Innovative Work Environment, Internal Locus of Control and Intrinsic Job Satisfaction: Evidence from Bangladeshi Employees

Pecuniary reward and perquisites can satisfy employees extrinsically; however, employees become intrinsically satisfied if they are offered challenge and autonomy in their jobs.  Thus, jobs can be tailored to increase workers’ intrinsic job satisfaction. Moreover, if employees of an organization are given an innovative work environment, then it can satisfy them intrinsically as well. A workplace is innovative if it allows employees to take new initiatives, to change the existing systems, and to do jobs in a new way that is more efficient than the existing one. However, these phenomena are related to employees with a high internal locus of control, a personality trait desirable to employers in many jobs.  Given these theoretical backdrops, this paper studies the influence of innovative work environments on intrinsic job satisfaction of employees in Bangladeshi organizations. Data were collected from 304 employees working in Bangladeshi organizations to investigate these. The contribution of this paper is that the finding of this study can give deep insight and thus help them framing organizational policy and recruitment policy. Keywords: Intrinsic Satisfaction, Innovative Environment, Internal Locus of Control, Personality Trait JEL Classification: D23 DOI: 10.7176/EJBM/12-29-05 Publication date:October 31st 202

Teaching-Learning Practices of Information and Communication Technology in Secondary Schools of Bangladesh

In Bangladesh, secondary school curricula have made Information and Communication Technology (ICT) education compulsory considering the importance of technology and innovation. Students’ performance varies highly across schools compared to within school. This study is conducted in an effort to know what teachers accomplish in ICT classes. The study follows a qualitative research design. 5 ICT teachers and 250 students from 5 secondary schools of Dhaka city were chosen as sample. Data were collected from students and teachers through semi-structured questionnaire, interviews and classroom observations. The major findings of this study reveal that teachers practice mostly lecture, demonstration and book reading method in ICT classes to engage the students in teaching-learning process. Moreover, students are given feedback based on individual assessment. Furthermore, most of the schools have sufficient infrastructure to conduct laboratory work and sometimes practical classes are taken in ICT labs. It is asserted that ICT teachers are punctual to prepare lesson plans and use text books as well as e-learning resources for preparation. However, further study is suggested to explore the overall scenario of ICT teaching learning practices in secondary level education of Bangladesh by comparing rural and urban secondary schools in large scale. Keywords: teaching-learning, ICT, secondary schools DOI: 10.7176/IKM/9-8-04 Publication date:September 30th 201

Estimating reflectance, illumination, and shape from a single view

This work investigates a core problem in computer vision: obtaining, from a single view, the geometric and photometric information of a scene - the reflectance properties of objects, their shapes, and the illumination direction. We focus on two important aspects of this problem: (a) adopting a general formulation which encompasses a number of physical phenomena and addresses a wide range of non-Lambertian surfaces, and (b) keeping the number of required input images and prior information as small as possible. There are three main contributions in this work. The first of these is the simultaneous recovery, from a single spectral image, of the surface reflectance properties and shape of objects in a scene. Although the general trend in the literature has been to employ trichromatic imagery and develop algorithms based on a specific reflectance model, we make use of the rich information content of spectral imagery and formulate the problem more generally. The spectral approach allows us to estimate the wavelength-dependent physical properties of objects, and the general formulation allows us to address a wide range of surfaces. In this way, we begin with a general, physical interpretation of the reflection process and cast the recovery of reflectance parameters and shape in terms of a structural optimisation. We produce results on synthetic images, and illustrate how the recovered photometric parameters can be applied to real world imagery for skin recognition. The second contribution addresses the problem, again from a single spectral image, of estimating the direction of illumination in a scene without having any prior knowledge of the reflectance properties or object shapes. Although specular highlights provide strong cues for determining illumination direction, most existing approaches require calibration targets, which limits their applicability. We overcome this limitation and determine the direction of the light source by placing two novel constraints on the specular highlights: coplanarity and Kullback-Leibler divergence. To do this, we start with a general formulation that models the scene radiance as a linear combination of specular and diffuse reflections. This permits the reflection parameters to be recovered through an iterative optimisation, which we render well-posed by adopting a novel reparameterisation. Once the reflectance parameters are in hand, we recover the direction of the single point-light source from the specular reflection and the 3D shape from the diffuse reflection. The third contribution of this thesis is to create a variant of colour photometric stereo which addresses two difficulties encountered in previous approaches: non-Lambertian reflectance and spatially varying albedo. We show that, under complementary coloured illumination, the observed colour of an object varies according to different reflections, which provides clues for estimating shape. To deal with multicoloured surfaces, we propose a colour-correction method which exploits the addition principle of complementary colours, allowing an object's true colour to be estimated. In addition, we present a segmentation method that utilises the colour difference between input images to detect diffuse reflections, specularities, and attached shadows. Finally, we employ an iterative optimisation based on the Torrance-Sparrow reflectance model to address non-Lambertian reflectance

