IBM (India)

In this paper, we explain the concept, characteristics & need of Big Data & different offerings available in the market to explore unstructured large data. This paper covers Big Data adoption trends, entry & exit criteria for the vendor and product selection, best practices, customer success story, benefits of Big Data analytics, summary and conclusion. Our analysis illustrates that the Big Data analytics is a fast-growing, influential practice and a key enabler for the social business. The insights gained from the user generated online contents and collaboration with customers is critical for success in the age of social media.

The main interconnect of the massively parallel Blue Gene®/L is a three-dimensional torus network with dynamic virtual cut-through routing. This paper describes both the architecture and the microarchitecture of the torus and a network performance simulator. Both simulation results and hardware measurements are presented.

Gene expression data are accumulating exponentially in public repositories. Reanalysis and integration of themed collections from these studies may provide new insights, but requires further human curation. Here we report a crowdsourcing project to annotate and reanalyse a large number of gene expression profiles from Gene Expression Omnibus (GEO). Through a massive open online course on Coursera, over 70 participants from over 25 countries identify and annotate 2,460 single-gene perturbation signatures, 839 disease versus normal signatures, and 906 drug perturbation signatures. All these signatures are unique and are manually validated for quality. Global analysis of these signatures confirms known associations and identifies novel associations between genes, diseases and drugs. The manually curated signatures are used as a training set to develop classifiers for extracting similar signatures from the entire GEO repository. We develop a web portal to serve these signatures for query, download and visualization.

Purpose Over last few years, a major innovation known as blockchain technology has emerged as potentially one of the most disruptive technology of recent times. The purpose of this paper is to identify and analyze various critical success factors (CSFs) that can facilitate success of blockchain-based cloud services. Further, this paper aims to analyze and understand mutual interactions among these CSFs. Design/methodology/approach In this paper, 19 CSFs have been identified through literature review and expert opinions. The hierarchical framework developed using total interpretive structural modeling has revealed the inter-dependencies among these CSFs. The methodology employed in this study provides a mechanism to conduct an exploratory study by identifying the factors and analyzing their interactions through the development of a hierarchical framework. This research further categorizes CSFs into multiple clusters based on their driving power and dependence power. Findings This paper has identified 19 CSFs, namely, user engagement, industry collaboration, rich ecosystem, blockchain technology standardization, regulatory clarity, cost efficiency, energy efficiency (wasted resources), handling blockchain bloat, miner incentives, business case alignment to blockchain capability, sidechains development, blockchain talent pool availability, leadership readiness for a decentralized consensus based technology, technology investment and maturity, trust on blockchain networks, integration with other cloud services, robust and mature smart contracts platform, blockchain security and user control on data (privacy). Further, driver and dependent variables have been identified. Research limitations/implications Future research can discover and detail the sub-factors behind the 19 CSFs identified in this paper. Additionally, more work can be done to extend the current structural model for blockchain-based services to a more functional form. Practical implications It provides a comprehensive list of CSFs that are relevant for development of blockchain-based cloud services. This will help industry leaders to strategically focus on the main drivers that will ensure that businesses get maximum benefit of this disruptive technology. Originality/value This study makes a significant contribution in the literature of blockchain-based cloud services, which captures the perspective of different stakeholders. This study is one of the first (if not the first) systematic research on adoption of blockchain-based services. It creates the foundation to carry out further research in this area.

On shared-memory systems, Cilk-style work-stealing has been used to effectively parallelize irregular task-graph based applications such as Unbalanced Tree Search (UTS). There are two main difficulties in extending this approach to distributed memory. In the shared memory approach, thieves (nodes without work) constantly attempt to asynchronously steal work from randomly chosen victims until they find work. In distributed memory, thieves cannot autonomously steal work from a victim without disrupting its execution. When work is sparse, this results in performance degradation. In essence, a direct extension of traditional work-stealing to distributed memory violates the work-first principle underlying work-stealing. Further, thieves spend useless CPU cycles attacking victims that have no work, resulting in system inefficiencies in multi-programmed contexts. Second, it is non-trivial to detect active distributed termination (detect that programs at all nodes are looking for work, hence there is no work). This problem is well-studied and requires careful design for good performance. Unfortunately, in most existing languages/frameworks, application developers are forced to implement their own distributed termination detection.

