Areas of Lean Manufacturing for Productivity Improvement in a Manufacturing Unit

Many organisations are nowadays interested to adopt lean manufacturing strategy that would enable them to compete in this competitive globalisation market. In this respect, it is necessary to assess the implementation of lean manufacturing in different organisations so that the important best practices can be identified. This paper describes the development of key areas which will be used to assess the adoption and implementation of lean manufacturing practices. There are some key areas developed to evaluate and reduce the most optimal projects so as to enhance their production efficiency and increase the purpose of the economic benefits of the manufacturing unit. Lean manufacturing is becoming lean enterprise by treating its customers and suppliers as partners. This gives the extra edge in today-s cost and time competitive markets. The organisation is becoming strong in all the conventional competition points. They are Price, Quality and Delivery. Lean enterprise owners can deliver high quality products quickly, with low price.

Possible Protective Effect of Kombucha Tea Ferment on Cadmium Chloride Induced Liver and Kidney Damage in Irradiated Rats

Kombucha Tea Ferment (KT), was given to male albino rats, (1ml/Kg of body weight), via gavages, during 2 weeks before intraperitoneal administration of 3.5 mg/Kg body weight CdCl2 and/or whole body γ-irradiation with 4Gy, and during 4 weeks after each treatment. Hepatic and nephritic pathological changes included significant increases of serum alanine transaminase (ALT), aspartate transaminase (AST), and alkaline phosphatase (ALP) activities, and creatinine and urea contents with significant decrease in serum total antioxidant capacity (TAC). Increase in oxidative stress markers in liver and kidney tissues expressed by significant increase in malondialdehyde (MDA) and nitric oxide (NO) contents associated to significant depletion in superoxide dismutase (SOD) and catalase (CAT) activities, and reduced glutathione (GSH) content were recorded. KT administration results in recovery of all the pathological changes. It could be concluded that KT might protect liver and kidney from oxidative damage induced by exposure to cadmium and/ or γ-irradiation.

A Survey: Clustering Ensembles Techniques

The clustering ensembles combine multiple partitions generated by different clustering algorithms into a single clustering solution. Clustering ensembles have emerged as a prominent method for improving robustness, stability and accuracy of unsupervised classification solutions. So far, many contributions have been done to find consensus clustering. One of the major problems in clustering ensembles is the consensus function. In this paper, firstly, we introduce clustering ensembles, representation of multiple partitions, its challenges and present taxonomy of combination algorithms. Secondly, we describe consensus functions in clustering ensembles including Hypergraph partitioning, Voting approach, Mutual information, Co-association based functions and Finite mixture model, and next explain their advantages, disadvantages and computational complexity. Finally, we compare the characteristics of clustering ensembles algorithms such as computational complexity, robustness, simplicity and accuracy on different datasets in previous techniques.

The Oxidative Stress and the Antioxidant Defense of the Lower Vegetables towards an Environmental Pollution

The use of bioindicators plants (lichens, bryophytes and Sphagnum....) in monitoring pollution by heavy metals has been the subject of several works. However, few studies have addressed the impact of specific type-s pollutants (fertilizers, pesticides.) on these organisms. We propose in this work to make the highlighting effect of NPKs (NPK: nitrogen-phosphate-potassium-sulfate (NP2O5K2O) (15,15,15), at concentrations of 10, 20, 30 , 40 and 50mM/L) on the activity of detoxification enzymes (GSH/GST, CAT, APX and MDA) of plant bioindicators (mosses and lichens) after treatment for 3 and 7 days. This study shows the important role of the defense system in the accumulation and tolerance to chemical pollutants through the activation of enzymatic (GST (glutathione-S-transferase, APX (ascorbat peroxidase), CAT (catalase)) and nonenzymatic biomarkers (GSH (glutathione), MDA (malondialdehyde)) against oxidative stress generated by the NPKs.

