a case to illustrate our approach. Finally, we give the related work and future research directions.

Critical Assessment of Scoring Schemes for Protein-Protein Docking Predictions

Protein-protein interactions (PPI) play a crucial role in many biological processes such as cell signalling, transcription, translation, replication, signal transduction, and drug targeting, etc. Structural information about protein-protein interaction is essential for understanding the molecular mechanisms of these processes. Structures of protein-protein complexes are still difficult to obtain by biophysical methods such as NMR and X-ray crystallography, and therefore protein-protein docking computation is considered an important approach for understanding protein-protein interactions. However, reliable prediction of the protein-protein complexes is still under way. In the past decades, several grid-based docking algorithms based on the Katchalski-Katzir scoring scheme were developed, e.g., FTDock, ZDOCK, HADDOCK, RosettaDock, HEX, etc. However, the success rate of protein-protein docking prediction is still far from ideal. In this work, we first propose a more practical measure for evaluating the success of protein-protein docking predictions,the rate of first success (RFS), which is similar to the concept of mean first passage time (MFPT). Accordingly, we have assessed the ZDOCK bound and unbound benchmarks 2.0 and 3.0. We also createda new benchmark set for protein-protein docking predictions, in which the complexes have experimentally determined binding affinity data. We performed free energy calculation based on the solution of non-linear Poisson-Boltzmann equation (nlPBE) to improve the binding mode prediction. We used the well-studied thebarnase-barstarsystem to validate the parameters for free energy calculations. Besides,thenlPBE-based free energy calculations were conducted for the badly predicted cases by ZDOCK and ZRANK. We found that direct molecular mechanics energetics cannot be used to discriminate the native binding pose from the decoys.Our results indicate that nlPBE-based calculations appeared to be one of the promising approaches for improving the success rate of binding pose predictions.

Particle Filter Applied to Noisy Synchronization in Polynomial Chaotic Maps

Polynomial maps offer analytical properties used to obtain better performances in the scope of chaos synchronization under noisy channels. This paper presents a new method to simplify equations of the Exact Polynomial Kalman Filter (ExPKF) given in [1]. This faster algorithm is compared to other estimators showing that performances of all considered observers vanish rapidly with the channel noise making application of chaos synchronization intractable. Simulation of ExPKF shows that saturation drawn on the emitter to keep it stable impacts badly performances for low channel noise. Then we propose a particle filter that outperforms all other Kalman structured observers in the case of noisy channels.

Delay Specific Investigations on QoS Scheduling Schemes for Real-Time Traffic in Packet Switched Networks

Packet switched data network like Internet, which has traditionally supported throughput sensitive applications such as email and file transfer, is increasingly supporting delay-sensitive multimedia applications such as interactive video. These delaysensitive applications would often rather sacrifice some throughput for better delay. Unfortunately, the current packet switched network does not offer choices, but instead provides monolithic best-effort service to all applications. This paper evaluates Class Based Queuing (CBQ), Coordinated Earliest Deadline First (CEDF), Weighted Switch Deficit Round Robin (WSDRR) and RED-Boston scheduling schemes that is sensitive to delay bound expectations for variety of real time applications and an enhancement of WSDRR is proposed.

Study on the Effect of Weight Percentage Variation and Size Variation of Magnesium Ferrosilicon Added, Gating System Design and Reaction Chamber Design on Inmold Process

This research focuses on the effect of weight percentage variation and size variation of MgFeSi added, gating system design and reaction chamber design on inmold process. By using inmold process, well-known problem of fading is avoided because the liquid iron reacts with magnesium in the mold and not, as usual, in the ladle. During the pouring operation, liquid metal passes through the chamber containing the magnesium, where the reaction of the metal with magnesium proceeds in the absence of atmospheric oxygen [1].In this paper, the results of microstructural characteristic of ductile iron on this parameters are mentioned. The mechanisms of the inmold process are also described [2]. The data obtained from this research will assist in producing the vehicle parts and other machinery parts for different industrial zones and government industries and in transferring the technology to all industrial zones in Myanmar. Therefore, the inmold technology offers many advantages over traditional treatment methods both from a technical and environmental, as well as an economical point of view. The main objective of this research is to produce ductile iron castings in all industrial sectors in Myanmar more easily with lower costs. It will also assist the sharing of knowledge and experience related to the ductile iron production.