Global plastic waste is increasing rapidly. In general, densely populated regions generate tons of plastic waste daily, which is sometimes disposed of on land or diverged to sea. Most of the plastics created in the form of waste have complex degradation behavior and are non-biodegradable by nature. These remain intact in the environment for a long time span and potentially originate complications within terrestrial and marine life ecosystems. The strategic management of plastic waste and recycling can preserve environmental species and associated costs. The key contribution in this work focuses on ongoing efforts to utilize plastic waste by introducing blockchain during plastic waste recycling. It is proposed that the efficiency of plastic recycling can be improved enormously by using the blockchain phenomenon. Automation for the segregation and collection of plastic waste can effectively establish a globally recognizable tool using blockchain-based applications. Collection and sorting of plastic recycling are feasible by keeping track of plastic with unique codes or digital badges throughout the supply chain. This approach can support a collaborative digital consortium for efficient plastic waste management, which can bring together multiple stakeholders, plastic manufacturers, government entities, retailers, suppliers, waste collectors, and recyclers.

The IoT devices captures data and sends it to Cloud for computation but data transfer process from IoT device to Cloud can take lot of time if volume of data is large. Therefore, it makes sense to process captured data locally at IoT edge node to avoid latency. In Edge Computing, the Gateway stores data and perform computations along with traffic aggregation and routing. While Edge analytics allows pre-processing and filtering of the data closer to where it's being created but the data which falls within normal range can be stored in low cost IoT storage and abnormal readings will be sent to Data Lake or in-memory database. Edge Computing will boost traditional Cloud computing model with service nodes placed at the network edges. It will help traditional data center cloud models by reducing latency and increased bandwidth. In future computation and data processing power will slowly shift towards edge devices like sensors, drones, driverless cars etc. Playing augmented reality, 3D video games, content-based video analysis is a challenge on mobile phone due to limited processing power and battery life. Realtime analysis of massive sensor data is needed in industries like manufacturing, mining, transportation to detect anomalies and send alerts. Therefore, Edge Computing and Cloud computing are likely to follow more of a hybrid approach and complement each other. This paper talks about Edge computing architecture, computational offloading approaches, Edge Computing challenges and benefits etc.

As the semiconductor process technology advances into sub-10nm regime, cell pin accessibility, which is a complex joint effect from the pin shape and nearby blockages, becomes a main cause for DRC violations. Therefore, a machine learning model for DRC hotspot prediction needs to consider both very high-resolution pin shape patterns and low-resolution layout information as input features. A new convolutional neural network technique, J-Net, is introduced for the prediction with mixed resolution features. This is a customized architecture that is flexible for handling various input and output resolution requirements. It can be applied at placement stage without using global routing information. This technique is evaluated on 12 industrial designs at 7nm technology node. The results show that it can improve true positive rate by 37%, 40% and 14% respectively, compared to three recent works, with similar false positive rates.

The concept of containerization and virtualization is getting traction in the cloud based IT environments. Docker engine is popular implementation for simplifying and streamlining containerization technology. IT industry realizes numerous automation and acceleration features and facilities through the embracement of the Docker-sponsored containerization paradigm, which is an operating system (OS)-level and lightweight virtualization. However the security issues affect the widespread and confident usage of Docker platform. In this paper, we have discussed important security issues of the Docker containers as well as the related work that is being carried out in this area. Also we have proposed security algorithms and methods to address DoS attacks related issues in the Docker container technology. The preliminary experiments and testing of the security methods are promising.

Cloud computing has emerged as a transformative force in healthcare and biomedical sciences, offering scalable, on-demand resources for managing vast amounts of data. This review explores the integration of cloud computing within these fields, highlighting its pivotal role in enhancing data management, security, and accessibility. We examine the application of cloud computing in various healthcare domains, including electronic medical records, telemedicine, and personalized patient care, as well as its impact on bioinformatics research, particularly in genomics, proteomics, and metabolomics. The review also addresses the challenges and ethical considerations associated with cloud-based healthcare solutions, such as data privacy and cybersecurity. By providing a comprehensive overview, we aim to assist readers in understanding the significance of cloud computing in modern medical applications and its potential to revolutionize both patient care and biomedical research.

