bluuebunny/crossref_metadata_2025 huggingface dataset:
An Examination of Diet for the Maintenance of Remission in Inflammatory Bowel Disease
Authors: Haskey Natasha , Gibson Deanna
Published: March 2017

Diet has been speculated to be a factor in the pathogenesis of inflammatory bowel disease and may be an important factor in managing disease symptoms. Patients manipulate their diet in attempt to control symptoms, often leading to the adoption of inappropriately restrictive diets, which places them at risk for nutritional complications. Health professionals struggle to provide evidence-based nutrition guidance to patients due to an overall lack of uniformity or clarity amongst research studies. Well-designed diet studies are urgently needed to create an enhanced understanding of the role diet plays in the management of inflammatory bowel disease. The aim of this review is to summarize the current data available on dietary management of inflammatory bowel disease and to demonstrate that dietary modulation may be an important consideration in managing disease. By addressing the relevance of diet in inflammatory bowel disease, health professionals are able to better support patients and collaborate with dietitians to improve nutrition therapy.
Chondroprotective Effects of Ginsenoside Rg1 in Human Osteoarthritis Chondrocytes and a Rat Model of Anterior Cruciate Ligament Transection
Authors: Cheng Wendan , Jing Juehua , Wang Zhen , Wu Dongying , Huang Yumin
Published: March 2017

This study aimed to assess whether Ginsenoside Rg1 (Rg1) inhibits inflammatory responses in human chondrocytes and reduces articular cartilage damage in a rat model of osteoarthritis (OA). Gene expression and protein levels of type II collagen, aggrecan, matrix metalloproteinase (MMP)‐13 and cyclooxygenase‐2 (COX‐2) were determined in vitro by quantitative real‐time‐polymerase chain reaction and Western blotting. Prostaglandin E2 (PGE2) amounts in the culture medium were determined by enzyme‐linked immunosorbent assay (ELISA). For in vivo assessment, a rat model of OA was generated by anterior cruciate ligament transection (ACLT). Four weeks after ACLT, Rg1 (30 or 60 mg/kg) or saline was administered by gavage once a day for eight consecutive weeks. Joint damage was analyzed by histology and immunohistochemistry. Ginsenoside Rg1 inhibited Interleukin (IL)‐1β‐induced chondrocyte gene and protein expressions of MMP‐13, COX‐2 and PGE2, and prevented type II collagen and aggrecan degradation, in a dose‐dependent manner. Administration of Ginsenoside Rg1 to OA rats attenuated cartilage degeneration, and reduced type II collagen loss and MMP‐13 levels. These findings demonstrated that Ginsenoside Rg1 can inhibit inflammatory responses in human chondrocytes in vitro and reduce articular cartilage damage in vivo, confirming the potential therapeutic value of Ginsenoside Rg1 in OA.
The Smartphone-Based Offline Indoor Location Competition at IPIN 2016: Analysis and Future Work
Authors: Torres-Sospedra Joaquín , Jiménez Antonio , Knauth Stefan , Moreira Adriano , Beer Yair , Fetzer Toni , Ta Viet-Cuong , Montoliu Raul , Seco Fernando , Mendoza-Silva Germán , Belmonte Oscar , Koukofikis Athanasios , Nicolau Maria , Costa António , Meneses Filipe , Ebner Frank , Deinzer Frank , Vaufreydaz Dominique , Dao Trung-Kien , Castelli Eric
Published: March 2017

This paper presents the analysis and discussion of the off-site localization competition track, which took place during the Seventh International Conference on Indoor Positioning and Indoor Navigation (IPIN 2016). Five international teams proposed different strategies for smartphone-based indoor positioning using the same reference data. The competitors were provided with several smartphone-collected signal datasets, some of which were used for training (known trajectories), and others for evaluating (unknown trajectories). The competition permits a coherent evaluation method of the competitors’ estimations, where inside information to fine-tune their systems is not offered, and thus provides, in our opinion, a good starting point to introduce a fair comparison between the smartphone-based systems found in the literature. The methodology, experience, feedback from competitors and future working lines are described.
Autonomous Pointing Control of a Large Satellite Antenna Subject to Parametric Uncertainty
Authors: Wu Shunan , Liu Yufei , Radice Gianmarco , Tan Shujun
Published: March 2017

With the development of satellite mobile communications, large antennas are now widely used. The precise pointing of the antenna’s optical axis is essential for many space missions. This paper addresses the challenging problem of high-precision autonomous pointing control of a large satellite antenna. The pointing dynamics are firstly proposed. The proportional–derivative feedback and structural filter to perform pointing maneuvers and suppress antenna vibrations are then presented. An adaptive controller to estimate actual system frequencies in the presence of modal parameters uncertainty is proposed. In order to reduce periodic errors, the modified controllers, which include the proposed adaptive controller and an active disturbance rejection filter, are then developed. The system stability and robustness are analyzed and discussed in the frequency domain. Numerical results are finally provided, and the results have demonstrated that the proposed controllers have good autonomy and robustness.
A Novel Joint Power and Feedback Bit Allocation Interference Alignment Scheme for Wireless Sensor Networks
Authors: Li Shibao , He Chang , Wang Yixin , Zhang Yang , Liu Jianhang , Huang Tingpei
Published: March 2017

