Lotfollah Najjar

The influence of work‐cells and facility layout on the manufacturing efficiency

Purpose – The purpose of this paper is to analyse the use of a product‐oriented layout and a work‐cell strategy in order to maximise efficiency. These two categories of layout strategies are discussed separately, and are then used collectively in an analysis of the company. The aim is to understand how improvements on layout design could positively impact the future efficiency of the case study company.Design/methodology/approach – A model was developed and measured using 26 weeks of data between the fourth quarter of 2009 and the first quarter of 2010 during layout transformations at the case study company based in upstate New York. The model compared variables such as the distance traveled to retrieve parts, average daily output of engines, labour cost per unit produced, and the amount of time the engine remains in each cell; the aim of which is to increase the efficiency of the facility.Findings – The findings indicate that there is a strong correlation between the variables improved at both the cell‐s...

Incorporating Community Detection and Clustering Techniques into Collaborative Filtering Model

Abstract Recommender systems seek to predict the ‘rating’ or ‘preference’ that user would give to an item based upon historical grading datasets.At the era of IT, the Internet has the ability to reflect the social network, which makes possible to incorporate community detection and clustering algorithms to improve their performance. That is, we can discover the hidden information present in the social network by using community detection algorithms, and use clustering technique to reveal users’ preference on the basis of their behavioral history. Such information is used as feedback to our recommender system to improve the prediction accuracy. Based on this consideration, in this research, we revise the well-known SVD (Singular Value Decomposition) algorithm andhave made two contributions. First, we derive groups by overlapping the communities with the clusters, and feed them as implicit feedback to SVD++. In addition, we introduce a matrix, referred to as difference matrix, and use it as an input to our algorithm. The resulting model is referred to as difference-SVD. We test all the models on Baidus dataset, which is a large data set on movie recommendation. The results show that difference-SVD is quite promising: While both SVD++ and difference-SVD show higher accuracy than SVD, difference-SVD outperforms SVD++ in that it runs fasterthan SVD++.

Modeling the Effects of Microgravity on Oxidation in Mitochondria: A Protein Damage Assessment across a Diverse Set of Life Forms

Exposure to microgravity conditions is detrimental to animal and human protein tissue and is linked to ailments associated with aging, disease and other disorders originating at the protein level. With exposure, dangerously low blood pressure results from diminished blood production forces the heart to beat at abnormal rates and causes damage. The heart, like the other muscles of the body, risk developing muscular atrophy from the reduced dependence on muscle-use. Oxidative carbonylation, the addition of a CO to an amino acid chain, is a natural process used by the cell to degrade and remove proteins. This reaction may also cause many of the diseases associated with protein dysfunction (Alzheimers, muscular atrophy, Parkinsons, sepsis, etc.). Although aging has been associated with similar ailments from protein degradation, the stress from weightlessness is thought to increase the rates of oxidative processes impacting general health by upsetting protein function and its structure. Carbonylation is an oxidative reaction for which, motifs high in R, K, P, T, E and S residues can be used to explore its composition in protein data. Since mitochondria also apply oxidative processes to make energy, we hypothesize that this reaction is highly contained so as to minimize local oxidative damage. In this paper, we evaluate the coverage of motifs which are likely attractors of oxidative activity across mitochondrial and non-mitochondrial protein data of fourteen diverse organisms. Here we show that mitochondrial proteins have generally reduced amounts of the same oxidative carbonylation content which we found in abundance in the organisms nuclear proteins. Furthermore, we show that this general finding is similar between two major profiling systems: oxidative carbonylation (RKPT enriched sequences) and protein degradation (PEST sequences). We suggest an mitochondrial intolerance for motifs that may attract forms of oxidation.

Information and communications technology use and income growth: evidence of the multiplier effect in very small island states

ABSTRACT Very small island states face unique challenges, such as volatile economies, increasing vulnerability to natural disasters, particularly with raising seas, increases their dependence on the world economy. Despite their growing use of ICTs, the results are mixed in terms of the effect of growing ICT usage on income growth. This paper investigates how growth in ICT usage may enable growth in per capita Gross Domestic Product (GDP) in very small island states by analyzing the effects of average ICT usage on GDP growth based on the most recent data available from the World Bank and from the International Telecommunications Union (ITU). Following an analysis of data over four years of 32 very small island states, this paper identifies an ICT multiplier effect that may explain and predict the relationship between average ICT usage and GDP growth. By showing how the ICT multiplier effects may be connected to GDP growth, this paper adds to what we know about the relationship between these two indicators in very small island states. This has implications for how government interventions can enable ICT capacity to bring about GDP growth.

Evidence of a Pathway of Reduction in Bacteria: Reduced Quantities of Restriction Sites Impact tRNA Activity in a Trial Set

Occurring naturally along the genomes of many viruses and other pathogens, short palindromic restriction sites (<14bps) are often exploited by bacterial restriction enzymes as autoimmune defenses to end pathogen threats. These motifs may also appear in the hosts genome where they are methylated so as not to attract restriction enzymes to the hosts genetic material. Since these motifs in the hosts genome may pose a significant danger, it is likely that their numbers have been reduced due to possible failures of methylation during evolutionary time. These palindromes are composed of bases likely containing information relating to codons used for protein translation. If palindromes are reduced in the genome, then its sequence composition making up the codons may also be found in reduced quantities. Furthermore, during translation codons are associated with tRNAs for protein fabrication which may also occur in reduced numbers. We suggest that a pathway of reduction that can be followed from the onset of these missing palindromes to the reduction (or absence) of specific tRNAs correlated to the codons from the palindromes. To create evidence for this pathway, we studied the bacterial genomes of Bacillus subtilis, Escherichia coli, Haemophilus influenzae, Methanococcus jannaschii, Mycoplasma genitalium, Synechocystis sp. and Marchantia polymorpha. Across these organisms, we applied statistical data from reduced palindromic populations (biological and non-relevant words) to regression models and performed an analysis of genomic tRNA presence from their compositions. We illustrate a pathway of reduction that extends from palindromes to tRNAs which may follow from evolutionary pressures concerning restriction site handling.