Helium nanodroplets are widely used as a cold, weakly interacting matrix for spectroscopy of embedded species. In this work, we excite or ionize doped He droplets using synchrotron radiation and study the effect onto the dopant atoms depending on their location inside the droplets (rare gases) or outside at the droplet surface (alkali metals). Using photoelectron-photoion coincidence imaging spectroscopy at variable photon energies (20-25 eV), we compare the rates of charge-transfer to Penning ionization of the dopants in the two cases. The surprising finding is that alkali metals, in contrast to the rare gases, are efficiently Penning ionized upon excitation of the (n = 2)-bands of the host droplets. This indicates rapid migration of the excitation to the droplet surface, followed by relaxation, and eventually energy transfer to the alkali dopants.

In the present study, noncovalently functionalized tungsten disulfide (WS2) nanosheets were used as a toughening agent for epoxy nanocomposites. WS2 was modified with branched polyethyleneimine (PEI) to increase the degree of interaction of nanosheets with the epoxy matrix and prevent restacking and agglomeration of the sheets in the epoxy matrix. The functionalization of WS2 sheets was confirmed through Fourier transform infrared spectroscopy and thermogravimetric analysis. The exfoliation of the bulk WS2 was confirmed through X-ray diffraction and various microscopic techniques. Epoxy nanocomposites containing up to 1 wt % of WS2–PEI nanosheets were fabricated. They showed a remarkable improvement in fracture toughness (KIC). KIC increased from 0.94 to 1.72 MPa m–1/2 for WS2–PEI nanosheet loadings as low as 0.25 wt %. Compressive and flexural properties also showed a significant improvement as incorporation of 0.25 wt % of WS2–PEI nanosheets resulted in 43 and 65% increase in the compressive and flexural strengths of epoxy nanocomposites, respectively, compared with neat epoxy. Thermal stability and thermomechanical properties of the WS2–PEI-modified epoxy also showed a significant improvement. The simultaneous improvement in the mechanical and thermal properties could be attributed to the good dispersion of WS2–PEI nanosheets in the matrix, intrinsic high strength and thermal properties of the nanosheets, and improved interaction of the WS2 nanosheets with the epoxy matrix owing to the presence of PEI molecules on the surface of the WS2 nanosheets.

Harnessing unique physical properties of integrated circuits to enhance hardware security and IP protection has been extensively explored in recent years. Physical unclonable functions (PUFs) can sense inherent manufacturing variations as chip identifications. To enable the integration of PUFs into low-power and security applications, we study the impacts of process technology and supply voltage scaling on arbiter-based PUF circuit design. A Monte Carlo-based statistical analysis has demonstrated that advanced technologies and reduced supply voltage can improve the PUF uniqueness due to increased delay sensitivity. A linear regression approach has been leveraged to generate PUF delay profile by factoring in device, supply voltage and temperature variations. An accurate SVM-based software modeling analysis is used to verify the PUF additive delay behavior. Finally, postsilicon validation on arbiter-based PUF test chips in 45 nm SOICMOS technology has been correlated to simulation results and the inconsistency has been discussed. The test chips can resist the basic support vector machine attack due to the dynamic circuit effects and the limitation of our delay model.

Read-copy update (RCU) is a synchronization mechanism in the Linux™ kernel that provides significant improvements in multiprocessor scalability by eliminating the writer-delay problem of readers-writer locking. RCU implementations to date, however, have had the side effect of expanding non-preemptible regions of code, thereby degrading real-time response. We present here a variant of RCU that allows preemption of read-side critical sections and thus is better suited for real-time applications. We summarize priority-inversion issues with locking, present an overview of the RCU mechanism, discuss our counter-based adaptation of RCU for real-time use, describe an additional adaptation of RCU that permits general blocking in read-side critical sections, and present performance results. We also discuss an approach for replacing the readers-writer synchronization with RCU in existing implementations.

Abstract This article stresses the need for today's multinational firms to adopt their own political risk‐assessment and risk‐mitigation strategies. A comparative study of the energy, financial, and automobile sectors illustrates the need for all companies in these sectors to undertake comprehensive risk‐assessment strategies. Risk‐assessment models established by leading multinationals like British Petroleum, Bank of America, and General Motors are examined as examples that other companies in these sectors can build upon. The consistent micropolitical risk variables then lead to a proposed practical framework for examining sector‐specific micropolitical risk. © 2006 Wiley Periodicals, Inc.