It is necessary to improve the energy efficiency of batteries in wireless sensor networks (WSNs). The multiple-input multiple-output (MIMO) technique has become an important means to ameliorate WSNs, and interference management is the core of improving energy efficiency. A promising approach is interference alignment (IA), which effectively reduces the interference and improves the throughput of a system in the MIMO interference channels. However, the IA scheme requires perfect channel state information (CSI) at all transceivers in practice, which results in considerable feedback overhead. Thus, limited IA feedback has attracted much attention. In this paper, we analyze the throughput loss of the K-user MIMO interference channels when each transmitter delivers multiple streams in one slot, and derives the upper-bound of the system interference leakage and throughput loss. Then, to reduce the interference leakage and throughput loss for the MIMO interference alignment with limited feedback, a joint power and feedback bit allocation optimization scheme is proposed. The simulation results show that, compared with the conventional schemes, the presented optimal scheme achieves less residual interference and better performance in the system throughput.
Assessment of Alternative Scenarios for CO2 Reduction Potential in the Residential Building Sector
Authors: Jeong Young-Sun
Published: March 2017

The South Korean government announced its goals of reducing the country’s CO2 emissions by up to 30% below the business as usual (BAU) projections by 2020 in 2009 and 37% below BAU projections by 2030 in 2015. This paper explores the potential energy savings and reduction in CO2 emissions offered by residential building energy efficiency policies and plans in South Korea. The current and future energy consumption and CO2 emissions in the residential building were estimated using an energy–environment model from 2010 to 2030. The business as usual scenario is based on the energy consumption characteristic of residential buildings using the trends related to socio-economic prospects and the number of dwellings. The alternative scenarios took into account energy efficiency for new residential buildings (scenario I), refurbishment of existing residential buildings (scenario II), use of highly efficient boilers (scenario III), and use of a solar thermal energy system (scenario IV). The results show that energy consumption in the residential building sector will increase by 33% between 2007 and 2030 in the BAU scenario. Maximum reduction in CO2 emissions in the residential building sector of South Korea was observed by 2030 in scenario I. In each alternative scenario analysis, CO2 emissions were 12.9% lower than in the business as usual scenario by the year 2030.
Future Professionals: A Study of Sustainable Behavior
Authors: Martins Lohn Vanderleia , Tezza Rafael , Dias Alperstedt Graziela , M. S. Campos Lucila
Published: March 2017

Sustainability in an organizational environment involves a form of management that allows attaining a balance between the economic, environmental and social dimensions, and can contribute to the sustainable behavior of employees and administrators. Nevertheless, studies that evaluate sustainable behavior of future professionals using a multidimensional approach to create a scale to measure sustainable behavior of students are relatively rare and there is a need for research in this field. Therefore, the objective of this article is to analyze the sustainable behavior of potential professionals, using the multidimensional approach of item response theory (IRT). A set of 13 items evaluated by specialists and tested by graduate students was applied to 492 undergraduate students from a community university in Southern Brazil in the schools of administration, human resources, accounting, law, civil engineering and biology. The results indicate that the students have higher sustainable behavior in the social dimension and lower in the economic dimension, highlighted by participation in voluntary activities. This result can provide important information to companies, given that in their processes for recruiting and selecting new employees, many have included issues related to sustainable practices, not only from an economic perspective, but particularly from environmental and social perspectives.
An Alternative Method of Spatial Autocorrelation for Chlorophyll Detection in Water Bodies Using Remote Sensing
Authors: Guimarães Tainá , Veronez Maurício , Koste Emilie , Gonzaga Luiz , Bordin Fabiane , Inocencio Leonardo , Larocca Ana , De Oliveira Marcelo , Vitti Dalva , Mauad Frederico
Published: March 2017

Additional measures of in situ water quality monitoring in natural environments can be obtained through remote sensing because certain elements in water modify its spectral behavior. One of the indicators of water quality is the presence of algae, and the aim of this study was to propose an alternative method for the quantification of chlorophyll in water by correlating spectral data, infrared images, and limnology data. The object of study was an artificial lake located at Unisinos University, São Leopoldo/RS, Brazil. The area has been mapped with a modified NGB (near infrared (N), green (G) and blue (B)) camera coupled to an unmanned aerial vehicle (UAV). From the orthorectified and georeferenced images, a modified normalized difference vegetation index (NDVImod) image has been generated. Additionally, 20 sampling points have been established on the lake. At these points, in situ spectral analysis with a spectroradiometer has been performed, and water samples have been collected for laboratory determination of chlorophyll concentrations. The correlation resulted in two models. The first model, based on the multivariate analysis of spectral data, and the second model, based on polynomial equations from NDVI, had coefficients of determination (R2) of 0.86 and 0.51, respectively. This study confirmed the applicability of remote sensing for water resource management using UAVs, which can be characterized as a quick and easy methodology.
The Impact of a Local Development Project on Social Capital: Evidence from the Bohol Irrigation Scheme in the Philippines
Authors: Park Hogeun , Tsusaka Takuji , Pede Valerien , Kim Kyung-Min
Published: March 2017

