Business Value of IT: An Essay on Expanding Research Directions to Keep up with the Times

Much of the work on the business value of IT has examined relationships between IT inputs and economic outcomes of the firm. Yet, business executives and researchers continue to question the value of IT investments. We argue that while the current trajectory of research in this important area is useful, it is limited. In order to address the evolving nature of IT and the novel contexts in which it is being exploited, we must create a discontinuity in our thinking of how IT value should be studied. After summarizing what we have learned thus far, we discuss key new research themes that must be addressed if IT is to be demonstrably relevant. Further, we identify specific research thrusts, areas for theoretical development, and research questions on IT-based value that must be included in our research agenda for the future. We conclude by challenging IT researchers to consider the consequences of status quo research themes versus an expanded set of research questions

Long term monitoring and field testing of an innovative multi-storey timber building

Peer reviewedPostprin

Evaluation of timber-concrete floor performance under occupant-induced vibrations using continuous monitoring

Peer reviewedPreprin

Consensus Message Passing for Layered Graphical Models

Generative models provide a powerful framework for probabilistic reasoning. However, in many domains their use has been hampered by the practical difficulties of inference. This is particularly the case in computer vision, where models of the imaging process tend to be large, loopy and layered. For this reason bottom-up conditional models have traditionally dominated in such domains. We find that widely-used, general-purpose message passing inference algorithms such as Expectation Propagation (EP) and Variational Message Passing (VMP) fail on the simplest of vision models. With these models in mind, we introduce a modification to message passing that learns to exploit their layered structure by passing 'consensus' messages that guide inference towards good solutions. Experiments on a variety of problems show that the proposed technique leads to significantly more accurate inference results, not only when compared to standard EP and VMP, but also when compared to competitive bottom-up conditional models.Comment: Appearing in Proceedings of the 18th International Conference on Artificial Intelligence and Statistics (AISTATS) 201

Deep Learning based Differential Distinguisher for Lightweight Cipher PRESENT

Recent years have seen a major involvement of deep learning architecture in the cryptanalysis of various lightweight ciphers. The present study is inspired by the work of Gohr and Baksi et al. in the field to develop a deep neural network-based differential distinguisher for round reduced PRESENT lightweight block cipher. We present a multi-layer perceptron network which can distinguish between 3-6 rounds of PRESENT cipher data and a randomly generated data with a significantly high probability. We also discuss the possible improvements in the original approach of the differential distinguisher presented by Baksi et al

Deep Learning based analysis of Key Scheduling Algorithm of PRESENT cipher

The lightweight block cipher PRESENT has become viable for areas like IoT (Internet of Things) and RFID tags, due to its compact design and low power consumption, while providing a sufficient level of security for the aforementioned applications. However, the key scheduling algorithm of a cipher plays a major role in deciding how secure it is. In this paper we test the strength of the key scheduling algorithm (KSA) of the 80-bit key length variant of PRESENT by attempting to retrieve the main key register from the final round key register, using deep learning

A Randomized controlled trial to assess the effectiveness of group-based Diabetes Self-Management Education (DSME) program on glycemic control and self-care activities among type-2 diabetics in South-East Delhi

Introduction: India has the second-largest population of diabetes globally. The long-term complications due to poor glycemic control are concerning. Diabetes Self-Management Education (DSME) is a fundamental component in managing diabetes better. Objectives: This study was conducted to compare the effectiveness of group-based DSME in achieving glycemic control and improving self-care practices among people with type-2 diabetes as against the usual care. Methods: A non-blinded parallel-arm RCT among adults (? 30 years) diagnosed with Type-2 DM. Written informed consent was taken from each patient before enrollment. The sample size is estimated to be 85 in each arm according to the formula for equivalence design for an RCT. Randomization was done using a computer-generated random number table. The control arm received usual care, while the intervention group received group-based DSME in addition to usual care. At the end of 6 months, the change in glycemic control and self-care activity scores were compared between the two arms. Results: A total of 139 individuals (intervention =69; control =70) were analyzed. The proportion of females (62.1%) was higher than males (37.9%). There was no statistically significant difference at baseline. At end line, HbA1c showed a reduction from 9.3% to 6.9% in the intervention arm (P<0.001), which was greater than that in the control arm (p=0.017). All the self-care components showed a statistically significant improvement, except the medication score. Conclusions: Group-based DSME effectively increases self-care practices among people with diabetes, resulting in better glycemic control

Acute Kidney Injury, Immune Thrombocytopenic Purpura, and the Infection That Binds Them Together: Disseminated Histoplasmosis

Untreated human immunodeficiency virus (HIV) can be complicated by opportunistic infections, including disseminated histoplasmosis (DH). Although endemic to portions of the United States and usually benign, DH can rarely act as an opportunistic infection in immunocompromised patients presenting with uncommon complications such as acute kidney injury and idiopathic thrombocytopenic purpura. We report a rare presentation of DH presenting with acute kidney injury and immune thrombocytopenic purpura in an immunocompromised patient with HIV

Acute respiratory distress syndrome in Plasmodium vivax malaria. A case-control study of comparison between ARDS and non-ARDS patients in P. Vivax malaria

Background: Plasmodium vivax was conventionally considered to be a benign parasite for centuries but in the recent years have proved to be a virulent parasite causing severe malaria. Acute respiratory distress syndrome (ARDS) is one of such severe complications with a significant morbidity and mortality. The objective of this study was to find the prevalence of ARDS and identify the associated factors that could potentially lead to ARDS in patients with vivax malaria. Methods: A retrospective case-control study was conducted at a tertiary hospital in New Delhi. 329 patients with an established diagnosis of Plasmodium vivax mono-infection were identified using hospital medical records, the associated factors were evaluated and compared to calculate the odds of developing ARDS. All patients were categorized into ARDS cases and non-ARDS controls. Results: The incidence of ARDS was 7% with a female sex predominance (60.86%). Mean urea (71.5 mg/dl), creatinine (2.7 mg/dl), and AST (97.8 units/l) elevation in addition to decreased hemoglobin (7.7 gm/dl) and platelets count (38,217 cells/µl) proved to be significantly associated with ARDS in our study. Conclusions: Plasmodium vivax is a virulent parasite and can cause severe malaria even in the setting of isolated infection. Cytokine mediated diffuse inflammatory response is a postulated pathophysiology causing ARDS