Relationship of Reaction Temperature on Phosphate Oligomers Reactivity to Properties of Soy-Polyurethane

Polyurethane foam (PUF) were prepared by reacting polyols synthesized from soy-oil into mixture of 2,4- Toluene diisocyanate (TDI) with 4,4--Methylene Diamine Isocyanate (MDI) with ratio of 70:30. The polyols obtained via esterification reaction were categorize into different temperature of reaction and by used of varied concentration of phosphoric acid catalyst. The purpose of catalysts is to shifting selectivity to a desired and value added of product. The effect of stoichiometric balance (molar ratio of epoxide/ethylene glycol) to the concentration of the catalyst on the final properties was evaluated.

On The Analysis of a Compound Neural Network for Detecting Atrio Ventricular Heart Block (AVB) in an ECG Signal

Heart failure is the most common reason of death nowadays, but if the medical help is given directly, the patient-s life may be saved in many cases. Numerous heart diseases can be detected by means of analyzing electrocardiograms (ECG). Artificial Neural Networks (ANN) are computer-based expert systems that have proved to be useful in pattern recognition tasks. ANN can be used in different phases of the decision-making process, from classification to diagnostic procedures. This work concentrates on a review followed by a novel method. The purpose of the review is to assess the evidence of healthcare benefits involving the application of artificial neural networks to the clinical functions of diagnosis, prognosis and survival analysis, in ECG signals. The developed method is based on a compound neural network (CNN), to classify ECGs as normal or carrying an AtrioVentricular heart Block (AVB). This method uses three different feed forward multilayer neural networks. A single output unit encodes the probability of AVB occurrences. A value between 0 and 0.1 is the desired output for a normal ECG; a value between 0.1 and 1 would infer an occurrence of an AVB. The results show that this compound network has a good performance in detecting AVBs, with a sensitivity of 90.7% and a specificity of 86.05%. The accuracy value is 87.9%.

Mobile to Server Face Recognition: A System Overview

This paper presents a system overview of Mobile to Server Face Recognition, which is a face recognition application developed specifically for mobile phones. Images taken from mobile phone cameras lack of quality due to the low resolution of the cameras. Thus, a prototype is developed to experiment the chosen method. However, this paper shows a result of system backbone without the face recognition functionality. The result demonstrated in this paper indicates that the interaction between mobile phones and server is successfully working. The result shown before the database is completely ready. The system testing is currently going on using real images and a mock-up database to test the functionality of the face recognition algorithm used in this system. An overview of the whole system including screenshots and system flow-chart are presented in this paper. This paper also presents the inspiration or motivation and the justification in developing this system.

Automatic Generation of OWL Ontologies from UML Class Diagrams Based on Meta- Modelling and Graph Grammars

Models are placed by modeling paradigm at the center of development process. These models are represented by languages, like UML the language standardized by the OMG which became necessary for development. Moreover the ontology engineering paradigm places ontologies at the center of development process; in this paradigm we find OWL the principal language for knowledge representation. Building ontologies from scratch is generally a difficult task. The bridging between UML and OWL appeared on several regards such as the classes and associations. In this paper, we have to profit from convergence between UML and OWL to propose an approach based on Meta-Modelling and Graph Grammars and registered in the MDA architecture for the automatic generation of OWL ontologies from UML class diagrams. The transformation is based on transformation rules; the level of abstraction in these rules is close to the application in order to have usable ontologies. We illustrate this approach by an example.

Investigation of Undular Hydraulic Jump over Smooth Beds

Undular hydraulic jumps are illustrated by a smooth rise of the free surface followed by a train of stationary waves. They are sometimes experienced in natural waterways and rivers. The characteristics of undular hydraulic jumps are studied here. The height, amplitude and the main characteristics of undular jump is depended on the upstream Froude number and aspect ratio. The experiments were done on the smooth bed flume. These results compared with other researches and the main characteristics of the undular hydraulic jump were studied in this article.

A Comparison Study of Electrical Characteristics in Conventional Multiple-gate Silicon Nanowire Transistors

In this paper electrical characteristics of various kinds of multiple-gate silicon nanowire transistors (SNWT) with the channel length equal to 7 nm are compared. A fully ballistic quantum mechanical transport approach based on NEGF was employed to analyses electrical characteristics of rectangular and cylindrical silicon nanowire transistors as well as a Double gate MOS FET. A double gate, triple gate, and gate all around nano wires were studied to investigate the impact of increasing the number of gates on the control of the short channel effect which is important in nanoscale devices. Also in the case of triple gate rectangular SNWT inserting extra gates on the bottom of device can improve the application of device. The results indicate that by using gate all around structures short channel effects such as DIBL, subthreshold swing and delay reduces.