The purpose of this paper is to investigate the connection between local development projects and the residents’ social capital in Bohol, The Philippines. From this perspective, we hypothesized that social behaviors of local farmers are influenced by the availability of canal irrigation due to the collective water management required in irrigated societies. By combining the results of the ultimatum game (UG) with a household survey on 245 villagers in Bohol, this paper (1) measures the degree of social capital at the individual level and (2) quantifies the effects of irrigation on social capital by controlling household as well as individual characteristics. Moreover, we employed a Spatial Autoregressive model to explore the spatial effects and social contexts of farmers’ behavioral patterns. The empirical results show that the level of measured social behavior is strongly associated with access to community irrigation water and asset holdings. Additionally, increased physical distance between residents leads to a decrease in social capital, or interdependency, among them. The results suggest that community engagement (e.g., irrigation management committee and turnout service association) with local development projects would not only improve agricultural productivity but also enhance social relationships among farmers, highlighting its importance.
Late Miocene micromammals from the Lukeino Formation (6.1 to 5.8 Ma), Kenya
Authors: Mein Pierre , Pickford Martin
Published: March 2017

Micromammalian fossils have been recovered at several localities (Aragai, Kapsomin and Kapcheberek) in Late Miocene sediments of the Lukeino Formation, eastern foothills of the Tugen Hills, Kenya. The deposits range in age from 6.1 to 5.8 Ma. This paper includes over 800 specimens (897 teeth, not counting numerous rodent incisors), mostly isolated cheek teeth, but several mandibles and maxillae as well. The assemblage is dominated by four species, a late surviving phiomyid Apodecter (144 specimens), an early form of Abudhabia (114 specimens), a new genus of murid (124 specimens) and a primitive species of Saidomys (326 specimens (393 cheek teeth). Saccostomus is represented by 16 teeth, and dendromurines are quite common (31 specimens). The leporid Serengetilagus is also reasonably abundant (24 specimens), the remainder of the taxa being represented by fewer than 10 specimens each.

Remains of the early hominid, Orrorin tugenensis, has been found in intimate association with the microfauna which can thus be used to reconstruct the palaeoenvironment of the earliest known bipeds. The presence of galagids, fruit bats and the diversity of dendromurines (3 species) and some probably arboreal murids (possibly ancestral to Thallomys or Grammomys ) indicates the presence of trees in the vicinity of the site, but some of the taxa suggest the presence of relatively open environments in the vicinity of Kapsomin at the time of deposition. A similar mixture of vegetation types is indicated by the large mammals from Lukeino.
An rbcL reference library to aid in the identification of plant species mixtures by DNA metabarcoding
Authors: Bell Karen L. , Loeffler Virginia M. , Brosi Berry J.
Published: March 2017

Premise of the study:

DNA metabarcoding has broad‐ranging applications in ecology, aerobiology, biosecurity, and forensics. A bioinformatics pipeline has recently been published for identification using a comprehensive database of ITS2, one of the common plant DNA barcoding markers. There is, however, no corresponding database for rbcL, the other primary marker used in plants.

Methods:

Using publicly available data, we compiled a reference library of rbcL sequences and trained databases for use with UTAX and RDP classifier algorithms. We used this reference library, along with the existing bioinformatics pipeline and ITS2 reference library, to identify species in an artificial mixture of nine species of pollen. We have made this database publicly available in multiple formats, to allow use with multiple bioinformatics pipelines, now and in the future.

Results:

Using the rbcL database, in addition to the ITS2 database, we succeeded in making species‐level identifications for eight species and a family‐level identification of the ninth species. This is an improvement on ITS2 sequence alone.

Discussion:

The reference library described here will assist with identification of plant species using rbcL. By making another gene region available for standard barcoding, this will increase the resolution and accuracy of identifications.
Microsatellite markers for population studies of the salt marsh species Juncus roemerianus (Juncaceae)
Authors: Tumas Hayley R. , Shamblin Brian M. , Woodrey Mark S. , Nairn Campbell J.
Published: March 2017

Premise of the study:

Juncus roemerianus (Juncaceae) is a foundational species and ecosystem engineer of salt marshes in the Gulf of Mexico. These ecosystems provide coastal flood attenuation, nurseries for important species, and other ecosystem services, but are experiencing significant decline. Nuclear microsatellite markers were developed for J. roemerianus to study genetic diversity and population structure for conservation and restoration efforts.

Methods and Results:

Illumina NextSeq high‐throughput sequencing was used to develop a panel of 19 polymorphic microsatellite markers that were tested across individuals from three populations on the Gulf Coast. All markers were polymorphic, with observed and expected heterozygosities ranging from 0.212 to 0.828 and from 0.362 to 0.873, respectively. Allelic richness ranged from two to 13 alleles per locus with an average of 5.737.

