Engaging Mind Chemistry with Gamification: HR Practitioners Views

Purpose: The purpose of this study is to examineworkplace gamification in the HR process. Moreover, toexplore the impact of workplace gamification onemployee engagement and experience.Design/ Methodology /Approach: The current study isqualitative. The views of HR practitioners from Deloitte,TCS, Wipro, and Continental are taken through atelephonic and personal interview to understandworkplace gamification in the HR process. And its impacton employee engagement and employee experience.Findings: Workplace demographics are with changingdue to the entry of tech-savvy and hyperactivemillennials. Millennials get into an organization withmuch higher expectations in terms of work, workenvironment, and HR practices. Gamification is engrossedas one of the tools for employee engagement andemployee experience. Gamification is a psychologicalimperative. Playing games keeps the brain fit, reducesstress, helps deal with cognitive overload, and alsoteaches work skills and team spirit.Practical implications: The gamification made the workof HR practitioners easy. Creating user experience,involving them through practice and engagement was achallenge for HR practitioners. Now with the help ofworkplace gamification, feedback and rewards are more transparent; it strengthens interpersonal relationships,betters employee experience, and establishes friendlycompetitions.Originality/Value: The paper provides insights ongamification from HR practitioners' views. And theapplication of gamification in various HR-relatedprocesses such as recruitment, training, learning anddevelopment, performance management, andengagement. Hence, HR practitioners and policymakerscan take a call on implementing workplace gamificationin various HR processes, and that results in HR-relatedoutcomes.&nbsp

Expression of MHC class I polypeptide-related sequence A (MICA) in colorectal cancer

Background: The major histocompatibility complex class I polypeptide-related sequence A (MICA) is one of the ligands of the natural killer group 2D (NKG2D) activating receptor. MICA stimulates NKG2D, which further triggers activation of natural killer cells and leads to killing of infected target cells. To subvert the biological function of NKG2D, tumor cells utilize an escape strategy by shedding overexpressed MICA. In this study, we determined the levels of MICA in colorectal cancers (CRCs). Additionally, we established correlations between MICA expression and clinical characteristics. Publicly available data and bioinformatics tools were used for validation purposes. Methods: We determined the MICA RNA expression levels and assessed their correlation with clinicopathological parameters in CRC using the UALCAN web-portal. We performed immunohistochemical analysis on tissue microarrays having 192 samples, acquired from 96 CRC patients, to validate the expression of MICA in CRC and adjacent uninvolved tissue and investigated its prognostic significance by Kaplan-Meier and proportional hazards methods. Results: Bioinformatics and immunohistochemical analyses showed that MICA expression was significantly upregulated in CRCs as compared to uninvolved tissue, and the overexpression of MICA was independent of pathologic stage, histotype, nodal metastasis status, p53-status, as well as patient\u27s race, age and gender. Moreover, PROGgeneV2 survival analysis of two cohorts showed a poor prognosis for CRC patients exhibiting high MICA expression. Conclusions: Overall, our findings for CRC patients demonstrate generally high expression of MICA, and suggest that a poor prognosis relates to high MICA expression. These results can be further explored due to their potential to provide clues to the contribution of the tumor microenvironment to the progression of CRC

Expression of trefoil factor 3 is decreased in colorectal cancer

In colorectal cancer (CRC), high expression of trefoil factor 3 (TFF3) is associated with tumor progression and reduced patient survival; however, bioinformatics analyses of public \u27omics\u27 databases show low TFF3 expression in CRCs as compared to normal tissues. Thus, we examined TFF3 expression in CRCs and matching normal tissues to evaluate its role in CRC progression. TFF3 gene expression was char- acterized using the bioinformatics portal UALCAN (http:// ualcan.path.uab.edu). Tissue microarrays (TMAs) of archival CRC specimens (n=96) were immunostained with anti-human TFF3 antibodies. Immunohistochemical (IHC) staining intensity was semi-quantitatively scored. For this cohort, the median follow-up was 5.4 years. Associations between clinical and pathological variables were determined using Chi-square or Fisher\u27s exact tests. Univariate disease-free survival was estimated by the Kaplan-Meier method. Omics data analyses by UALCAN showed downregulation of TFF3 expression in CRC relative to normal tissue at protein (χ2, P\u3c0.0001) levels. There was a similar decreasing trend of TFF3 expression in the pathologic stages of the CRCs (RNA, χ2, P=0.88 and protein, χ2 P\u3c0.0001). UALCAN data analysis showed that TFF3 exhibited 27% lower mRNA expression in tumors with mutant TP53 (P=0.007). Confirming the findings of omics analyses, IHC analysis of TMAs exhibited lower TFF3 expression in 95.6% (65 of 68) of the available normal-tumor matching pairs (χ2, P\u3c0.0001). There was no statistically significant association of tumor TFF3 expression with patient sex, race/ ethnicity, tumor location within the colorectum, Tumor, Node, Metastasis (TNM) stage, lymph node metastasis, or surgical margins. However, low TFF3 IHC staining in tumor tissue was associated with histological grade (P=0.026). Kaplan-Meier survival analysis showed no prognostic value of low TFF3 expression relative to those with high expression (log-rank, P=0.605). Our findings demonstrate low expression of TFF3 in CRCs. Association between low TFF3 and histopathological features suggests involvement of this molecule in progression of CRC

