Indonesian Store Loyalty Factors for Modern Retailing Market

Modern retailers such as hypermarket/supermarket need to be more customer-oriented in order to survive in today-s competitive business world. As a result, the investigation of determinant factors of store loyalty becomes important issue for modern retailing players. This study suggests that consumers- store loyalty in the modern retailing market (hypermarkets and supermarkets) is influenced by environmental factors (such as store image, store personnel). Using a model of stimulus-organismresponse (S-O-R), this research examines S-R relationship of store loyalty. S-O-R framework is derived from the existence literature and tested empirically based on Indonesian consumers- experience. The stimuli for this study are store image, store personnel, satisfaction and culture factors. Affect, or the consumers- liking to modern retailing stores, mediates the chosen environmental factors on consumer-s store loyalty. The findings showed that store image, store satisfaction and culture have significant positive relationship to store loyalty via affect.

Skew Detection Technique for Binary Document Images based on Hough Transform

Document image processing has become an increasingly important technology in the automation of office documentation tasks. During document scanning, skew is inevitably introduced into the incoming document image. Since the algorithm for layout analysis and character recognition are generally very sensitive to the page skew. Hence, skew detection and correction in document images are the critical steps before layout analysis. In this paper, a novel skew detection method is presented for binary document images. The method considered the some selected characters of the text which may be subjected to thinning and Hough transform to estimate skew angle accurately. Several experiments have been conducted on various types of documents such as documents containing English Documents, Journals, Text-Book, Different Languages and Document with different fonts, Documents with different resolutions, to reveal the robustness of the proposed method. The experimental results revealed that the proposed method is accurate compared to the results of well-known existing methods.

Generating Qualitative Causal Graph using Modeling Constructs of Qualitative Process Theory for Explaining Organic Chemistry Reactions

This paper discusses the causal explanation capability of QRIOM, a tool aimed at supporting learning of organic chemistry reactions. The development of the tool is based on the hybrid use of Qualitative Reasoning (QR) technique and Qualitative Process Theory (QPT) ontology. Our simulation combines symbolic, qualitative description of relations with quantity analysis to generate causal graphs. The pedagogy embedded in the simulator is to both simulate and explain organic reactions. Qualitative reasoning through a causal chain will be presented to explain the overall changes made on the substrate; from initial substrate until the production of final outputs. Several uses of the QPT modeling constructs in supporting behavioral and causal explanation during run-time will also be demonstrated. Explaining organic reactions through causal graph trace can help improve the reasoning ability of learners in that their conceptual understanding of the subject is nurtured.

Face Texture Reconstruction for Illumination Variant Face Recognition

In illumination variant face recognition, existing methods extracting face albedo as light normalized image may lead to loss of extensive facial details, with light template discarded. To improve that, a novel approach for realistic facial texture reconstruction by combining original image and albedo image is proposed. First, light subspaces of different identities are established from the given reference face images; then by projecting the original and albedo image into each light subspace respectively, texture reference images with corresponding lighting are reconstructed and two texture subspaces are formed. According to the projections in texture subspaces, facial texture with normal light can be synthesized. Due to the combination of original image, facial details can be preserved with face albedo. In addition, image partition is applied to improve the synthesization performance. Experiments on Yale B and CMUPIE databases demonstrate that this algorithm outperforms the others both in image representation and in face recognition.