Conclusions:

The 19 microsatellite markers are useful for population studies throughout the range of J. roemerianus. Three loci cross‐amplified in the related taxon J. effusus.
Development and validation of EST‐SSR markers for Fokienia hodginsii (Cupressaceae)
Authors: Ding Mingyan , Meng Kaikai , Fan Qiang , Tan Weizheng , Liao Wenbo , Chen Sufang
Published: March 2017

Premise of the study:

Fokienia hodginsii (Cupressaceae) is a Tertiary relict evergreen conifer of the monotypic genus Fokienia. Polymorphic microsatellite markers were developed to investigate its genetic diversity and population structure.

Methods and Results:

RNA transcripts of F. hodginsii were sequenced and de novo assembled into 85,818 unigenes, and 1892 simple sequence repeat (SSR) markers were detected from the unigenes. A total of 273 expressed sequence tag–SSR primer pairs were designed and tested, and 129 successfully amplified. Eleven displayed clear polymorphisms in F. hodginsii. Amplification of these polymorphic primers across three populations of F. hodginsii showed the number of alleles per locus ranged from two to seven, and the expected heterozygosity per locus varied from 0.067 to 0.847. All 11 polymorphic primers amplified in Thuja occidentalis, while 10 amplified in T. standishii, Platycladus orientalis, and Chamaecyparis obtusa.

Conclusions:

These microsatellite markers will be useful in exploring genetic diversity of F. hodginsii and other conifer trees.
Investigation of the action of poly(ADP-ribose)-synthesising enzymes on NAD+ analogues
Authors: Wallrodt Sarah , Simpson Edward L , Marx Andreas
Published: March 2017

ADP-ribosyl transferases with diphtheria toxin homology (ARTDs) catalyse the covalent addition of ADP-ribose onto different acceptors forming mono- or poly(ADP-ribos)ylated proteins. Out of the 18 members identified, only four are known to synthesise the complex poly(ADP-ribose) biopolymer. The investigation of this posttranslational modification is important due to its involvement in cancer and other diseases. Lately, metabolic labelling approaches comprising different reporter-modified NAD+ building blocks have stimulated and enriched proteomic studies and imaging applications of ADP-ribosylation processes. Herein, we compare the substrate scope and applicability of different NAD+ analogues for the investigation of the polymer-synthesising enzymes ARTD1, ARTD2, ARTD5 and ARTD6. By varying the site and size of the NAD+ modification, suitable probes were identified for each enzyme. This report provides guidelines for choosing analogues for studying poly(ADP-ribose)-synthesising enzymes.
Deep Recurrent Neural Networks for Supernovae Classification
Authors: Charnock Tom , Moss Adam
Published: March 2017

We apply deep recurrent neural networks, which are capable of learning complex sequential information, to classify supernovae (code available at https://github.com/adammoss/supernovae). The observational time and filter fluxes are used as inputs to the network, but since the inputs are agnostic, additional data such as host galaxy information can also be included. Using the Supernovae Photometric Classification Challenge (SPCC) data, we find that deep networks are capable of learning about light curves, however the performance of the network is highly sensitive to the amount of training data. For a training size of 50% of the representational SPCC data set (around 104 supernovae) we obtain a type-Ia versus non-type-Ia classification accuracy of 94.7%, an area under the Receiver Operating Characteristic curve AUC of 0.986 and an SPCC figure-of-merit F
1 = 0.64. When using only the data for the early-epoch challenge defined by the SPCC, we achieve a classification accuracy of 93.1%, AUC of 0.977, and F
1 = 0.58, results almost as good as with the whole light curve. By employing bidirectional neural networks, we can acquire impressive classification results between supernovae types I, II and III at an accuracy of 90.4% and AUC of 0.974. We also apply a pre-trained model to obtain classification probabilities as a function of time and show that it can give early indications of supernovae type. Our method is competitive with existing algorithms and has applications for future large-scale photometric surveys.
Surface Variability of Short-wavelength Radiation and Temperature on Exoplanets around M Dwarfs
Authors: Zhang Xin , Tian Feng , Wang Yuwei , Dudhia Jimy , Chen Ming
Published: March 2017

It is a common practice to use 3D General Circulation Models (GCM) with spatial resolution of a few hundred kilometers to simulate the climate of Earth-like exoplanets. The enhanced albedo effect of clouds is especially important for exoplanets in the habitable zones around M dwarfs that likely have fixed substellar regions and substantial cloud coverage. Here, we carry out mesoscale model simulations with 3 km spatial resolution driven by the initial and boundary conditions in a 3D GCM and find that it could significantly underestimate the spatial variability of both the incident short-wavelength radiation and the temperature at planet surface. Our findings suggest that mesoscale models with cloud-resolving capability be considered for future studies of exoplanet climate.
Is Proxima Centauri b Habitable? A Study of Atmospheric Loss
Authors: Dong Chuanfei , Lingam Manasvi , Ma Yingjuan , Cohen Ofer
Published: March 2017