Active Tendons for Seismic Control of Buildings

In this study, active tendons with Proportional Integral Derivation type controllers were applied to a SDOF and a MDOF building model. Physical models of buildings were constituted with virtual springs, dampers and rigid masses. After that, equations of motion of all degrees of freedoms were obtained. Matlab Simulink was utilized to obtain the block diagrams for these equations of motion. Parameters for controller actions were found by using a trial method. After earthquake acceleration data were applied to the systems, building characteristics such as displacements, velocities, accelerations and transfer functions were analyzed for all degrees of freedoms. Comparisons on displacement vs. time, velocity vs. time, acceleration vs. time and transfer function (Db) vs. frequency (Hz) were made for uncontrolled and controlled buildings. The results show that the method seems feasible.

Using Data Mining Methodology to Build the Predictive Model of Gold Passbook Price

Gold passbook is an investing tool that is especially suitable for investors to do small investment in the solid gold. The gold passbook has the lower risk than other ways investing in gold, but its price is still affected by gold price. However, there are many factors can cause influences on gold price. Therefore, building a model to predict the price of gold passbook can both reduce the risk of investment and increase the benefits. This study investigates the important factors that influence the gold passbook price, and utilize the Group Method of Data Handling (GMDH) to build the predictive model. This method can not only obtain the significant variables but also perform well in prediction. Finally, the significant variables of gold passbook price, which can be predicted by GMDH, are US dollar exchange rate, international petroleum price, unemployment rate, whole sale price index, rediscount rate, foreign exchange reserves, misery index, prosperity coincident index and industrial index.

Fuzzy Relatives of the CLARANS Algorithm With Application to Text Clustering

This paper introduces new algorithms (Fuzzy relative of the CLARANS algorithm FCLARANS and Fuzzy c Medoids based on randomized search FCMRANS) for fuzzy clustering of relational data. Unlike existing fuzzy c-medoids algorithm (FCMdd) in which the within cluster dissimilarity of each cluster is minimized in each iteration by recomputing new medoids given current memberships, FCLARANS minimizes the same objective function minimized by FCMdd by changing current medoids in such away that that the sum of the within cluster dissimilarities is minimized. Computing new medoids may be effected by noise because outliers may join the computation of medoids while the choice of medoids in FCLARANS is dictated by the location of a predominant fraction of points inside a cluster and, therefore, it is less sensitive to the presence of outliers. In FCMRANS the step of computing new medoids in FCMdd is modified to be based on randomized search. Furthermore, a new initialization procedure is developed that add randomness to the initialization procedure used with FCMdd. Both FCLARANS and FCMRANS are compared with the robust and linearized version of fuzzy c-medoids (RFCMdd). Experimental results with different samples of the Reuter-21578, Newsgroups (20NG) and generated datasets with noise show that FCLARANS is more robust than both RFCMdd and FCMRANS. Finally, both FCMRANS and FCLARANS are more efficient and their outputs are almost the same as that of RFCMdd in terms of classification rate.

Analysis of Palm Perspiration Effect with SVM for Diabetes in People

In this research, the diabetes conditions of people (healthy, prediabete and diabete) were tried to be identified with noninvasive palm perspiration measurements. Data clusters gathered from 200 subjects were used (1.Individual Attributes Cluster and 2. Palm Perspiration Attributes Cluster). To decrase the dimensions of these data clusters, Principal Component Analysis Method was used. Data clusters, prepared in that way, were classified with Support Vector Machines. Classifications with highest success were 82% for Glucose parameters and 84% for HbA1c parametres.