Power and Delay Optimized Graph Representation for Combinational Logic Circuits

Structural representation and technology mapping of a Boolean function is an important problem in the design of nonregenerative digital logic circuits (also called combinational logic circuits). Library aware function manipulation offers a solution to this problem. Compact multi-level representation of binary networks, based on simple circuit structures, such as AND-Inverter Graphs (AIG) [1] [5], NAND Graphs, OR-Inverter Graphs (OIG), AND-OR Graphs (AOG), AND-OR-Inverter Graphs (AOIG), AND-XORInverter Graphs, Reduced Boolean Circuits [8] does exist in literature. In this work, we discuss a novel and efficient graph realization for combinational logic circuits, represented using a NAND-NOR-Inverter Graph (NNIG), which is composed of only two-input NAND (NAND2), NOR (NOR2) and inverter (INV) cells. The networks are constructed on the basis of irredundant disjunctive and conjunctive normal forms, after factoring, comprising terms with minimum support. Construction of a NNIG for a non-regenerative function in normal form would be straightforward, whereas for the complementary phase, it would be developed by considering a virtual instance of the function. However, the choice of best NNIG for a given function would be based upon literal count, cell count and DAG node count of the implementation at the technology independent stage. In case of a tie, the final decision would be made after extracting the physical design parameters. We have considered AIG representation for reduced disjunctive normal form and the best of OIG/AOG/AOIG for the minimized conjunctive normal forms. This is necessitated due to the nature of certain functions, such as Achilles- heel functions. NNIGs are found to exhibit 3.97% lesser node count compared to AIGs and OIG/AOG/AOIGs; consume 23.74% and 10.79% lesser library cells than AIGs and OIG/AOG/AOIGs for the various samples considered. We compare the power efficiency and delay improvement achieved by optimal NNIGs over minimal AIGs and OIG/AOG/AOIGs for various case studies. In comparison with functionally equivalent, irredundant and compact AIGs, NNIGs report mean savings in power and delay of 43.71% and 25.85% respectively, after technology mapping with a 0.35 micron TSMC CMOS process. For a comparison with OIG/AOG/AOIGs, NNIGs demonstrate average savings in power and delay by 47.51% and 24.83%. With respect to device count needed for implementation with static CMOS logic style, NNIGs utilize 37.85% and 33.95% lesser transistors than their AIG and OIG/AOG/AOIG counterparts.

A Maximum Parsimony Model to Reconstruct Phylogenetic Network in Honey Bee Evolution

Phylogenies ; The evolutionary histories of groups of species are one of the most widely used tools throughout the life sciences, as well as objects of research with in systematic, evolutionary biology. In every phylogenetic analysis reconstruction produces trees. These trees represent the evolutionary histories of many groups of organisms, bacteria due to horizontal gene transfer and plants due to process of hybridization. The process of gene transfer in bacteria and hybridization in plants lead to reticulate networks, therefore, the methods of constructing trees fail in constructing reticulate networks. In this paper a model has been employed to reconstruct phylogenetic network in honey bee. This network represents reticulate evolution in honey bee. The maximum parsimony approach has been used to obtain this reticulate network.

Harmful Effect of Ambient Ozone on Growth and Productivity of Two Legume Crops Visia Faba, and Pisum sativum in Riyadh City, K.S.A.

Ozone (O3) is considered as one of the most phytotoxic pollutants with deleterious effects on living and non living components of Ecosystems. It reduces growth and yield of many crops as well as alters the physiology and crop quality. The present study described series of experiments to investigate the effects of ambient O3 at different locations with different ambient levels of O3 depending on proximity to pollutant source and ranged between 17 ppb/h in control experiment to 112 ppb/h in industrial area respectively. The ambient levels in other three locations (King Saud University botanical garden, King Fahd Rd, and Almanakh Garden) were 61,61,77 ppb/h respectively. Tow legume crops species (vicia vaba L ; and Pisum sativum) differ in their phenology and sensitivity were used. The results showed a significant negative effect to ozone on morphology, number of injured leaves, growth and productivity with a difference in the degree of response depending on the plant type. Visia Faba showed sensitivity to ozone to number and leaf area and the degree of injury leaves 3, pisum sativum show higher sensitivity for the gas for degree of injury 1,The relative growth rate and seed weight, it turns out there is no significant difference between the two plants in plant height and number of seeds.

Knowledge Sharing: A Survey, Assessment and Directions for Future Research: Individual Behavior Perspective

One of the most important areas of knowledge management studies is knowledge sharing. Measured in terms of number of scientific articles and organization-s applications, knowledge sharing stands as an example of success in the field. This paper reviews the related papers in the context of the underlying individual behavioral variables to providea direction framework for future research and writing.

Solving Partially Monotone Problems with Neural Networks

In many applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. Here we consider partially monotone problems, where the target variable depends monotonically on some of the predictor variables but not all. We propose an approach to build partially monotone models based on the convolution of monotone neural networks and kernel functions. The results from simulations and a real case study on house pricing show that our approach has significantly better performance than partially monotone linear models. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.