We address the important question of whether the newly discovered exoplanet, Proxima Centauri b (PCb), is capable of retaining an atmosphere over long periods of time. This is done by adapting a sophisticated multi-species MHD model originally developed for Venus and Mars and computing the ion escape losses from PCb. The results suggest that the ion escape rates are about two orders of magnitude higher than the terrestrial planets of our Solar system if PCb is unmagnetized. In contrast, if the planet does have an intrinsic dipole magnetic field, the rates are lowered for certain values of the stellar wind dynamic pressure, but they are still higher than the observed values for our solar system’s terrestrial planets. These results must be interpreted with due caution since most of the relevant parameters for PCb remain partly or wholly unknown.
Production of more durable and sustainable concretes using volcanic scoria as cement replacement
Authors: Al-Swaidani A. M.
Published: March 2017

The objective of the study is to investigate strength and durability-related properties of volcanic scoria-based cements. Compressive and tensile strength development of mortars and concretes containing volcanic scoria with replacement levels ranging from 10 to 35% was investigated. Water permeability, chloride penetrability and porosity of concretes cured for 2, 7, 28, 90 and 180 days were also examined. Results revealed that volcanic scoria could be suitable for making blended cements. The strength of mortar/concrete containing volcanic scoria was lower than that of plain cement mortar/concrete at all ages. However, at 90 day curing, the strengths of volcanic scoria-based mortars/concretes were comparable to those of plain cement. In addition, water permeability, chloride penetrability and porosity of scoria-based concretes were much lower than those of plain concrete. Further, the results were statistically analysed and estimation equations have been developed to predict the studied properties. SEM/EDX analysis was employed, as well.
A Comprehensive Literature Review on Nature-Inspired Soft Computing and Algorithms
Authors: Ervural Bilal , Ervural Beyzanur Cayir , Kahraman Cengiz
Published: March 2017

Soft Computing techniques are capable of identifying uncertainty in data, determining imprecision of knowledge, and analyzing ill-defined complex problems. The nature of real world problems is generally complex and their common characteristic is uncertainty owing to the multidimensional structure. Analytical models are insufficient in managing all complexity to satisfy the decision makers' expectations. Under this viewpoint, soft computing provides significant flexibility and solution advantages. In this chapter, firstly, the major soft computing methods are classified and summarized. Then a comprehensive review of eight nature inspired – soft computing algorithms which are genetic algorithm, particle swarm algorithm, ant colony algorithms, artificial bee colony, firefly optimization, bat algorithm, cuckoo algorithm, and grey wolf optimizer algorithm are presented and analyzed under some determined subject headings (classification topics) in a detailed way. The survey findings are supported with charts, bar graphs and tables to be more understandable.
A Survey of Computational Intelligence Algorithms and Their Applications
Authors: Bouarara Hadj Ahmed
Published: March 2017

This chapter subscribes in the framework of an analytical study about the computational intelligence algorithms. These algorithms are numerous and can be classified in two great families: evolutionary algorithms (genetic algorithms, genetic programming, evolutionary strategy, differential evolutionary, paddy field algorithm) and swarm optimization algorithms (particle swarm optimisation PSO, ant colony optimization (ACO), bacteria foraging optimisation, wolf colony algorithm, fireworks algorithm, bat algorithm, cockroaches colony algorithm, social spiders algorithm, cuckoo search algorithm, wasp swarm optimisation, mosquito optimisation algorithm). We have detailed each algorithm following a structured organization (the origin of the algorithm, the inspiration source, the summary, and the general process). This paper is the fruit of many years of research in the form of synthesis which groups the contributions proposed by various researchers in this field. It can be the starting point for the designing and modelling new algorithms or improving existing algorithms.
Speaker Recognition With Normal and Telephonic Assamese Speech Using I-Vector and Learning-Based Classifier
Authors: Sharma Mridusmita , Kaushik Rituraj , Sarma Kandarpa Kumar
Published: March 2017

Speaker recognition is the task of identifying a person by his/her unique identification features or behavioural characteristics that are included in the speech uttered by the person. Speaker recognition deals with the identity of the speaker. It is a biometric modality which uses the features of the speaker that is influenced by one's individual behaviour as well as the characteristics of the vocal cord. The issue becomes more complex when regional languages are considered. Here, the authors report the design of a speaker recognition system using normal and telephonic Assamese speech for their case study. In their work, the authors have implemented i-vectors as features to generate an optimal feature set and have used the Feed Forward Neural Network for the recognition purpose which gives a fairly high recognition rate.
Modeling and Simulation of Surface Texture for End-Milling Process
Authors: Kumar Manoj
Published: March 2017