Estimating Reflectance Parameters, Light Direction, and Shape From a Single Multispectral Image

This paper presents a novel approach for estimating the light direction, shape, and reflectance parameters from a single multispectral image. We start from a general formulation that hinges in the notion that the light reflected from an object can be deemed to be a linear combination of specular and diffuse reflections. This permits the recovery of the reflection parameters through an iterative optimization scheme, which we render well posed by adopting a novel reparameterization that reduces the number of degrees of freedom in the cost function. With the estimated specular reflectance parameters, we recover the single point light source position from specular highlights by applying two novel constraints, coplanarity and Kullback-Leibler divergence. Then, by integrating the knowledge of light source and diffuse reflectance parameters, we recover shape of the scene from the diffuse component. Our approach is quite general in nature and can be applied to a family of reflectance models that are based on the Fresnel reflection theory. We demonstrate the utility of our method on synthetic and real world imagery. We also compare our results to several alternatives in the literature

An optimisation approach to the recovery of reflection parameters from a single hyperspectral image

In this paper, we present a method to recover the parameters governing the reflection of light from a surface making use of a single hyperspectral image. To do this, we view the image radiance as a combination of specular and diffuse reflection component

On the Recovery of Shape and Reflectance from a Single Multispectral Image

This paper presents a method for recovering the reflectance and shape of a surface from a single hyper spectral image. To do this, we depart from a reflectance model based on a physical interpretation of the reflection process where the geometry of the scene and the properties of the object surface describe the image formation process. With the model in hand, we propose a solution to the recovery of the reflection parameters via an optimisation approach that aims at recovering both the surface normals and the reflectance. This, in turn, allows for the application of the method by Frankot and Chellappa [8] so as to recover the surface depth at each pixel. We demonstrate the utility of our method for the recovery of both reflectance and surface depth on synthetic and real world images

A method for estimating light direction, shape, and reflection parameters from a single image

This paper presents a novel approach for estimating light direction, shape, and reflectance parameters from a single image based on iterative optimisation. We depart from a generalist view of the reflection process based upon a physical interpretation and cast the recovery of the reflection parameters in an optimisation setting. With the estimated specular reflectance parameters, we recover the light source direction from specular highlights while applying two novel constraints, coplanarity and Kullback-Leibler divergence. Then, by integrating the knowledge of light source direction and diffuse reflectance parameters, we recover shape of the scene from diffuse component. Our approach is quite general in nature and can be applied to a family of reflectance models that are based on the Fresnel reflection theory. We demonstrate the utility of our method on synthetic and real world imagery

No-Reference Quality Assessment of Transmitted Stereoscopic Videos Based on Human Visual System

Provisioning the stereoscopic 3D (S3D) video transmission services of admissible quality in a wireless environment is an immense challenge for video service providers. Unlike for 2D videos, a widely accepted No-reference objective model for assessing transmitted 3D videos that explores the Human Visual System (HVS) appropriately has not been developed yet. Distortions perceived in 2D and 3D videos are significantly different due to the sophisticated manner in which the HVS handles the dissimilarities between the two different views. In real-time video transmission, viewers only have the distorted or receiver end content of the original video acquired through the communication medium. In this paper, we propose a No-reference quality assessment method that can estimate the quality of a stereoscopic 3D video based on HVS. By evaluating perceptual aspects and correlations of visual binocular impacts in a stereoscopic movie, the approach creates a way for the objective quality measure to assess impairments similarly to a human observer who would experience the similar material. Firstly, the disparity is measured and quantified by the region-based similarity matching algorithm, and then, the magnitude of the edge difference is calculated to delimit the visually perceptible areas of an image. Finally, an objective metric is approximated by extracting these significant perceptual image features. Experimental analysis with standard S3D video datasets demonstrates the lower computational complexity for the video decoder and comparison with the state-of-the-art algorithms shows the efficiency of the proposed approach for 3D video transmission at different quantization (QP 26 and QP 32) and loss rate (1% and 3% packet loss) parameters along with the perceptual distortion features