Comparative Studies on Vertical Stratification,Floristic Composition, and Woody Species Diversity of Subtropical Evergreen Broadleaf Forests Between the Ryukyu Archipelago, Japan, and South China

In order to compare vertical stratification, floristic composition, and woody species diversity of subtropical evergreen broadleaf forests between the Ryukyu Archipelago, Japan, and South China, tree censuses in a 400 m2 plot in Ishigaki Island and a 1225 m2 plot in Dinghushan Nature Reserve were performed. Both of the subtropical forests consisted of five vertical strata. The floristic composition of the Ishigaki forest was quite different from that of the Dinghushan forest in terms of similarity on a species level (Kuno-s similarity index r0 = 0.05). The values of Shannon-s index H' and Pielou-s index J ' tended to increase from the bottom stratum upward in both forests, except H' for the top stratum in the Ishigaki forest and the upper two strata in the Dinghushan forest. The woody species diversity in the Dinghushan forest (H'= 3.01 bit) was much lower than that in the Ishigaki forest (H'= 4.36 bit).

Classification of Soil Aptness to Establish of Panicum virgatum in Mississippi using Sensitivity Analysis and GIS

During the last decade Panicum virgatum, known as Switchgrass, has been broadly studied because of its remarkable attributes as a substitute pasture and as a functional biofuel source. The objective of this investigation was to establish soil suitability for Switchgrass in the State of Mississippi. A linear weighted additive model was developed to forecast soil suitability. Multicriteria analysis and Sensitivity analysis were utilized to adjust and optimize the model. The model was fit using seven years of field data associated with soils characteristics collected from Natural Resources Conservation System - United States Department of Agriculture (NRCS-USDA). The best model was selected by correlating calculated biomass yield with each model's soils-based output for Switchgrass suitability. Coefficient of determination (r2) was the decisive factor used to establish the 'best' soil suitability model. Coefficients associated with the 'best' model were implemented within a Geographic Information System (GIS) to create a map of relative soil suitability for Switchgrass in Mississippi. A Geodatabase associated with soil parameters was built and is available for future Geographic Information System use.

Double Reduction of Ada-ECATNet Representation using Rewriting Logic

One major difficulty that faces developers of concurrent and distributed software is analysis for concurrency based faults like deadlocks. Petri nets are used extensively in the verification of correctness of concurrent programs. ECATNets [2] are a category of algebraic Petri nets based on a sound combination of algebraic abstract types and high-level Petri nets. ECATNets have 'sound' and 'complete' semantics because of their integration in rewriting logic [12] and its programming language Maude [13]. Rewriting logic is considered as one of very powerful logics in terms of description, verification and programming of concurrent systems. We proposed in [4] a method for translating Ada-95 tasking programs to ECATNets formalism (Ada-ECATNet). In this paper, we show that ECATNets formalism provides a more compact translation for Ada programs compared to the other approaches based on simple Petri nets or Colored Petri nets (CPNs). Such translation doesn-t reduce only the size of program, but reduces also the number of program states. We show also, how this compact Ada-ECATNet may be reduced again by applying reduction rules on it. This double reduction of Ada-ECATNet permits a considerable minimization of the memory space and run time of corresponding Maude program.

Making Businesses Work Smarter with Mobile Business Intelligence

Through the course of this paper we outline how mobile Business Intelligence (m-BI) can help businesses to work smarter and to improve their agility. When we analyze the industry from the usage perspective or how interaction with the enterprise BI system happens via mobile devices, we may easily understand that there are two major types of mobile BI: passive and active. Active mobile BI gives provisions for users to interact with the BI systems on-the-fly. Active mobile business intelligence often works as a combination of both “push and pull" techniques. Some mistakes were done in the up-to-day progress of mobile technologies and mobile BI, as well as some problems that still have to be resolved. We discussed in the paper rather broadly.

Finite Volume Model to Study the Effect of Buffer on Cytosolic Ca2+ Advection Diffusion

Calcium [Ca2+] is an important second messenger which plays an important role in signal transduction. There are several parameters that affect its concentration profile like buffer source etc. The effect of stationary immobile buffer on Ca2+ concentration has been incorporated which is a very important parameter needed to be taken into account in order to make the model more realistic. Interdependence of all the important parameters like diffusion coefficient and influx over [Ca2+] profile has been studied. Model is developed in the form of advection diffusion equation together with buffer concentration. A program has been developed using finite volume method for the entire problem and simulated on an AMD-Turion 32-bit machine to compute the numerical results.