Analysis and simulation of manufacturing process require extensive and complicated computations. Nowadays, computer resources and computational algorithms reach to the state that can model and simulate the problem efficiently. One of the important processes in manufacturing is machining. In this research end-milling process which is one of the complex and wide-spread processes in machining is chosen. Most important parameters in end-milling are surface roughness and surface location errors. A comprehensive simulation software is developed to model end-milling process in order to anticipate finishing parameter such as surface roughness and errors. The proposed algorithm takes into account cutting conditions, such as feed, doc, woc, tool run out, etc. In addition, dynamic simulation module of the software can accurately model flexible end-mill tool, the milling cutting forces and regeneration of waviness effects. The software can accurately determine the most commonly used index of surface roughness parameters such as Ra, P.T.V. and surface errors.
Modeling and Analysis of Cold Drawing Process
Authors: Loharkar Praveen Kumar , Pradhan Mohan Kumar
Published: March 2017

Products of cold drawing process are extensively used due to their characteristics such as very good surface finish, close dimensional control and superior mechanical properties. Therefore, this process has drawn attention of several researchers over the years. The chapter describes the state of research scenario in the field of cold drawing process analysis with a focus on various parameters and methods involved in its study. Work carried out in this context is described briefly along with the steps to carry out finite element analysis. It has also accounted for methods to design experiments and to optimize the process parameters. Upon reading this chapter, the reader would get acquainted with various aspects of cold drawing process modeling and scope for further research. With the help of fundamental knowledge of process and systematic application of the available tools and techniques, the reader would be equipped with the knowledge to work on related industrial problems and enhance process capability by applying soft computing techniques in process optimization.
Optimization of Laser Transmission Welding Parameters Using Chicken Swarm Optimization Algorithm
Authors: Acherjee Bappa , Maity Debanjan , Kuar Arunanshu S. , Mitra Souren , Misra Dipten
Published: March 2017

The ever-increasing demand of high quality joints with improved cycle times leads the industries, those involve welding of plastics, to use laser for welding plastics. Laser transmission welding is the latest development in the field of welding of plastics. In present research work, experimental investigation, parametric modeling and optimization of laser transmission welding of polycarbonate is carried out. A systematic experimental plan is executed using central composite design of response surface methodology (RSM). Mathematical models are developed using RSM for establishing an interrelationship between the process parameters and the responses of interest. Chicken swarm optimization (CSO) algorithm is employed with the developed RSM models to set the optimal process parameters combinations to achieved desired weld qualities. Here, the objectives are set as to increase the weld strength and decrease the weld width independently, as well as simultaneously. The interdependent parametric trends are also studied and discussed.
Impact of Human Resources on Quality After Just-in-Time Implementation
Authors: Molina Teresita , García-Alcaraz Jorge Luis , Loya Valeria Martínez , Tanino Nadia Sofia , Tlapa Diego
Published: March 2017

Nowadays maquiladoras require improving processes and reducing costs in order to stay in the market and be competitive. Just in Time (JIT), the lean manufacturing tool, works specifically on materials handling, but critical success factors (CSFs) for its implementation are unknown. For this reason, in this chapter the results of a survey applied to 372 maquiladora workers of Ciudad Juárez (México) are reported. Six hypotheses are proposed and validated through a structural equations model executed in WarpPLS 5.0® software, where four latent variables related with Management Commitment, Human Resources, Suppliers and Quality benefits in a JIT environment are associated. Direct effects, indirect effects and total effects of each one of the variables are analyzed. The results show there is enough statistical evidence to state that there is a direct and positive impact of Human Resources on the obtained Quality in a JIT environment application.
Prediction of Water Quality Indices by Using Artificial Neural Network Models
Authors: Mishra Prakash Chandra , Giri Anil Kumar
Published: March 2017

Conventionally, fixed techniques are used for prediction of future time-series data. Subsequently adaptive techniques are used to forecast improved future data. The adaptive techniques are essentially based on ANN and fuzzy logic techniques. It is observed that these techniques also perform poorly when the input data set available is less and when there is abrupt change in the input data set. In this paper the proposed hybrid technique is based on data farming for intermediate data generation and the ANN model for better learning and forecasting. The performance of the proposed model has been tested with actual pertaining to water quality indices of various water samples collected from different sources.
A Cloud Computing Adoption Framework for Developing Countries
Authors: Ta Anh D.
Published: March 2017

This chapter explores Cloud computing adoption strategies for small and medium enterprises (SMEs) and microenterprise that can enhance the economic growth of local industries in developing countries. This focus is based on the recognitions that (1) economic growths of local industries reduce poverty through the creation of new jobs for poor people to earn a living wage and support their families, and (2) there is a lack of research on Cloud computing adoption strategy that addresses the unique constraints of small and medium enterprises (SMEs) in developing countries.
An Efficient All Shapes Busy List Processor Allocation Algorithm for 3D Mesh Multicomputers
Authors: Bani-Mohammad Saad
Published: March 2017

