Information system adoption and usage: validating UTAUT model for Bangladeshi SMES

Small and medium enterprises (SME) are an integral part of any country’s economy. Therefore, their existence, operational efficiency and effectiveness must be ensured. Implementation of information system (IS) in business value chain allows organizations to enhance this efficiency thus enables organizations to grow and sustain. This research explores 255 Bangladeshi SMEs to conceptualize current trend of IS usage and validates four constructs of unified theory of acceptance and use of technology (UTAUT) model to explain IS adoption behavior. The outcome of the study shows that, though a number of Bangladeshi SME’s are exposed to computer based IS, their usage, in most cases, are limited to operational level of activities. SMEs are also less concerned about the further development of IS and allocated a minimum budget for IS development. It is also found that the adoption and usage of IS by the Bangladeshi SMEs are strongly influenced by performance efficiency, effort efficiency and facilitating condition and moderately influenced by social influence

Non-equilibrium scalar field dynamics starting from Fock states: Absence of thermalization in one dimensional phonons coupled to fermions

We propose a new method to study non-equilibrium dynamics of scalar fields starting from non-Gaussian initial conditions using Keldysh field theory. We use it to study dynamics of phonons coupled to non-interacting bosonic and fermionic baths, starting from initial Fock states. We find that in one dimension long wavelength phonons coupled to fermionic baths do not thermalize both at low and high bath-temperatures. At low temperature, constraints from energy-momentum conservation lead to a narrow bandwidth of particle-hole excitations and the phonons effectively do not see this bath. On the other hand, the strong band-edge divergence of the particle-hole density of states leads to an undamped polariton-like mode of the dressed phonons above the band edge of the particle-hole excitations. These undamped modes contribute to the lack of thermalization of long wavelength phonons at high temperatures. In higher dimensions, these constraints and the divergence of density of states are weakened and lead to thermalization at all wavelengths.Comment: 14+10 pages, 5+5 figures. Version accepted in PR

Deep learning for 3D ear detection: A complete pipeline from data generation to segmentation

The human ear has distinguishing features that can be used for identification. Automated ear detection from 3D profile face images plays a vital role in ear-based human recognition. This work proposes a complete pipeline including synthetic data generation and ground-truth data labeling for ear detection in 3D point clouds. The ear detection problem is formulated as a semantic part segmentation problem that detects the ear directly in 3D point clouds of profile face data. We introduce EarNet, a modified version of the PointNet++ architecture, and apply rotation augmentation to handle different pose variations in the real data. We demonstrate that PointNet and PointNet++ cannot manage the rotation of a given object without such augmentation. The synthetic 3D profile face data is generated using statistical shape models. In addition, an automatic tool has been developed and is made publicly available to create ground-truth labels of any 3D public data set that includes co-registered 2D images. The experimental results on the real data demonstrate higher localization as compared to existing state-of-the-art approaches

Biometric security: A novel ear recognition approach using a 3D morphable ear model

Biometrics is a critical component of cybersecurity that identifies persons by verifying their behavioral and physical traits. In biometric-based authentication, each individual can be correctly recognized based on their intrinsic behavioral or physical features, such as face, fingerprint, iris, and ears. This work proposes a novel approach for human identification using 3D ear images. Usually, in conventional methods, the probe image is registered with each gallery image using computational heavy registration algorithms, making it practically infeasible due to the time-consuming recognition process. Therefore, this work proposes a recognition pipeline that reduces the one-to-one registration between probe and gallery. First, a deep learning-based algorithm is used for ear detection in 3D side face images. Second, a statistical ear model known as a 3D morphable ear model (3DMEM), was constructed to use as a feature extractor from the detected ear images. Finally, a novel recognition algorithm named you morph once (YMO) is proposed for human recognition that reduces the computational time by eliminating one-to-one registration between probe and gallery, which only calculates the distance between the parameters stored in the gallery and the probe. The experimental results show the significance of the proposed method for a real-time application

Does Employee Involvement Really Increase Employee Productivity? – An Employee Perception Based Study

The purpose of this paper is to analyze the relationship between employee involvement and productivity evidence from banking industry. Self-administrated survey method was used to conduct the study. Data were collected from 100 bank employees through a well-structured questionnaire. The results were analyzed through frequency analysis, mean and standard deviation, t-test and canonical correlation by using SPSS 23 package software. For demographic information of gender of the respondents sample t-test was used and found that there is no significant difference of response between male and female also difference of response between public banks and private banks towards employee involvement and employee productivity. Canonical Correlation shows the relationship between employee involvement and employee productivity. The research helps to understand the relationship between employee involvement and employee productivity in baking industry of Bangladesh. It will also make worthy contribution to the literature and enhance the knowledge in this subject area as it provides authentic results that can be used in further research

Species diversity, seasonal abundance and morphometric analysis of grasshopper (Orthoptera: Caelifera) in Rajshahi City, Bangladesh

A study from July 2016 to June 2017 was carried out to assess the species diversity, seasonal abundance and morphometric characteristics of grasshopper (Orthoptera: Caelifera) at Rajshahi city of Rajshahi District, Bangladesh. A total number of 286 individuals of grasshopper were examined during the study. Eight species of grasshopper were identified under seven genera of 2 families. The numbers of identified species were seven and one, and their percentages were calculated as 90.9% and 9.1% in families Acrididae and Tetrigidae respectively. Based on monthly occurrence, four species of grasshopper were found throughout 12 months, three were 9-11 months and one was 6-8 months. The highest species abundance of grasshoppers was recorded in the month of July to August and lowest in November to January. Among the collected species the status of Camnula pellucida was very common (VC) and rest seven species were considered as not rare (NR). The Simpson’s diversity index (1-D) for grasshopper species was 0.80. For the study of inter-specific variations, morphometric analysis of nine parameters viz. length of body, antenna, foreleg, midleg, hindleg, forewing and hindwing; width of forewing and hindwing was evaluated. The lengths or widths of these parameters were measured by ImageJ software (1.48v) and data were analyzed by GraphPad InStat 3 and MS Excel 2007. Relationship among parameters and different species were determined using repeated measures ANOVA with Tukey post-test. The variation between these species and parameters was considered highly significant (p< 0.001) and showed the dynamic speciation. Morphometric analysis of these eight species was done for the first time from this region

Effect of w/c ratio and cement content on diffusivity of chloride ion in concrete: A molecular dynamics study

When a reinforced structure is exposed to marine environments, chloride-induced corrosion occurs and it decreases the durability and performance of the structure. The degree of humidity, the presence of cracks, environmental conditions, w/c ratio, and cement content are the influencing factors for chloride ion ingress into concrete. All of them, w/c ratio and cement content are treated as the most crucial factors on diffusion. This paper focus on Molecular Dynamics (MD) simulation method to determine the diffusion coefficient of chloride ion in concrete. The effect of w/c ratio and cement content on the diffusivity of chloride ion is also evaluated. The diffusion coefficients are obtained 2.88x10-12 m2/s, 3.13x10-12 m2/s, and 3.61x10-12 m2/s respectively for different w/c ratio of 0.40, 0.45 and 0.50 with constant cement content. Again the diffusion coefficient are calculated 4.6x10-12 m2/s, 3.13x10-12 m2/s, 2.78x10-12 m2/s respectively for different cement content of 300 kg/m3, 350 kg/m3 and 400 kg/m3 with constant w/c ratio. The simulation results clearly indicate that the diffusion coefficient of chlorine was affected by w/c ratio and cement content significantly