An Intelligent Fuzzy-Neural Diagnostic System for Osteoporosis Risk Assessment

In this article, we propose an Intelligent Medical Diagnostic System (IMDS) accessible through common web-based interface, to on-line perform initial screening for osteoporosis. The fundamental approaches which construct the proposed system are mainly based on the fuzzy-neural theory, which can exhibit superiority over other conventional technologies in many fields. In diagnosis process, users simply answer a series of directed questions to the system, and then they will immediately receive a list of results which represents the risk degrees of osteoporosis. According to clinical testing results, it is shown that the proposed system can provide the general public or even health care providers with a convenient, reliable, inexpensive approach to osteoporosis risk assessment.

Insertion of Thiazolidinediones into Carbon Nanotube

In this study we investigate the insertion of pioglitazone, a Thiazolidinedione, into the two different sizes of Carbon nanotub. It was shown that the insertion of pioglitazone into the carbon nanotube in a water solute environment could be related to the diameter of the nanotube and in the flow of the waters via hydrophilic interactions. This encapsulated drug-carbon nanotube molecule can be further applicable in other investigations in target therapy with these agents regarding to reduce their potential toxic effects.

Performance Enhancement of Motion Estimation Using SSE2 Technology

Motion estimation is the most computationally intensive part in video processing. Many fast motion estimation algorithms have been proposed to decrease the computational complexity by reducing the number of candidate motion vectors. However, these studies are for fast search algorithms themselves while almost image and video compressions are operated with software based. Therefore, the timing constraints for running these motion estimation algorithms not only challenge for the video codec but also overwhelm for some of processors. In this paper, the performance of motion estimation is enhanced by using Intel's Streaming SIMD Extension 2 (SSE2) technology with Intel Pentium 4 processor.

Packaging the Alkaloids of Cinchona Bark in Combination with Etoposide in Polymeric Micelles Nanoparticles

Today, cancer remains one of the major diseases that lead to death. The main obstacle in chemotherapy as a main cancer treatment is the toxicity to normal cells due to Multidrug Resistance (MDR) after the use of anticancer drugs. Proposed solution to overcome this problem is the use of MDR efflux inhibitor of cinchona alkaloids which is delivered together with anticancer drugs encapsulated in the form of polymeric nanoparticles. The particles were prepared by the hydration method. The characterization of nanoparticles was particle size, zeta potential, entrapment efficiency and in vitro drug release. Combination nanoparticle size ranged 29-45 nm with a neutral surface charge. Entrapment efficiency was above 87% for the use quinine, quinidine or cinchonidine in combination with etoposide. The release test results exhibited that the cinchona alkaloids release released faster than that of etoposide. Collectively, cinchona alkaloids can be packaged along with etoposide in nanomicelles for better cancer therapy.

Biospeckle Techniques in Quality Evaluation of Indian Fruits

In this study spatial-temporal speckle correlation techniques have been applied for the quality evaluation of three different Indian fruits namely apple, pear and tomato for the first time. The method is based on the analysis of variations of laser light scattered from biological samples. The results showed that crosscorrelation coefficients of biospeckle patterns change subject to their freshness and the storage conditions. The biospeckle activity was determined by means of the cross-correlation functions of the intensity fluctuations. Significant changes in biospeckle activity were observed during their shelf lives. From the study, it is found that the biospeckle activity decreases with the shelf-life storage time. Further it has been shown that biospeckle activity changes according to their respiration rates.

Institutionalising Corporate Social Responsibility: A Study on the CSR Statements on Corporate Websites of Malaysian and Singapore Corporations

The purpose of this paper is to examine the current state of corporate social responsibility statements on corporate websites of Malaysian and Singaporean corporations and analyze how the CSR statements contribute in building a unique corporate identity of corporations. Content analysis is employed to examine the websites of Malaysian and Singaporean consumer corporations. It is believed that generally most companies tend to publish and communicate their CSR statements visibly to general stakeholders. However, there is a significantly different outcome of the articulation of CSR on practices on websites between Malaysian and Singaporean consumer corporations. A number of Singaporean organizations were found less concerned with CSR practices as compared to Malaysian organizations. The findings indicate a need for corporations in Malaysia and Singapore to orchestrate their core competence of CSR activities in order to develop a unique corporate identity in a global business environment.