Contiguous processor allocation is useful for security and accounting reasons. This is due to the allocated jobs are separated from one another, where each sub-mesh of processors is allocated to an exclusive job request, and the allocated sub-mesh has the same size and shape of the requested job. The size and shape constraint leads to high processor fragmentation. Most recent contiguous allocation strategies suggested for 3D mesh-connected multiconputers try all possible orientations of an allocation request when allocation fails for the requested orientation, which reduces processor fragmentation and hence improves system performance. However, none of them considers all shapes of the request in the process of allocation. To generalize this restricted rotation, we propose, in this paper, a new contiguous allocation strategy for 3D mesh-connected multicomputers, referred to as All Shapes Busy List (ASBL for short), which takes into consideration all possible contiguous request shapes when attempting allocation for a job request. ASBL depends on the list of allocated sub-meshes, in the method suggested in (Bani-Mohammad et al., 2006), for selecting an allocated sub-mesh. The performance of the proposed ASBL allocation strategy has been evaluated considering several important scheduling strategies under a variety of system loads based on different job size distributions. The simulation results have shown that the ASBL allocation strategy improves system performance in terms of parameters such as the average turnaround time of jobs and system utilization under all scheduling strategies considered.
Homomorphic Encryption as a Service for Outsourced Images in Mobile Cloud Computing Environment
Authors: Ibtihal Mouhib , Driss El Ouadghiri , Hassan Naanani
Published: March 2017

The integration of cloud computing with mobile computing and internet has given birth to mobile cloud computing. This technology offers many advantages to users, like Storage capacity, Reliability, Scalability and Real time data availability. Therefore, it is s increasing fast and it is inevitably integrated into everyday life. In MCC, data processing and data storage can be migrated into the cloud servers. However, the confidentiality of images and data is most important in today's environment. In this paper, we mainly focus on secure outsourcing of images. For this purpose, we propose a secure architecture composed by two clouds a private cloud dedicated for encryption/decryption and a second public cloud dedicated for storage. We have implemented the first cloud using openstack while respecting the encryption as a service concept. As an encryption scheme, we have used paillier's homomorphic cryptosystem designed specifically for images. The test of the homomorphic property is done by applying the Watermarking algorithm DWT.
Envy Sensitivity on Twitter and Facebook Among Japanese Young Adults
Authors: Yoshida Shogoro , Hijikata Yoshinori
Published: March 2017

Social media such as Facebook and Twitter have grown to be popular communication tools that, ironically, have a negative aspect of increasing users' opportunity to feel envy. In this study, the authors examine the difference in the envy sensitivity people feel when online using several different social media and offline from social media (Study 1) and the types of people who are sensible to envy (Study 2), analyzing data gathering through questionnaire survey. The authors target Facebook and Twitter in this survey. As the results, Study 1 shows that people's envy sensitivity differ between offline from social media, on Twitter and on Facebook. Study 2 shows that people's envy sensitivity when on social media differed by their demographic categories. They also find that some types of usage objectives and user actions on social media are correlated with envy sensitivity. The authors hope that their findings will contribute to understanding the envy on social media and will help people avoid or cope with their envy.
Development and Validation of Teachers Mobile Learning Acceptance Scale for Higher Education Teachers
Authors: Mittal Niti , Chaudhary Monica , Alavi Shirin
Published: March 2017

Technological advancements in mobile devices coupled with their increased use in informal and formal learning at an individual level have forced academicians to implement full-scale mobile learning in higher education. However, its full-scale implementation can be achieved if the perception and attitude towards its acceptance are studied from the viewpoint of higher education teachers. This exploratory study begins with the identification of potential determinants of mobile learning acceptance. Thereafter, Teachers Mobile Learning Acceptance Scale was developed based on the explored factors. There is no available instrument so far that encompasses important factors for determining acceptance of mobile learning by higher education teachers in ‘one go'. This instrument serves to be a comprehensive measure of teacher's acceptance of mobile learning. Two new factors ‘teacher authority and privacy' and ‘motivational factors for students' have been added. Although these factors have not been addressed in the past research, yet they play a significant role when considered from teachers' perspective. This instrument depicts a high level of content validity and reliability.
Aras
Authors: Barkhordari Mohammadhossein , Niamanesh Mahdi
Published: March 2017

Because of to the high rate of data growth and the need for data analysis, data warehouse management for big data is an important issue. Single node solutions cannot manage the large amount of information. Information must be distributed over multiple hardware nodes. Nevertheless, data distribution over nodes causes each node to need data from other nodes to execute a query. Data exchange among nodes creates problems, such as the joins between data segments that exist on different nodes, network congestion, and hardware node wait for data reception. In this paper, the Aras method is proposed. This method is a MapReduce-based method that introduces a data set on each mapper. By applying this method, each mapper node can execute its query independently and without need to exchange data with other nodes. Node independence solves the aforementioned data distribution problems. The proposed method has been compared with prominent data warehouses for big data, and the Aras query execution time was much lower than other methods.
The Sense-it App
Authors: Sharples Mike , Aristeidou Maria , Villasclaras-Fernández Eloy , Herodotou Christothea , Scanlon Eileen
Published: March 2017