FRC – A New Sustainable Option for Construction to Mitigate Earthquakes

Ten simply supported grossly underreinforced tapered concrete beams of full size were tested upto complete collapse under flexural effect .Out of 10 beams, 5 beams were nonfibrous and the remaining beams contained fibres. The beams had a variation in the tapered angle as 2°, 4°, 6°, 8° and 10°. The concrete mix, conventional steel and the type of fibre used were held constant. Flat corrugated steel fibres were utilized as secondary reinforcement. The strength and stability parameters were measured. It is established that the fibrous tapered beams can be used economically in earthquake prone areas.

Risk Assessment of Acrylamide Intake from Roasted Potatoes in Latvia

From food consumption surveys has been found that potato consumption comparing to other European countries is one of the highest. Hence acrylamide (AA) intake coming from fried potatoes in population might be high as well. The aim of the research was to determine acrylamide content and estimate intake of acrylamide from roasted potatoes bred and cultivated in Latvia. Five common Latvian potato varieties were selected: Lenora, Brasla, Imanta, Zile, and Madara. A two-year research was conducted during two periods: just after harvesting and after six months of storage. Time and temperature (210 ± 5°C) was recorded during frying. AA was extracted from potatoes by solid phase extraction and AA content was determined by LC-MS/MS. estimated intake of acrylamide ranges from 0.012 to 0.496μgkg-1 BW per day.

Modelling Indoor Air Carbon Dioxide (CO2)Concentration using Neural Network

The use of neural networks is popular in various building applications such as prediction of heating load, ventilation rate and indoor temperature. Significant is, that only few papers deal with indoor carbon dioxide (CO2) prediction which is a very good indicator of indoor air quality (IAQ). In this study, a data-driven modelling method based on multilayer perceptron network for indoor air carbon dioxide in an apartment building is developed. Temperature and humidity measurements are used as input variables to the network. Motivation for this study derives from the following issues. First, measuring carbon dioxide is expensive and sensors power consumptions is high and secondly, this leads to short operating times of battery-powered sensors. The results show that predicting CO2 concentration based on relative humidity and temperature measurements, is difficult. Therefore, more additional information is needed.

Security Enhanced RFID Middleware System

Recently, the RFID (Radio Frequency Identification) technology attracts the world market attention as essential technology for ubiquitous environment. The RFID market has focused on transponders and reader development. But that concern has shifted to RFID software like as high-valued e-business applications, RFID middleware and related development tools. However, due to the high sensitivity of data and service transaction within the RFID network, security consideration must be addressed. In order to guarantee trusted e-business based on RFID technology, we propose a security enhanced RFID middleware system. Our proposal is compliant with EPCglobal ALE (Application Level Events), which is standard interface for middleware and its clients. We show how to provide strengthened security and trust by protecting transported data between middleware and its client, and stored data in middleware. Moreover, we achieve the identification and service access control against illegal service abuse. Our system enables secure RFID middleware service and trusted e-business service.

Generating Frequent Patterns through Intersection between Transactions

The problem of frequent itemset mining is considered in this paper. One new technique proposed to generate frequent patterns in large databases without time-consuming candidate generation. This technique is based on focusing on transaction instead of concentrating on itemset. This algorithm based on take intersection between one transaction and others transaction and the maximum shared items between transactions computed instead of creating itemset and computing their frequency. With applying real life transactions and some consumption is taken from real life data, the significant efficiency acquire from databases in generation association rules mining.

A Study on using N-Pattern Chains of Design Patterns based on Software Quality Metrics

Design patterns describe good solutions to common and reoccurring problems in program design. Applying design patterns in software design and implementation have significant effects on software quality metrics such as flexibility, usability, reusability, scalability and robustness. There is no standard rule for using design patterns. There are some situations that a pattern is applied for a specific problem and this pattern uses another pattern. In this paper, we study the effect of using chain of patterns on software quality metrics.

