Critical success factors in ERP implementation: A review

ERP systems have become vital strategic tools in today’s competitive business environment. This ongoing research study presents a review of recent research work in ERP systems. It attempts to identify the main benefits of ERP systems, the drawbacks and the critical success factors for implementation discussed in the relevant literature. The findings revealed that despite some organizations have faced challenges undertaking ERP implementations, many others have enjoyed the benefits that the systems have brought to the organizations. ERP system facilitates the smooth flow of common functional information and practices across the entire organization. In addition, it improves the performance of the supply chain and reduces the cycle times. However, without top management support, having appropriate business plan and vision, re-engineering business process, effective project management, user involvement and education and training, organizations can not embrace the full benefits of such complex system and the risk of failure might be at high level

The role of senior executives in managing key customers in Arab context

Purpose: The purpose of this paper is to explore the role of senior managers in managing intra-and inter-organizational relationships with key customers and the factors that influence such involvement in a novel context in the Arab Middle East region. Design/methodology/approach: An exploratory qualitative research design was used in which 68 face-to-face semi-structured interviews were conducted in Jordan with endogenous and Western firms. Findings: Top/senior managers play a significant role in Arab business relationships and in creating value for the firms. Their involvement in key accounts is imperative at all levels – strategic, operational, and relational – mainly due to cultural and institutional factors that are unique to the Arab context. Research limitations/implications: The study is limited to operations in one emerging country situated in a novel setting in one particular region of the world, which is the Middle East. Practical implications: Arab senior managers’ participation is imperative and should continue with their relatively intense involvement with key accounts. For foreign investors operating in that part of the world, it is highly recommended that senior management have a more a hands-on approach when dealing with the Arab key customer and to focus more on the relational aspect of key account management than on the organizational aspect. Originality/value: This paper adds to the very limited number of studies on senior management involvement in key account management, making a theoretical and practical contribution and adding insight on how to manage the relationship with the Arab key customer

Unsupervised Multimodal Surface Registration with Geometric Deep Learning

This paper introduces GeoMorph, a novel geometric deep-learning framework designed for image registration of cortical surfaces. The registration process consists of two main steps. First, independent feature extraction is performed on each input surface using graph convolutions, generating low-dimensional feature representations that capture important cortical surface characteristics. Subsequently, features are registered in a deep-discrete manner to optimize the overlap of common structures across surfaces by learning displacements of a set of control points. To ensure smooth and biologically plausible deformations, we implement regularization through a deep conditional random field implemented with a recurrent neural network. Experimental results demonstrate that GeoMorph surpasses existing deep-learning methods by achieving improved alignment with smoother deformations. Furthermore, GeoMorph exhibits competitive performance compared to classical frameworks. Such versatility and robustness suggest strong potential for various neuroscience applications

Robust and Generalisable Segmentation of Subtle Epilepsy-causing Lesions: a Graph Convolutional Approach

Focal cortical dysplasia (FCD) is a leading cause of drug-resistant focal epilepsy, which can be cured by surgery. These lesions are extremely subtle and often missed even by expert neuroradiologists. "Ground truth" manual lesion masks are therefore expensive, limited and have large inter-rater variability. Existing FCD detection methods are limited by high numbers of false positive predictions, primarily due to vertex- or patch-based approaches that lack whole-brain context. Here, we propose to approach the problem as semantic segmentation using graph convolutional networks (GCN), which allows our model to learn spatial relationships between brain regions. To address the specific challenges of FCD identification, our proposed model includes an auxiliary loss to predict distance from the lesion to reduce false positives and a weak supervision classification loss to facilitate learning from uncertain lesion masks. On a multi-centre dataset of 1015 participants with surface-based features and manual lesion masks from structural MRI data, the proposed GCN achieved an AUC of 0.74, a significant improvement against a previously used vertex-wise multi-layer perceptron (MLP) classifier (AUC 0.64). With sensitivity thresholded at 67%, the GCN had a specificity of 71% in comparison to 49% when using the MLP. This improvement in specificity is vital for clinical integration of lesion-detection tools into the radiological workflow, through increasing clinical confidence in the use of AI radiological adjuncts and reducing the number of areas requiring expert review.Comment: accepted at MICCAI 202

