Face authentication system based on FDA and ANN.

Face authentication systems (FAS) are still in their infancy and many types of algorithms and techniques have been proposed to improve the ability of these systems. Artificial Neural Networks (ANN) have been commonly used as the classifiers for FAS whereas Fisher's Discrimination Analysis (FDA) has been used widely as the feature extractor. However, many current FAS still experiencing low accuracy rates using these techniques due to factors such as illumination, orientation and other disturbance. The purpose of this paper is to investigate the application of photometric normalization, linear subspace feature extraction, and ANN classification in enhancing FAS, and to build and evaluate the performance of the proposed FAS based on this approaches. We similarly used the popular ANN classification, namely Multi-Layer Perceptrons (MLP) as the classifier for our FAS as it has proven to be simple for implementation. meanwhile, we proposed linear subspace feature extraction techniques based on FDA to reduce the dimentionality of the face image. In addition, the photometric normalization techniques based on Histogram Equalization and Homomorphic Filtering are used to improve the appearance of the face. The effect of different combinations of the photometric normalization techniques on the performance of the proposed FAS was studied and the effectiveness of these techniques was highlighted. The results of the proposed FAS were compared among Eigenface and Fisherface FAS. It was discovered that using AT&T datasets, the proposed FAS solution outperformed the FAS based on Eigenface and Fisherface in term of False Acceptance and False Rejection rate. Furthermore, the experimental results demonstrated that MLP was able to produce better classification model that can satisfy the model authentication tests with significant advantages over Euclidean Distance, and Normalized Correlation classifier

Impaired haematopoietic stem cell differentiation and enhanced skewing towards myeloid progenitors in aged caspase-2-deficient mice

The apoptotic cysteine protease caspase-2 has been shown to suppress tumourigenesis in mice and its reduced expression correlates with poor prognosis in some human malignancies. Caspase-2-deficient mice develop normally but show ageing-related traits and, when challenged by oncogenic stimuli or certain stress, show enhanced tumour development, often accompanied by extensive aneuploidy. As stem cells are susceptible to acquiring age-related functional defects because of their self-renewal and proliferative capacity, we examined whether loss of caspase-2 promotes such defects with age. Using young and aged Casp2−/− mice, we demonstrate that deficiency of caspase-2 results in enhanced aneuploidy and DNA damage in bone marrow (BM) cells with ageing. Furthermore, we demonstrate for the first time that caspase-2 loss results in significant increase in immunophenotypically defined short-term haematopoietic stem cells (HSCs) and multipotent progenitors fractions in BM with a skewed differentiation towards myeloid progenitors with ageing. Caspase-2 deficiency leads to enhanced granulocyte macrophage and erythroid progenitors in aged mice. Colony-forming assays and long-term culture-initiating assay further recapitulated these results. Our results provide the first evidence of caspase-2 in regulating HSC and progenitor differentiation, as well as aneuploidy, in vivo.Swati Dawar, Nur Hezrin Shahrin, Nikolina Sladojevic, Richard J D, Andrea, Loretta Dorstyn, Devendra K Hiwase and Sharad Kuma

Understanding Network Congestion Effects On Performance: Article Review

Networking communications have become popular worldwide in human daily services. Network Congestion (NC) happens whenever because nodes and links are overloaded. Such situations affect the network expected performance and its services quality. Congestion /NC occurs as a results of its subnets’ links overload, which gradually (overtime) affects the network performance with an increase of transmission delay, a slowdown of throughput as generally perceived by network’s users. NC is considerable as the basis problem in network performance quality acceptance; and most of its existing problem solutions are expected still playing a great role in the future networks model, which will be running mostly too many multimedia applications. However, various researches over past years have initiated the study on the causes leading to congestion and, different lessons can be learnt from NC situations analysis to understand its relationship with the future network’s performance. This paper presents an analytical review of NC occurrence causes and the fundamentals of the existing control solutions/frameworks as available and studied from some former and recent networks publications. A particular attention has been paid throughout this study to found out how NC may still affect the future networks performance (i.e. QoS in the world of multimedia networks). And the coverage/content of this paper is expected to serve as a quick access to the knowledge essentials for researchers on related subject as stated in this paper topic

Analysis on Differential Router Buffer Size towards Network Congestion

Network resources are shared amongst a large number of users. Improper managing network traffic leads to congestion problem that degrades a network performance. It happens when the traffic exceeds the network capacity. In this research, We plan to observe the value of buffer size that contributes to network congestion. A simulation study by using OPNET Modeler 14.5 is conducted to achieve the purpose. A simple dumb-bell topology is used to observe several parameter such as number of packet dropped,retransmission count, end-to-end TCP delay, queuing delay and link utilization. The results show that the determination of buffer size based on Bandwidth-Delay Product (BDP) is still applicable for up to 500 users before network start to he congested. The symptom of near-congestion situation also being discussed corresponds to simulation results. Therefore, the buffer size needs to be determined to optimize the network performance based on our network topology. In future, the extension study will be carried out to investigate the effect of other buffer size models such as Stanford Model and Tiny Buffer Model.In addition, the buffer size has to be determined for wireless environment later on

Topology influence on TCP congestion control performance in multi-hop ad hoc wireless

Wireless ad hoc nodes are freely and dynamically self-organize in communicating with others.Each node can act as host or router.However it actually depends on the capability of nodes in terms of its current power level, signal strength, number of hops, routing protocol, interference and others.In this research, a study was conducted to observe the effect of hops count over different network topologies that contribute to TCP Congestion Control performance degradation.To achieve this objective, a simulation using NS-2 with different topologies have been evaluated.The comparative analysis has been discussed based on standard observation metrics: throughput, delay and packet loss ratio.As a result, there is a relationship between types of topology and hops counts towards the performance of ad hoc network.In future, the extension study will be carried out to investigate the effect of different error rate and background traffic over same topologies

