On the Computation of a Common n-finger Robotic Grasp for a Set of Objects

Industrial robotic arms utilize multiple end-effectors, each for a specific part and for a specific task. We propose a novel algorithm which will define a single end-effector’s configuration able to grasp a given set of objects with different geometries. The algorithm will have great benefit in production lines allowing a single robot to grasp various parts. Hence, reducing the number of endeffectors needed. Moreover, the algorithm will reduce end-effector design and manufacturing time and final product cost. The algorithm searches for a common grasp over the set of objects. The search algorithm maps all possible grasps for each object which satisfy a quality criterion and takes into account possible external wrenches (forces and torques) applied to the object. The mapped grasps are- represented by high-dimensional feature vectors which describes the shape of the gripper. We generate a database of all possible grasps for each object in the feature space. Then we use a search and classification algorithm for intersecting all possible grasps over all parts and finding a single common grasp suitable for all objects. We present simulations of planar and spatial objects to validate the feasibility of the approach.

Evaluation of Total Cross Section of Photo-Ionization of Helium in Weak Field on Base of Trajectory Method

Total cross section of helium atom photo-ionization by weak short pulse is calculated using the variant of trajectory method, developed in our earlier work. The method enables simple estimation of total ionization probability (or cross section) without integration of differential one.

Comparison of Two Types of Preconditioners for Stokes and Linearized Navier-Stokes Equations

To solve saddle point systems efficiently, several preconditioners have been published. There are many methods for constructing preconditioners for linear systems from saddle point problems, for instance, the relaxed dimensional factorization (RDF) preconditioner and the augmented Lagrangian (AL) preconditioner are used for both steady and unsteady Navier-Stokes equations. In this paper we compare the RDF preconditioner with the modified AL (MAL) preconditioner to show which is more effective to solve Navier-Stokes equations. Numerical experiments indicate that the MAL preconditioner is more efficient and robust, especially, for moderate viscosities and stretched grids in steady problems. For unsteady cases, the convergence rate of the RDF preconditioner is slightly faster than the MAL perconditioner in some circumstances, but the parameter of the RDF preconditioner is more sensitive than the MAL preconditioner. Moreover the convergence rate of the MAL preconditioner is still quite acceptable. Therefore we conclude that the MAL preconditioner is more competitive than the RDF preconditioner. These experiments are implemented with IFISS package. 

Positive Solutions of Initial Value Problem for the Systems of Second Order Integro-Differential Equations in Banach Space

In this paper, by establishing a new comparison result, we investigate the existence of positive solutions for initial value problems of nonlinear systems of second order integro-differential equations in Banach space.We improve and generalize some results  (see[5,6]), and the results is new even in finite dimensional spaces.

The Implementation of the Multi-Agent Classification System (MACS) in Compliance with FIPA Specifications

The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). The Microsoft's .NET widows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.

Using Multi-Linguistic Techniques for Thailand Herb and Traditional Medicine Registration Systems

Thailand has evolved many unique culture and knowledge, and the leading is the Thai traditional medicine (TTM). Recently, a number of researchers have tried to save this indigenous knowledge. However, the system to do so has still been scant. To preserve this ancient knowledge, we therefore invented and integrated multi-linguistic techniques to create the system of the collected all of recipes. This application extracted the medical recipes from antique scriptures then normalized antiquarian words, primitive grammar and antiquated measurement of them to the modern ones. Then, we applied ingredient-duplication-calculation, proportion-similarity-calculation and score-ranking to examine duplicate recipes. We collected the questionnaires from registrants and people to investigate the users’ satisfaction. The satisfactory results were found. This application assists not only registrants to validating the copyright violation in TTM registration process but also people to cure their illness that aids both Thai people and all mankind to fight for intractable diseases.

Partial Purification of Cytotoxic Peptides against Gastric Cancer Cells from Protein Hydrolysate of Euphorbia hirta Linn.

Protein hydrolysates prepared from a number of medicinal plants are promising sources of various bioactive peptides. In this work, proteins from dried whole plant of Euphorbia hirta Linn. were extracted and digested with pepsin for 12h. The hydrolysates of lesser than 3 KDa were fractionated by a cut-off membrane. The peptide hydrolysate was then purified by an anion-exchange chromatography on DEAE-Sephacel™ column and reverse-phase chromatography on Sep-pak C18 column, respectively. The cytotoxic effect of each peptide fraction against a gastric carcinoma cell line (KATO-III, ATCC No. HTB103) was investigated using colorimetric MTT viability assay. A human liver cell line (Chang Liver, CLS No. 300139) was used as a control normal cell line. Two purified peptide peaks, peak l and peak ll at 100µg peptides mL-1 affected cell viability of the gastric cancer cell lines to 63.85±4.94 and 66.92±6.46%, respectively. Our result showed for the first time that the peptide fractions derived from protein hydrolysate of Euphorbia hirta Linn. have anti-gastric cancer activity, which offers a potential novel and natural anti-gastric cancer remedy.