Surgical Skill Assessment on In-Vivo Clinical Data via the Clearness of Operating Field

Surgical skill assessment is important for surgery training and quality control. Prior works on this task largely focus on basic surgical tasks such as suturing and knot tying performed in simulation settings. In contrast, surgical skill assessment is studied in this paper on a real clinical dataset, which consists of fifty-seven in-vivo laparoscopic surgeries and corresponding skill scores annotated by six surgeons. From analyses on this dataset, the clearness of operating field (COF) is identified as a good proxy for overall surgical skills, given its strong correlation with overall skills and high inter-annotator consistency. Then an objective and automated framework based on neural network is proposed to predict surgical skills through the proxy of COF. The neural network is jointly trained with a supervised regression loss and an unsupervised rank loss. In experiments, the proposed method achieves 0.55 Spearman's correlation with the ground truth of overall technical skill, which is even comparable with the human performance of junior surgeons.Comment: MICCAI 201

Contribution of copy number variants (CNVs) to congenital, unexplained intellectual and developmental disabilities in Lebanese patients

International audienceBackground: Chromosomal microarray analysis (CMA) is currently the most widely adopted clinical test for patients with unexplained intellectual disability (ID), developmental delay (DD), and congenital anomalies. Its use has revealed the capacity to detect copy number variants (CNVs), as well as regions of homozygosity, that, based on their distribution on chromosomes, indicate uniparental disomy or parental consanguinity that is suggestive of an increased probability of recessive disease. Results: We screened 149 Lebanese probands with ID/DD and 99 healthy controls using the Affymetrix Cyto 2.7 M and SNP6.0 arrays. We report all identified CNVs, which we divided into groups. Pathogenic CNVs were identified in 12.1% of the patients. We review the genotype/phenotype correlation in a patient with a 1q44 microdeletion and refine the minimal critical regions responsible for the 10q26 and 16q monosomy syndromes. Several likely causative CNVs were also detected, including new homozygous microdeletions (9p23p24.1, 10q25.2, and 8p23.1) in 3 patients born to consanguineous parents, involving potential candidate genes. However, the clinical interpretation of several other CNVs remains uncertain, including a microdeletion affecting ATRNL1. This CNV of unknown significance was inherited from the patient's unaffected-mother; therefore, additional ethnically matched controls must be screened to obtain enough evidence for classification of this CNV. Conclusion: This study has provided supporting evidence that whole-genome analysis is a powerful method for uncovering chromosomal imbalances, regardless of consanguinity in the parents of patients and despite the challenge presented by analyzing some CNVs

Quantification of three macrolide antibiotics in pharmaceutical lots by HPLC: Development, validation and application to a simultaneous separation

A new validated high performance liquid chromatographic (HPLC) method with rapid analysis time and high efficiency, for the analysis of erythromycin, azithromycin and spiramycin, under isocratic conditions with ODB RP18 as a stationary phase is described. Using an eluent composed of acetonitrile –2-methyl-2-propanol –hydrogenphosphate buffer, pH 6.5, with 1.5% triethylamine (33:7: up to 100, v/v/v), delivered at a flow-rate of 1.0 mL min-1. Ultra Violet (UV) detection is performed at 210 nm. The selectivity is satisfactory enough and no problematic interfering peaks are observed. The procedure is quantitatively characterized and repeatability, linearity, detection and quantification limits are very satisfactory. The method is applied successfully for the assay of the studied drugs in pharmaceutical dosage forms as tablets and powder for oral suspension. Recovery experiments revealed recovery of 97.13–100.28%