Handwritten Digit Recognition Using Machine Learning Algorithms

Handwritten character recognition is one of the practically important issues in pattern recognition applications. The applications of digit recognition includes in postal mail sorting, bank check processing, form data entry, etc. The heart of the problem lies within the ability to develop an efficient algorithm that can recognize hand written digits and which is submitted by users by the way of a scanner, tablet, and other digital devices. This paper presents an approach to off-line handwritten digit recognition based on different machine learning technique. The main objective of this paper is to ensure effective and reliable approaches for recognition of handwritten digits. Several machines learning algorithm namely, Multilayer Perceptron, Support Vector Machine, NaFDA5; Bayes, Bayes Net, Random Forest, J48 and Random Tree has been used for the recognition of digits using WEKA. The result of this paper shows that highest 90.37% accuracy has been obtained for Multilayer Perceptron

Spontaneous breaking of time reversal symmetry in strongly interacting two dimensional electron layers in silicon and germanium

We report experimental evidence of a remarkable spontaneous time reversal symmetry breaking in two dimensional electron systems formed by atomically confined doping of phosphorus (P) atoms inside bulk crystalline silicon (Si) and germanium (Ge). Weak localization corrections to the conductivity and the universal conductance fluctuations were both found to decrease rapidly with decreasing doping in the Si:P and Ge:P $\delta-$layers, suggesting an effect driven by Coulomb interactions. In-plane magnetotransport measurements indicate the presence of intrinsic local spin fluctuations at low doping, providing a microscopic mechanism for spontaneous lifting of the time reversal symmetry. Our experiments suggest the emergence of a new many-body quantum state when two dimensional electrons are confined to narrow half-filled impurity bands

Prevalence and severity of depression among undergraduate students in Karachi, Pakistan: a cross sectional study

Purpose: To highlight the prevalence and severity of depression among undergraduate students in public and private universities in Karachi, Pakistan.Methods: In this cross-sectional study a total of 408 undergraduate students from both public and private universities in Karachi, Pakistan completed Zung Self-Rating Depression Scale (SDS) questionnaire to appraise the presence and extent of depression among the participants. Their sociodemographic characteristics such as age, gender and course of study as well as drug use data were also collected and analyzed.Results: Depression prevalence was 53.43 % (38.07 % for males and 61.00 % for females). A significant disparity in the prevalence of depression across ethnicity was observed. Less than 50 % (n = 163) of the students were satisfied with their duration of degree course work while 111 (27.20 %) participants were not sure about this. The intensity of depression increased with declining satisfaction level (Gamma = 0.264, p = 0.001) which affected the performance and results of students during their studies. A majority of the participants (89 %, n = 358) of our study have never used medicines to alter their mood.Conclusion: The findings of this study highlight the importance of understanding the unique strains and mental health effect of university education on undergraduate students, especially female students.Keywords: Depression, Undergraduate students, Mood alteration, Zung self-rating depression scale (SDS), Mental health, Risk assessmen

Industrial Digitization, the Use of Real-Time Information, and Operational Agility: Digital and Information Perspectives for Supply Chain Resilience

Change is the permanent reality of the digital business world. Firms manage it by their ability and capability to cope with short-term and long-term deviations and disruptions. This paper presents an examination of the supply chain resilience (SCR) of firms operating in the Malaysian Service Sector. The data for this study were collected from 157 managers of 59 firms operating in seven sub-service sectors. Following Organizational Information Processing Theory (OIPT) and reviewing the relevant literature for the conceptualization, we tested a framework that suggests that the use of real-time information (URTI) enhances the SCR. We also found that the industrial digital environment has an important link with the URTI. The results indicate that the URTI is significantly associated with SCR and operational agility, which partially mediates the relationship between the URTI and SCR. We further discuss the theoretical contributions and implications with practical, and policy implications arising from this research

DESIGN, PERFORMANCE ANALYSIS AND EFFICIENCY OPTIMIZATION OF COPPER INDIUM GALLIUM SELENIDE (CIGS) SOLAR CELL

A comparative investigation of the cell performance of Copper Indium Gallium Selenide (CIGS) thin-film solar cell, fabricated using ZnO:Al/i-ZnO/CdS/CIGS layers, has been reported. ADEPT 2.0, a 1D simulation software, were used throughout the whole research for the simulation of light J-V characteristics for different designs. Energy conversion efficiency for each design was calculated from its corresponding light J-V characteristics curve. The efficiency variation were investigated under 1 sun, AM1.5G illumination and optimized layer parameters (thickness) for each layer of the device. The device has designed with an ntype ZnO window layer, an n-type CdS as buffer layer and a p-type CIGS as absorber layer. Molybdenum (Mo) substrate is used for the structure. A totalarea efficiency of 19·75% for ZnO:Al/i-ZnO/CdS/CIGS based thin-film solar cells had been found. Performance is improved due to higher fill factor. The device parameters are optimized separately for each layer. Based on these optimizations, the ultra-thin film solar cell design is proposed after careful consideration of lattice mismatch between two adjacent layers of the device

Combustion and Emission Analysis of Mahua and Jujube Biodiesel Blends as Fuel in a CI Engine

This present study on biodiesel blends shows the performance, emission and combustion characteristics of the DI diesel engine, which is been run independently on direct diesel fuel, 20% blending of zizipus jujbe methyl ester (ZJME20), and 20% blending of mahua methyl ester (MME20) with diesel. In this study, the tested fuels were obtained by catalytic transesterification process. Based on the experimental results, MME20 is favorable for less HC, CO, and smoke density than diesel and ZJME20. Based on the brake thermal efficiency and specific fuel consumption, MME20 is better when compared with ZJME20. The result also showed momentous improvement in the heat releasing rate due to the better performance characteristic of MME20

The Impact of Brick Kiln Operation to the Degradation of Topsoil Quality of Agricultural Land

Brick kiln is a big environmental issue for the agriculture of Bangladesh as it was observed that the agricultural production in the soil close to the brick kiln was lesser than the same soil far from brick kiln. The study was conducted to assess the impact of brick kiln operation to the degradation of topsoil quality at Singair of Kalihati upazila in Tangail, Bangladesh, during the period of July to December 2013. The Soil was collected from areas close to the brick fields and far from the brick fields at a depth of 0-15 cm. The Electrical Conductance (EC) was found almost double in the soil samples close to the brick field than the soil samples far from brick field. The organic mattter content in the soil sample close to the brickfield was significantly lower than that of the far soil sample. The mean values of total N, available P and S were also significantly lower in the soil samples close to the brick kiln, 0.05%, 12.4, and 8.36 ppm respectively in the close soils, while 0.06%, 24.6, and 11.7 ppm respectively in the far soil. There were no significant changes observed in the other elements