Application of Particle Swarm Optimization for Economic Load Dispatch and Loss Reduction

This paper proposes a particle swarm optimization (PSO) technique to solve the economic load dispatch (ELD) problems. For the ELD problem in this work, the objective function is to minimize the total fuel cost of all generator units for a given daily load pattern while the main constraints are power balance and generation output of each units. Case study in the test system of 40-generation units with 6 load patterns is presented to demonstrate the performance of PSO in solving the ELD problem. It can be seen that the optimal solution given by PSO provides the minimum total cost of generation while satisfying all the constraints and benefiting greatly from saving in power loss reduction.

Some Preconditioners for Block Pentadiagonal Linear Systems Based on New Approximate Factorization Methods

In this paper, getting an high-efficiency parallel algorithm to solve sparse block pentadiagonal linear systems suitable for vectors and parallel processors, stair matrices are used to construct some parallel polynomial approximate inverse preconditioners. These preconditioners are appropriate when the desired target is to maximize parallelism. Moreover, some theoretical results about these preconditioners are presented and how to construct preconditioners effectively for any nonsingular block pentadiagonal H-matrices is also described. In addition, the availability of these preconditioners is illustrated with some numerical experiments arising from two dimensional biharmonic equation.

Analysis of GI/M(n)/1/N Queue with Single Working Vacation and Vacation Interruption

This paper presents a finite buffer renewal input single working vacation and vacation interruption queue with state dependent services and state dependent vacations, which has a wide range of applications in several areas including manufacturing, wireless communication systems. Service times during busy period, vacation period and vacation times are exponentially distributed and are state dependent. As a result of the finite waiting space, state dependent services and state dependent vacation policies, the analysis of these queueing models needs special attention. We provide a recursive method using the supplementary variable technique to compute the stationary queue length distributions at pre-arrival and arbitrary epochs. An efficient computational algorithm of the model is presented which is fast and accurate and easy to implement. Various performance measures have been discussed. Finally, some special cases and numerical results have been depicted in the form of tables and graphs. 

Reliability Approximation through the Discretization of Random Variables using Reversed Hazard Rate Function

Sometime it is difficult to determine the exact reliability for complex systems in analytical procedures. Approximate solution of this problem can be provided through discretization of random variables. In this paper we describe the usefulness of discretization of a random variable using the reversed hazard rate function of its continuous version. Discretization of the exponential distribution has been demonstrated. Applications of this approach have also been cited. Numerical calculations indicate that the proposed approach gives very good approximation of reliability of complex systems under stress-strength set-up. The performance of the proposed approach is better than the existing discrete concentration method of discretization. This approach is conceptually simple, handles analytic intractability and reduces computational time. The approach can be applied in manufacturing industries for producing high-reliable items.

Future Logistics - Challenges, Requirements and Solutions for Logistics Networks

The importance of logistics has changed enormously in the last few decades. While logistics was formerly one of the core functions of most companies, logistics or at least parts of their functions are nowadays outsourced to external logistic service providers in terms of contracts. As a result of this shift new business models like the fourth party logistics provider emerged, which designs, plans and monitors the resulting logistics networks. This new business model and topics such as Synchromodality or Big Data impose new requirements on the underlying IT, which cannot be met with conventional concepts and approaches. In this paper, the challenges of logistics network monitoring are outlined by using a scenario. The most common layers in a logical multilayered architecture for an information system are used to point out the arising challenges for IT. In addition, first appropriate solution approaches are introduced.  

Simulating Voltage Sag Using PSCAD Software

Power quality is used to describe the degree of consistency of electrical energy expected from generation source to point of use. The term power quality refers to a wide variety of electromagnetic phenomena that characterize the voltage and current at a given time and at a given location on the power system. Power quality problems can be defined as problem that results in failure of customer equipments, which manifests itself as an economic burden to users, or produces negative impacts on the environment. Voltage stability, power factor, harmonics pollution, reactive power and load unbalance are some of the factors that affect the consistency or the quality level. This research proposal proposes to investigate and analyze the causes and effects of power quality to homes and industries in Sarawak. The increasing application of electronics equipment used in the industries and homes has caused a big impact on the power quality. Many electrical devices are now interconnected to the power network and it can be observed that if the power quality of the network is good, then any loads connected to it will run smoothly and efficiently. On the other hand, if the power quality of the network is bad, then loads connected to it will fail or may cause damage to the equipments and reduced its lifetime. The outcome of this research will enable better and novel solutions of poor power quality to small industries and reduce damage of electrical devices and products in the industries.