Using gait parameters to recognize various stages of Parkinson's disease

Monitoring gait patterns seamlessly and continuously over time provides valuable information that could help physicians diagnose diseases in the early stages. Currently, traditional gait measurement approaches do not support continuous monitoring of gait and focus on collecting limited data points in controlled lab environments. However, with advancements in wireless technology, movement patterns can be recorded using small portable wearable devices. Parkinsons disease (PD) is a progressively disabling neurodegenerative disorder that is affecting gait and posture and consequently leads to higher risk of falling. Several research studies have looked into changes in the gait parameters of PD patients compared to healthy adults. However, there are only few studies with the focus on gait assessment of PD patients in the early stages as compared to patterns associated with patients at advanced stages. In addition, the number of gait-related studies in this domain using accelerometers on ankle is very limited. Knowing which body location could serve as a target place for accelerometers to provide accurate information is a necessary step toward the health assessment of PD patients. The purpose of this study was to evaluate the gait parameters of patients with mild or moderate PD using accelerometers on ankles. A number of gait parameters, including average stride time, stride time variability, stride time symmetry, and oscillation of acceleration in the mediolateral (ML) direction were calculated and compared between PD patients and healthy elderlies. Preliminary results indicate that features extracted from accelerometers on ankles can be effective in differentiating between healthy elderlies and PD patients at mid-stages of disease but less so at earlier stages of disease.

Emerging Technology Use in Very Small Island States: A Tenuous Relationship between Average Information and Communication Technology (ICT) Usage and Per Capita Gross Domestic Product (GDP) Growth

Very small island states face unique challenges, such as volatile economies increasingly vulnerable to climate change. They are used in this analysis because their populations rely on emerging technologies for their livelihoods, especially growing mobile phone usage. This paper investigates how growth in ICT usage may enable growth in per capita GDP in very small island states by analyzing the effects of average ICT usage on GDP growth based on the most recent data. Following an analysis of data over four years, of 32 very small island states, this paper identifies an ICT multiplier effect that can explain and predict the relationship between average ICT usage and GDP growth. By showing how the ICT multiplier effect may be connected to GDP growth, this paper adds to what we know about the relationship between these two indicators. This has implications for how government interventions can enable ICT capacity to bring about GDP growth.

The Antecedents of Commitment towards Collaborative Work Practice Outcomes

Collaboration technologies offer benefits for organizations to make teamwork more productive and creative. Yet the organizational transition towards using particular types of collaboration technologies is often fraught with challenges. A key condition for successfully transitioning towards a new way of working is that the stakeholders are committed to the outcomes of the new collaboration process. Little is known about the antecedents of this commitment. This study investigates the antecedents of user commitment using the Technology Transition Model (TTM) and Yield Shift Theory (YST). Specifically, this study examines the effect of satisfaction with process (SP), satisfaction with outcomes (SO), and perceived magnitude of net value (MNV) on user commitment (C) to the results of collaborative work practices. Subjects from three international organizations participated in the study. Results show that MNV and SO predict commitment while SP partially predicted commitment, with MNV the strongest predictor.

PathwayLinks: Network analysis of metabolic pathways across bacterial organisms in a community

The Human Microbiome Project (HMP) recognizes that several microbiome environments reside within the human body (such as the mouth and the GI tract). HMP is involved in documenting and sequencing bacteria existing in these environments. These environments can be considered to host a community of bacteria, where one bacterium may provide support for the metabolic needs of other bacteria. Publicly available metabolic pathway information exists for many of these organisms, most notably the well-established KEGG database. To predict the metabolic relationships that exist between organisms living in a community, we analyzed publicly available metabolic data and developed a set of procedures whose input is a set of organisms in a community and whose output is a set of predictions of possible metabolic linkages between them. We refer to these procedures collectively as the PathwayLinks procedures, as they find possible links between metabolic pathways. A pilot study was conducted using the well-known Red-Complex of bacteria in the mouth, which is linked to gingivitis. Results indicate that the Citrulline and Protoporphyrin metabolites may link two of the key organisms in the complex. This research shows promise in providing a theoretical basis for predicting metabolic relationships between bacteria living in a community.

Comparative Analysis of Software Repository Metrics in BioPerl, BioJava and BioRuby

Abstract The open source programming languages, often with a bio- suffix, i.e. BioPerl, BioJava, and BioRuby, have been widely used in bioinformatics and computational biology research. The computational tools written in these languages provide multiple functionalities as the languages make them flexible to create customized analysis and examination of biological data. In this paper, we investigate one of the software quality parameters, maintainability, in BioPerl, BioJava, and BioRuby projects using comment density metric in their source code repositories of these three languages in bioinformatics communities using three other software metrics such as number of committers, commit frequency, and lines of code. To perform this study, source code repositories of these three open source projects have been analyzed from the first release, which covers all the programming activities of the projects from the starting date until July 2011. Our results show BioPerl to be the most popular language among the three languages in open source communities. In addition, investigation on comment density of these three open source projects has shown that BioPerl is the most promising one in terms of future maintainability and quality of the project. The results of this research can be useful for developers in choosing an appropriate language for the development of bioinformatics applications.