Tunnel progression effects to the ground surface and the adjacent pile

Tunnelling close to existing structure in urban area has become unavoidable. The progression tunneling activities induced ground movement and might affect the integrity of existing structure especially the one lies within the tunneling influence zone. It may cause catastrophic failures of structures and can cause losses of human lives. Therefore, considering its risk, this study focuses on the tunnel-soil-pile interaction by performing a physical model testing. By conducting a series of laboratory tests, the ground subsidence and pile behavior is presented herein. For a twice diameter distance of tunnel and pile, the pile axial settlement is 0.04% of the tunnel diameter respectively, while the maximum pile bending moment is 4928. 93kN.m. Maximum ground settlement is 0.56% respectively to tunnel diameter. To sum up, the axial displacement of pile decreases when the pile located further away from the tunneling zone. Similarly, the ground surface subsidence decreases when the pile location is more in distance during the tunneling advancement

Convergence study for rock unconfined compression test using discrete element method

Mesh convergence is a vital issue that needs to be addressed in a numerical model. This study investigated the effects of mesh element number on the Discrete Element Method (DEM) to granite rock response under compression loading. This study used the 3D finite-element code LS-DYNA to model the Unconfined Compression Test (UCT) numerical simulation. Models with five different mesh types were conducted for convergence mesh, namely normal mesh, fine mesh, super fine mesh, coarse mesh, and super coarse mesh. The mesh convergence of rock media has been conducted using DEM and steel plates simulated using the Finite Element Method (FEM). The DEM-FEM numerical analysis is compared with the results obtained from the experimental test. The best mesh was obtained as the simulation could reproduce the stress-strain curve trends, the failure behaviour and compression strength observed in the experimental test. The normal mesh was selected as the best mesh type in this study based on the comparisons that have been made. This study shows that the DEM-FEM numerical simulation can represent granite rock and can be used for further study based on mesh convergence

Impact of additional genetic abnormalities at diagnosis of chronic myeloid leukemia for first-line imatinib-treated patients receiving proactive treatment intervention

Early view: March 23, 2023The BCR::ABL1 gene fusion initiates chronic myeloid leukemia (CML), however evidence has accumulated from studies of highly selected cohorts that variants in other cancer-related genes are associated with treatment failure. Nevertheless, the true incidence and impact of additional genetic abnormalities (AGAs) at diagnosis of chronic phase (CP)-CML is unknown. We sought to determine whether AGAs at diagnosis in a consecutive imatinib-treated cohort of 210 patients enrolled in the TIDEL-II trial influenced outcome despite a highly proactive treatment intervention strategy. Survival outcomes including overall survival, progression-free survival, failure-free survival and BCR::ABL1 kinase domain mutation acquisition were evaluated. Molecular outcomes were measured at a central laboratory and included major molecular response (MMR, BCR::ABL1 ≤0.1%IS), MR4 (BCR::ABL1 ≤0.01%IS) and MR4.5 (BCR::ABL1 ≤0.0032%IS). AGAs included variants in known cancer genes and novel rearrangements involving the formation of the Philadelphia chromosome. Clinical outcomes and molecular response were assessed based on the genetic profile and other baseline factors. AGAs were identified in 31% of patients. Potentially pathogenic variants in cancer-related genes were detected in 16% of patients at diagnosis (including gene fusions and deletions) and structural rearrangements involving the Philadelphia chromosome (Ph-associated rearrangements), detected in 18%. Multivariable analysis demonstrated that the combined genetic abnormalities plus the ELTS clinical risk score were independent predictors of lower molecular response rates and higher treatment failure. Despite a highly proactive treatment intervention strategy, first-line imatinib-treated patients with AGAs had poorer response rates. This data provides evidence for the incorporation of genomically-based risk assessment for CML.Naranie Shanmuganathan, Carol Wadham, NurHezrin Shahrin, Jinghua Feng, Daniel Thomson, Paul Wang, Verity Saunders, Chung Hoow Kok, Rob M. King, Rosalie R. Kenyon, Ming Lin, Ilaria S. Pagani, David M. Ross, Agnes S.M. Yong, Andrew P. Grigg, Anthony K. Mills, Anthony P. Schwarer, Jodi Braley, Haley Altamura, David T. Yeung, Hamish S. Scott, Andreas W. Schreiber, Timothy P. Hughes and Susan Branfor

The genomic landscape of balanced cytogenetic abnormalities associated with human congenital anomalies

Despite the clinical significance of balanced chromosomal abnormalities (BCAs), their characterization has largely been restricted to cytogenetic resolution. We explored the landscape of BCAs at nucleotide resolution in 273 subjects with a spectrum of congenital anomalies. Whole-genome sequencing revised 93% of karyotypes and demonstrated complexity that was cryptic to karyotyping in 21% of BCAs, highlighting the limitations of conventional cytogenetic approaches. At least 33.9% of BCAs resulted in gene disruption that likely contributed to the developmental phenotype, 5.2% were associated with pathogenic genomic imbalances, and 7.3% disrupted topologically associated domains (TADs) encompassing known syndromic loci. Remarkably, BCA breakpoints in eight subjects altered a single TAD encompassing MEF2C, a known driver of 5q14.3 microdeletion syndrome, resulting in decreased MEF2C expression. We propose that sequence-level resolution dramatically improves prediction of clinical outcomes for balanced rearrangements and provides insight into new pathogenic mechanisms, such as altered regulation due to changes in chromosome topology