Inexact Alternating Direction Method for Variational Inequality Problems with Linear Equality Constraints

In this article, a new inexact alternating direction method(ADM) is proposed for solving a class of variational inequality problems. At each iteration, the new method firstly solves the resulting subproblems of ADM approximately to generate an temporal point ˜xk, and then the multiplier yk is updated to get the new iterate yk+1. In order to get xk+1, we adopt a new descent direction which is simple compared with the existing prediction-correction type ADMs. For the inexact ADM, the resulting proximal subproblem has closedform solution when the proximal parameter and inexact term are chosen appropriately. We show the efficiency of the inexact ADM numerically by some preliminary numerical experiments.

Design of Two-Channel Quadrature Mirror Filter Banks Using Digital All-Pass Filters

The paper deals with the minimax design of two-channel linear-phase (LP) quadrature mirror filter (QMF) banks using infinite impulse response (IIR) digital all-pass filters (DAFs). Based on the theory of two-channel QMF banks using two IIR DAFs, the design problem is appropriately formulated to result in an appropriate Chebyshev approximation for the desired group delay responses of the IIR DAFs and the magnitude response of the low-pass analysis filter. Through a frequency sampling and iterative approximation method, the design problem can be solved by utilizing a weighted least squares approach. The resulting two-channel QMF banks can possess approximately LP response without magnitude distortion. Simulation results are presented for illustration and comparison.

Particle Swarm Optimization with Interval-valued Genotypes and Its Application to Neuroevolution

The author proposes an extension of particle swarm optimization (PSO) for solving interval-valued optimization problems and applies the extended PSO to evolutionary training of neural networks (NNs) with interval weights. In the proposed PSO, values in the genotypes are not real numbers but intervals. Experimental results show that interval-valued NNs trained by the proposed method could well approximate hidden target functions despite the fact that no training data was explicitly provided.

Comparison of Two Interval Models for Interval-Valued Differential Evolution

The author previously proposed an extension of differential evolution. The proposed method extends the processes of DE to handle interval numbers as genotype values so that DE can be applied to interval-valued optimization problems. The interval DE can employ either of two interval models, the lower and upper model or the center and width model, for specifying genotype values. Ability of the interval DE in searching for solutions may depend on the model. In this paper, the author compares the two models to investigate which model contributes better for the interval DE to find better solutions. Application of the interval DE is evolutionary training of interval-valued neural networks. A result of preliminary study indicates that the CW model is better than the LU model: the interval DE with the CW model could evolve better neural networks. 

Adsorption Refrigeration Working Pairs: The State-of-the-Art in the Application

Adsorption refrigeration working pair is a vital and is the main component in the adsorption refrigeration machine. Therefore the development key is laying on the adsorption pair that leads to the improvement of the adsorption refrigeration machine. In this study the state-of-the-art in the application of the adsorption refrigeration working pairs in both classical and modern adsorption pairs are presented, compared and summarized. It is found that the maximum adsorption capacity for the classical working pairs was 0.259kg/kg for activated carbon/methanol and that for the modern working pairs was 2kg/kg for maxsorb III/R-134a. The study concluded that, the performances of the adsorption working pairs of adsorption cooling systems are still need further investigations as well as developing adsorption pairs having higher sorption capacity with low or no impact on environmental, to build compact, efficient, reliable and long life performance adsorption chillier. Also, future researches need to be focused on designing the adsorption system that provide efficient heating and cooling for the adsorbent materials through distributing the adsorbent material over heat exchanger surface, to allow good heat and mass transfer between the adsorbent and the refrigerant.

Comparison of Welding Fumes Exposure during Standing and Sitting Welder’s Position

Experimental study was conducted to assess personal welding fumes exposure toward welders during an aluminum metal inert gas (MIG) process. The welding process was carried out by a welding machine attached to a Computer Numerical Control (CNC) workbench. A dummy welder was used to replicate welder during welding works and was attached with sampling pumps and filter cassettes for welding fumes sampling. Direct reading instruments to measure air velocity, humidity, temperature and particulate matter with diameter size 10µm or less (PM10) were located behind the dummy welder and parallel to the neck collar level to make sure the measured welding fumes exposure were not being influenced by other factors. Welding fumes exposure during standing and sitting position with and without the usage of local exhaust ventilation (LEV) was investigated. Welding fume samples were then digested and analyzed by using inductively coupled plasma mass spectroscopy (ICP-MS) according to ASTM D7439-08 method. The results of the study showed the welding fume exposure during sitting was lower compared to standing position. LEV helped reduce aluminum and lead exposure to acceptable levels during standing position. However during sitting position reduction of exposure was smaller. It can be concluded that welder position and the correct positioning of LEV should be implemented for effective exposure reduction. 

ICT for Social Networking in Flood Risk and Knowledge Management Strategies- An MCDA Approach

This paper discusses the role and importance of Information and Communication Technologies (ICT) and social Networking (SN) in the process of decision making for Flood Risk and Knowledge Management Strategies. We use Mozambique Red Cross (CVM) as the case study and further more we address scenarios for flood risk management strategies, using earlier warning and social networking and we argue that a sustainable desirable stage of life can be achieved by developing scenario strategic planning based on backcasting.