A CBR System to New Product Development: An Application for Hearing Devices Design

Nowadays, quick technological changes force companies to develop innovative products in an increasingly competitive environment. Therefore, how to enhance the time of new product development is very important. This design problem often lacks the exact formula for getting it, and highly depends upon human designers- past experiences. For these reasons, in this work, a Casebased reasoning (CBR) system to assist in new product development is proposed. When a case is recovered from the case base, the system will take into account not only the attribute-s specific value and how important it is. It will also take into account if the attribute has a positive influence over the product development. Hence the manufacturing time will be improved. This information will be introduced as a new concept called “adaptability". An application to this method for hearing instrument new design illustrates the proposed approach.

Efficient Power-Delay Product Modulo 2n+1 Adder Design

As embedded and portable systems were emerged power consumption of circuits had been major challenge. On the other hand latency as determines frequency of circuits is also vital task. Therefore, trade off between both of them will be desirable. Modulo 2n+1 adders are important part of the residue number system (RNS) based arithmetic units with the interesting moduli set (2n-1,2n, 2n+1). In this manuscript we have introduced novel binary representation to the design of modulo 2n+1 adder. VLSI realization of proposed architecture under 180 nm full static CMOS technology reveals its superiority in terms of area, power consumption and power-delay product (PDP) against several peer existing structures.

Scenarios for a Sustainable Energy Supply Results of a Case Study for Austria

A comprehensive discussion of feasible strategies for sustainable energy supply is urgently needed to achieve a turnaround of the current energy situation. The necessary fundamentals required for the development of a long term energy vision are lacking to a great extent due to the absence of reasonable long term scenarios that fulfill the requirements of climate protection and sustainable energy use. The contribution of the study is based on a search for sustainable energy paths in the long run for Austria. The analysis makes use of secondary data predominantly. The measures developed to avoid CO2 emissions and other ecological risk factors vary to a great extent among all economic sectors. This is shown by the calculation of CO2 cost of abatement curves. In this study it is demonstrated that the most effective technical measures with the lowest CO2 abatement costs yield solutions to the current energy problems. Various scenarios are presented concerning the question how the technological and environmental options for a sustainable energy system for Austria could look like in the long run. It is shown how sustainable energy can be supplied even with today-s technological knowledge and options available. The scenarios developed include an evaluation of the economic costs and ecological impacts. The results are not only applicable to Austria but demonstrate feasible and cost efficient ways towards a sustainable future.

Compressive Properties of a Synthetic Bone Substitute for Vertebral Cancellous Bone

Transpedicular screw fixation in spinal fractures, degenerative changes, or deformities is a well-established procedure. However, important rate of fixation failure due to screw bending, loosening, or pullout are still reported particularly in weak bone stock in osteoporosis. To overcome the problem, mechanism of failure has to be fully investigated in vitro. Post-mortem human subjects are less accessible and animal cadavers comprise limitations due to different geometry and mechanical properties. Therefore, the development of a synthetic model mimicking the realistic human vertebra is highly demanded. A bone surrogate, composed of Polyurethane (PU) foam analogous to cancellous bone porous structure, was tested for 3 different densities in this study. The mechanical properties were investigated under uniaxial compression test by minimizing the end artifacts on specimens. The results indicated that PU foam of 0.32 g.cm-3 density has comparable mechanical properties to human cancellous bone in terms of young-s modulus and yield strength. Therefore, the obtained information can be considered as primary step for developing a realistic cancellous bone of human vertebral body. Further evaluations are also recommended for other density groups.

Application of Vortex Tubes for Extracting Sediments Using SHARC Software - A Case Study of the Western Canal in the Dez Diversion Weir

Sediment loads transfer in hydraulic installations and their consequences for the O&M of modern canal systems is emerging as one of the most important considerations in hydraulic engineering projects apriticularly those which are inteded to feed the irrigation and draiange schemes of large command areas such as the Dez and Mogahn in Iran.. The aim of this paper is to investigate the applicability of the vortex tube as a viable means of extracting sediment loads entering the canal systems in general and the water inatke structures in particulars. The Western conveyance canal of the Dez Diversion weir which feeds the Karkheh Flood Plain in Sothwestern Dezful has been used as the case study using the data from the Dastmashan Hydrometric Station. The SHARC software has been used as an analytical framework to interprete the data. Results show that given the grain size D50 and the canal turbulence the adaption length from the beginning of the canal and after the diversion dam is estimated at 477 m, a point which is suitable for laying the vortex tube.