A Study on Stock Co-Movement’s Analysis of Select Bank and IT Company Stocks

The risk of a portfolio depends on the co- movement between the security returns forming the portfolio. The coefficient of correlation is an important measure for studying co movement between securities. Banking and IT company’s shares represent sizable share of market portfolio of common investors. In this perspective the present study has been undertaken to help small retail investors who commonly invest in these two major sectors to understand the co movement of returns among Banking and IT industry stocks. This study covers correlation co movement calculation between selected four Banking shares and four IT companies’ shares for a period from 16th June 2014 to 15th June 2015. The correlation between banking shares are more positive compared to correlation between IT company shares. This implies that the banking stocks return more or less move in the same direction. The correlation between Banking and IT Company stocks are either zero or negative which implies that these two sectors shares are not related or move in the opposite direction in terms of return. This implies that banking and IT industry shares are good combinations for portfolio construction which substantially reduces the risk of that particular portfolio

A Novel Data Generation Approach for Digital Forensic Application in Data Mining

With the rapid advancements in information and communication technology in the world, crimes committed are also becoming technically intensive. When crimes committed use digital devices, forensic examiners have to adopt practical frameworks and methods for recovering data for analysis as evidence. Data Generation, Data Warehousing and Data Mining, are the three essential features involved in this process. This paper proposes a unique way of generating, storing and analyzing data, retrieved from digital devices which pose as evidence in forensic analysis. A statistical approach is used in validating the reliability of the pre-processed data. This work proposes a practical framework for digital forensics on flash drives

Prevalence of goitre and its associated factors in a coastal district of Karnataka

Context: Iodine deficiency Disorders (IDDs) are a major public health problem globally. In India more than 200 million are at risk for this disorder. It affects people of all ages and both sexes. The mental impairment caused by IDD especially in children is an important consequence of IDD. Aim: To find the prevalence of IDDs and the associated factors with it. Settings and Design: A school based cross – sectional study. Methods and Material: The study was done in Udupi district of Karnataka using a pretested, semistructured questionnaire. The villages of the three talukas (Udupi, Kundapur and Karkala) of Udupi district were sampled according to Probability Proportionate to Size (PPS).One school was chosen for the study from each of the 30 selected villages. Minimum of 90 students were selected from each school. Salt and urine samples were collected for Iodine estimation from a sub sample. Goitre was graded according to WHO/UNICEF/ICCIDD criteria. Results: A total of 3023 children were examined (M = 49.1%, F = 50.9%). The prevalence of goitre in Udupi district was 19.8%. The prevalence of goitre was found to be more amongst females compared to males (p = 0.021) and also was found to be increasing with the increasing age (p = 0.003). Of the 539 salt samples analyzed 23.7 % were inadequately iodized. Education of the father, fish consumption and occupation of the mother were found to be significant predictors of goitre. Conclusions: Goitre is a public health problem in Udupi district of Karnataka. The adequately Iodized salt coverage which should have been more than 90 % is not fulfilled. More awareness is required amongst the people about IDDs and its predictors

ReP-ETD: A Repetitive Preprocessing technique for Embedded Text Detection from images in spam emails

Email service proves to be a convenient and powerful communication tool. As internet continues to grow, the type of information available to user has shifted from text only to multimedia enriched. Embedded text in multimedia content is one of the prevalent means for delivering messages to content viewers. With the increasing importance of emails and the incursions of internet marketers, spam has become a major problem and has given rise to unwanted mails. Spammers are continuously adopting new techniques to evade detection. Image spam is one such technique where in embedded text within images carries the main information of the spam message instead of text based spam. Currently, image spam is evaluated to be roughly 50% of all spam traffic and is still on the rise, thus a serious research issue. Filtering mails is one of the popular approaches used to block spam mails. This work proposes new model ReP-ETD (Repetitive Pre-processing technique for Embedded Text Detection) for efficiently and accurately detecting spam in email images. The performance of the proposed ReP-ETD model has been evaluated across the identified parameters and compared with other existing models. The simulation results demonstrate the effectiveness of the proposed model

Steganalysis of YASS using Huffman Length statistics

This work proposes two main contributions to statistical steganalysis of Yet Another Steganographic Scheme (YASS) in JPEG images. Firstly, this work presents a reliable blind steganalysis technique to predict YASS which is one of recent and least statistically detectable embedding scheme using only five features, four Huffman length statistics (H) and the ratio of file size to resolution (FR Index). Secondly these features are shown to be unique, accurate and monotonic over a wide range of settings for YASS and several supervised classifiers with the accuracy of prediction superior to most blind steganalyzers in vogue. Overall, the proposed model having Huffman Length Statistics as its linchpin predicts YASS with an average accuracy of over 94 percent

A data mining approach for data generation and analysis for digital forensic application

With the rapid advancements in information and communication technology in the world, crimes committed are becoming technically intensive. When crimes committed use digital devices, forensic examiners have to adopt practical frameworks and methods to recover data for analysis which can pose as evidence. Data Generation, Data Warehousing and Data Mining, are the three essential features involved in the investigation process. This paper proposes a unique way of generating, storing and analyzing data, retrieved from digital devices which pose as evidence in forensic analysis. A statistical approach is used in validating the reliability of the pre-processed data. This work proposes a practical framework for digital forensics on flash drives

Member, IAENG, Prasanth G Rao, Abhilash VR, P. Deepa Shenoy, Venugopal KR and LM Patnaik. A Data Mining Approach for Data Generation and Analysis for Digital Forensic Application

With the rapid advancements in information and communication technology in the world, crimes committed are becoming technically intensive. When crimes committed use digital devices, forensic examiners have to adopt practical frameworks and methods to recover data for analysis which can pose as evidence. Data Generation, Data Warehousing and Data Mining, are the three essential features involved in the investigation process. This paper proposes a unique way of generating, storing and analyzing data, retrieved from digital devices which pose as evidence in forensic analysis. A statistical approach is used in validating the reliability of the pre-processed data. This work proposes a practical framework for digital forensics on flash drive