The authors describe the design and formative evaluation of a sensor toolkit for Android smartphones and tablets that supports inquiry-based science learning. The Sense-it app enables a user to access all the motion, environmental and position sensors available on a device, linking these to a website for shared crowd-sourced investigations. The authors describe the four investigations with the toolkit: environmental noise, sunlight levels, air pressure and rainfall, and the speed of lifts (elevators). These show a variety of methods to initiate, orchestrate and conclude inquiry-based science learning. Two of the missions are in the context of a study to develop a community of inquiry around weather and meteorology. The others are intended to engage members of the public in practical science activities. Analysis of the missions and the associated online discussions reveals that the Sense-it toolkit can be adopted for engaging science investigations, though the practical issue of calibrating sensors on personal devices needs to be addressed.
An Empirical Comparison of Java and C# Programs in Following Naming Conventions
Authors: Ebad Shouki A. , Manzoor Danish
Published: March 2017

An important indicator of source code quality is compliance with naming conventions. It is believed that such practices improve program comprehension, which directly affects maintainability and reusability. In this paper, the authors conduct an experiment to determine how well Java and C# programs follow a set of well-publicized naming practices. The experiment evaluated 120 arbitrarily selected open-source Java and C# classes from different programmers with respect to four naming conventions. The results indicate that Java and C# programs do not always follow naming conventions. However, Java developers are more attentive than C# developers in terms of following naming practices. A disturbing trend was found in variable and constant naming conventions, which were violated in most C# subjects. Moreover, there is a positive correlation between the number of violations found in a C# class and its size but a negative correlation in case of Java class. The findings are expected to contribute to the existing knowledge of the use of coding standards and source code quality. The paper also discusses the threats to the validity of the study and suggests open issues for future research.
A Case Study on the Socio-Economic Conditions of the Artisanal Fisheries in the Cagayan De Oro River
Authors: Almaden Catherine Roween C.
Published: March 2017

Freshwater fishing is an important socioeconomic aspect of the communities in the Cagayan de Oro River (CDOR), Philippines. The fishery sector in CDOR has the elements that are generally characteristic of artisanal or small-scale fisheries. Before this study, very little was known of the scope and magnitude of artisanal level fishing activities within the CDOR. It has remained undocumented by Local Government Units (LGUs) as it does not contribute directly to the economy in terms of measurable cash flow. However, a number of fishes in the river have higher commercial value compared to marine fisheries in the nearby Macajalar Bay. This study is an attempt to examine the conditions of the CDOR fisheries and to quantify its economic contributions. The economic contribution is measured in terms of the market value of captured aquatic resources. In order to establish the behavior and trends in the fisheries of the different communities, the study area was divided into three sub-zones. Data in this study were collected through interviews of identified fishermen in the different sub-zones. Majority of the fishermen venture into other menial jobs due to proximity to the urban center. Many of them have subsidiary occupations which serve the dual purpose of alternative income and job opportunities and food source because fishing is seasonal. The peak fishing season usually spans two to four months. Comparatively, the earnings derived by the Cagayan de Oro River fishermen are relatively in almost the same range as the marine fishermen in the different parts of the country.
Perceived Use and Acceptance of Cloud Enterprise Resource Planning (ERP) Implementation in the Manufacturing Industries
Authors: Adeboye Adewale
Published: March 2017

The purpose of this study was to gain an insight into perceived use and acceptance for implementing an enterprise resource planning (ERP) system and the decision whether to contract out the ERP service to a cloud provider. A non-experimental, quantitative method of analysis was used for this research and a survey instrument developed by Venkatesh (2003) was used to gather data from information technology professionals in the United States. The data generated were tested using Chi Square and Multiple Regression. Chi square was used to test the hypotheses and the result establishes a pertinent relationship between the dependent variable and the independent variables. Multiple regression analysis was also conducted on the four independent variables and all of the independent variables tested have a p- value that is greater than 0.05 (p>0.05). Hence, it was concluded that the null hypothesis be accepted for all the four independent variables tested.
Technology Diffusion Determines Productivity Distribution and Aggregate Growth
Authors: Kumar Manoj
Published: March 2017

This paper studies how technology diffusion interacts to endogenously determine the productivity distribution and generate aggregate growth. This paper models firms that choose to adopt technology, or produce with their existing technology. In the context of technology diffusion, one therefore has to consider whether redistributive revenues of the government may, in fact, be allocated towards reducing the fixed costs associated with productive technologies. This paper presents a model in which the cost of technology diffusion is endogenous and varies across heterogeneous firms. The results indicate that the technology with low productivity is used by the majority of individuals in the early stages of development. At this stage, a relatively higher level of inequality characterizes the income distribution. As capital deepening and redistribution of income and wealth takes place, the inequality among individuals tends to decrease. Once this happens individuals prefer a relatively larger proportion of government revenue to be allocated towards cost-reducing Research and Development (R&D) expenditures. Eventually all individuals make the switch to the better technology and consequently their incomes converge.