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HCL Technologies Ltd. is an IT Software, service, and consulting company, headquartered at Noida, Uttar Pradesh, India. It is the part of HCL Enterprises Company. In 1976, a group of six engineers started a company that would make personal computers and the group was led by Mr. Shiv Nadar. Initially, the company name was Micro Comp Ltd. The company started to sell tile digital calculators to gather capital for their main project. On 11 August 1976, the company was renamed to Hindustan Computer Limited (HCL). On 12th November 1991, another subsidiary company called HCL Overseas Limited was incorporated as a provider of technology development service. HCL company is one of the four companies comes under the company HCL enterprises. HCL developed an indigenous microcomputer in 1978, and a networking OS and client-server architecture in 1983. On 12 November 1991, HCL Technologies was distributed as a separate unit to provide software services. Hindustan Computer Limited offers services including IT Consulting, Enterprise Transformation, remote infrastructure management, engineering and R&D, and business process outsourcing (BPO). HCL services include DRYiCE, Cybersecurity, and digital & analytics. The company has the branches in 34 countries including USA, CANADA, JAPAN, UK, FRANCE, and GERMANY. It operates across sectors including aerospace and defense, automotive, consumer electronics energy and utilities, financial service and governments. HCL Technologies in Forbes Global 2000 list. As of September 2017, the company along with its subsidiaries had consolidated revenue of $7.4 billion. In this paper, we have studied the products and services of HCL technologies and its strategies to face competitions using various case study methodologies. The internal and external opportunities analysis is done by means of SWOT analysis.

Wireless sensor network (WSN) is a low-powered prestigious network fashioned by sensor nodes that treasures application in civilian, military, visual sense models and many others. Reduced energy utilization is an exigent task for these sensor networks. By the data aggregation procedure, needless communication between sensor nodes, cluster head and the base station is eluded. An evaluation of energy efficient optical low energy adaptive clustering hierarchy has been performed and the enactments have been compared with the prevailing low energy adaptive clustering hierarchy algorithm, between two detached wireless sensor network fields. The proposed clustering procedure has been primarily implemented to join two distinct wireless sensor fields. An optical fiber is used to join two reserved wireless sensor fields. This distributed clustering methodology chiefly targets in exploiting the parameters like network lifetime, throughput and energy efficiency of the whole wireless sensor system.

Unacceptable philosophies are stifled by social rather than official pressures

AbstractSelective catalytic reduction (SCR) systems are employed by automobile manufacturers for the abatement of environmental pollutants like oxides of nitrogen (NOx) emitted from exhaust gases of diesel engines. In SCR, the urea-water solution (UWS) is injected to exhaust gases in the form of a spray to generate the reducing agent NH3. Deposit formation at lower temperatures is a major concern with this technology. The deposits not only create backpressure but also leak NH3 to the environment as they deplete. It is very important to know the depletion characteristics of deposits formed at lower temperatures in order to assess the NH3 leakage to the environment when the engine exhaust gases attain higher temperatures. In the present work, deposits formed at a low-temperature range of 150–200°C for continuous run along with UWS injection were investigated. Additionally, they were aged at 300°C in the absence of UWS to check the variation in characteristics with the rise of temperature. By gravimetric analysis, it is inferred that the deposits formed at higher pre-age temperatures are less prone to depletion as the temperature increases. The elemental analysis using energy-dispersive X-ray spectroscopy (EDX) indicates slight variation in carbon, nitrogen and oxygen compositions for all the pre-age conditions. As an extended study, the byproducts at pre-age and post-age conditions were investigated through X-ray diffraction (XRD). The compounds like cyanuric acid (CYA) and biuret were not observed when pre-age samples were aged at 300°C. Instead, the compounds like ammelide, ammeline, triuret and melamine were observed. Scanning electron microscope (SEM) study revealed morphological changes in both pre-age and post-age samples. