DJ Academy of Design

Sangam Literature stands as the canonical wellspring of the Tamil language, underpinned by a dense and rigorously maintained tradition of scholarly inquiry. This paper offers a comprehensive historical description and analysis of formalistic studies—the examination of meter, structure, and poetic architecture—as applied to the Sangam corpus. This research field has evolved dynamically, influenced sequentially by the establishment of native grammatical norms, the development of exhaustive commentary traditions, the advent of print publication, the filtering influence of Western critical pedagogy, and finally, the application of modern linguistic and literary theories. Studies focusing on the formal structure of Sangam texts have been systematically compiled by the authors across four distinct archival levels: contributions published in academic journals, proceedings from scholarly conferences, doctoral dissertations, and the critical engagements offered by non-Tamil scholars. Beginning with the pioneering efforts of the 19th century, this analysis traces the historical trajectory of the field, examining sociological perspectives (e.g., K. Sivathamby and A. Shanmugadas) that investigated how socio-political development informed and affected the expansion of poetic forms—such as the notable extension of the Akaval meter within the longer narratives of Pattupattu. Furthermore, the paper delves into core theoretical debates that define the field: C. V. Shanmugam’s crucial contributions identifying the link between prosody (Yāppiyal) and linguistic sentence structure; A. Pitchai’s seminal hypothesis positing the Akaval meter as the fundamental, archaic Tamil poetic form; and M. Kasthuri’s influential discussions concerning the inclusion of Nālacai-cīr (four-unit feet) found within the Vañci lines of the Poruṇarāṟṟuppaṭai. Finally, the study recognizes the essential contributions of non-Tamil scholars, including the work of John Marr (likely a reference to George L. Hart in the context of oral performance theory) who connected the formal elegance of the Akaval meter to the vibrant culture of oral performance, and Kamil Zvelebil, whose subtle and profound observations focused on the phonaesthetics (sound-aesthetics) of the ancient verse. Ultimately, this paper argues for future approaches to Sangam poetics that rely on a multivalent methodology, integrating expertise in musicology, linguistic science, and comparative literature to unlock the enduring complexity of these classical texts.

The total number of TB cases in Indonesia is 969,000. This figure represents a 17% increase compared to 2020. SITB 2022 data shows there are 15,375 cases of co-infection of pulmonary TB with HIV. The treatment success rate for pulmonary TB co-infection with HIV in Indonesia in 2022 is 71%. This is still far from the national target of 90%.This case report discusses a 33-year-old man with pulmonary TB and TB lymphadenitis with HIV at clinical stage 4. The CD4 count was 10 cells/mm3. The degree of immunodeficiency suffered by this patient is severe immunodeficiency. The management was to administer OAT first, followed by ART within 2 weeks after OAT was administered and well tolerated. OAT was administered for 9 months due to the presence of TB lymphadenitis. Treatment evaluation showed clinical improvement and the patient did not develop IRIS. The incidence of IRIS in patients with TB is 8%-43%. Factors influencing the occurrence of IRIS include the CD4 count at the start of ART.

PurposeThe purpose of this paper is to find the influence of retailer equity and perceived risk on attitudes toward private label brand (PLB) grocery products.Design/methodology/approachRetailer equity includes four variables: retailer awareness, retailer association, retailer perceived quality and retailer loyalty. The perceived risk factors include functional risk, financial risk and social risk. The attitude toward PLBs was taken as the dependent variable. The study was carried out by using a standardized questionnaire for all three constructs. The convenience sampling method was adopted to carry out data collection from customers of organized retail stores in the city of Coimbatore, in the state of Tamil Nadu, India. The relationship between the three variables was studied with structural equation modeling using IBM SPSS Amos software.FindingsThe study revealed that excluding the Financial Risk and the Social Risk, functional risk alone has significant influence over the PLB Attitude. The Retailer Equity variables, retailer perceived quality and retailer loyalty have positive influence on the PLB Attitude, while the other two variables do not show any influence. Retailer Awareness shows a negative influence over the social risk. Retailer Association does not show any influence on any of the three risk factors. Retailer perceived quality shows negative influence over the functional risk while retailer loyalty negatively influences social risk.Research limitations/implicationsThe research study was carried out in cities that are populous in the Indian state of Tamil Nadu. All the respondents came from three cities in Tamil Nadu, namely, Coimbatore, Tiruppur and Madurai. Hence, extending the findings of the study to other countries where organized retail penetration is deeper may be attempted with caution.Practical implicationsThe study will offer managers in the retail industry some understanding of the risk-relieving factors in operation when buying grocery goods.Originality/valueThe research paper contributes to the literature concerning the role played by retailer equity and perceived risk factors on attitudes toward PLBs.

SummaryThe ever increasing number of Android malware has always been a concern for cybersecurity professionals. Even though plenty of anti‐malware solutions exist, we hypothesize that the performance of existing approaches can be improved by deriving relevant attributes through effective feature selection methods. In this paper, we propose a novel two‐step feature selection approach based on Rough Set and Statistical Test named as RSST to extract refined system calls, which can effectively discriminate malware from benign apps. By refined set of system call, we mean the existence of highly relevant calls that are uniformly distributed thought target classes. Moreover, an optimal attribute set is created, which is devoid of redundant system calls. To address the problem of higher dimensional attribute set, we derived suboptimal system call space by applying the proposed feature selection method to maximize the separability between malware and benign samples. Comprehensive experiments conducted on three datasets resulted in an accuracy of 99.9%, Area Under Curve (AUC) of 1.0, with 1% False Positive Rate (FPR). However, other feature selectors (Information Gain, CFsSubsetEval, ChiSquare, FreqSel, and Symmetric Uncertainty) used in the domain of malware analysis resulted in the accuracy of 95.5% with 8.5% FPR. Moreover, the empirical analysis of RSST derived system calls outperformed other attributes such as permissions, opcodes, API, methods, call graphs, Droidbox attributes, and network traces.

<p>The purpose of this paper is to value the Performance efficiency of Intellectual Capital (IC) on Financial performance indicators of Titan Company Limited. Data required for analysis were collected from the Annual reports of the company for a period of twenty years. This study uses a DEA – CCR – Output Model which consist of intellectual capital indices as input and financial performance measures as output. Results of the efficiency analysis reveals that of the 20 years studied, only 6 years (2007, 2011, 2012, 2013, 2015, and 2016) were found to be the best performing years in terms of harnessing the goodness of intellectual capital. Some years were very close to perfect efficiency score of one, but the rest of the years showed very poor utilisation of intellectual capital to impact financial performance.</p>

The use of forward error correcting codes in the digital communication is used to overcome the data corruptions. Although widely-used, the most popular communications decoding algorithm, the Viterbi algorithm, requires an exponential increase in hardware complexity to achieve greater decode accuracy. The Viterbi decoder that forms the dominant module of TCM decoders are responsible for the overall power consumption. We have analyzed the original T-algorithm with that of the precomputation architecture’s of the T-algorithm. The T-algorithm reduces the complexity of the original viterbi algorithm and reduces the power consumption by 70%.This can be done with the reduction in the negligible clock speed.