PURPOSE: The purpose of this paper is to explore the route map for employing efficient e-governance so that at least existing resource and infrastructure are better utilized and deficiencies are tracked for future planning. National health is one of the most important factors in a country's economic growth. India seems to be a victim of the vicious cycle around poor economy and poor health conditions. DESIGN/METHODOLOGY/APPROACH: A detailed study was carried out to find out India's healthcare infrastructure and its standing in e-governance initiatives. After consolidating the fact that effective e-governance can enhance the quality of healthcare service even within limited resources, authors explored success and failure factors of many e-governance initiatives in India and abroad. Finally, an e-governance framework is suggested based on the above factors together with the authors' own experience of implementing e-governance projects in India and abroad. FINDINGS: The suggested framework is based on a phased implementation approach. The first phase "Information Dissemination" is more geared towards breaking the "digital divide" across three dimensions: G2Business; G2Citizen; and G2Agent. The most advanced stage is aimed towards joining up healthcare information across the above three dimensions and drawing meaningful analytics out of it. The recommendations also include management of Policies, Scope, Process Reform, Infrastructure, Technology, Finance, Partnership and People for efficient implementation of such e-governance initiatives. RESEARCH LIMITATIONS/IMPLICATIONS: The paper provides measures for continuous evaluation of systems as one passes through various stages of implementation. However, the framework can be tested on real or simulated environment to prove its worthiness. PRACTICAL IMPLICATIONS: This paper can be a potential frame of reference for nation-wide e-healthcare projects not only in India but also in other developing countries. The paper also describes challenges that are most likely to be faced during implementation. ORIGINALITY/VALUE: Since the paper is practical in nature, the real appeal will be to practitioners who are responsible for implementation of large e-governance initiatives for improving healthcare services.

Advanced computing systems have long been enablers for breakthroughs in artificial intelligence (AI) and machine learning (ML) algorithms, either through sheer computational power or form-factor miniaturization. However, as AI/ML algorithms become more complex and the size of data sets increases, existing computing platforms are no longer sufficient to bridge the gap between algorithmic innovation and hardware design. This article presents a survey about various ML accelerators.

In this work, the high frequency (RF) performance of FinFETs is investigated in detail using a two-level parasitic model comprising outer and inner parasitic capacitances in addition to parasitic series resistances. Use of scaling relations of these parasitic capacitances with numbers of fins and fingers allows extraction of these elements. Next, by defining a series of reference surfaces, each associated with a certain set of parasitic elements, we proceed to calculate the RF Figures of Merit, namely fT and fmax at these surfaces. These are called ‘available fT (fmax)’ in this work. Analysis of the available fT (fmax) gives insight into the extent to which different parasitics affect the FinFET’s RF performance. The main bottleneck to the FinFET’s RF performance is identified, solutions are proposed and relevant trade-offs are discussed.

In recent years, cloud computing has emerged as a successful mode of delivery for Software as a Service (SaaS) offerings and more generically anything as a service (XaaS) offerings. Cloud computing is, an evolutionary paradigm shift in the ways computing platforms and services are made available to the consumers, and this has been made possible due to numerous technology enablers, along with changing business strategies. These changes have contributed significantly in achieving the market shift from differentiated to undifferentiated price models, thereby helping the market movements from monopolistic to perfect competition, and resulting in converting traditional enterprise class software tools and hardware platforms into a commodity. This paper, is a survey on pricing strategies and schemes employed in cloud offerings wherein we study various mechanisms currently being used. The literature survey encompasses market trends on cloud pricing with specific focus on emerging market scenario of India. Based on the need of providing flexible pricing, we discuss our position on a revenue framework wherein cloud pricing strategy is a function of periodic resource utilization analysis, and provide details of our revenue generation model that depends on cross over of different pricing schemes.

The importance of tiles or blocks in scientific computing cannot be overstated. Many algorithms, both iterative and recursive, can be expressed naturally if tiles are represented explicitly. From the point of view of performance, tiling, either as a code or a data layout transformation, is one of the most effective ways to exploit locality, which is a must to achieve good performance in current computers because of the significant difference in speed between processor and memory. Furthermore, tiles are also useful to express data distribution in parallel computations. However, despite the importance of tiles, most languages do not support them directly. This gives place to bloated programs populated with numerous subscript expressions which make the code difficult to read and coding mistakes more likely.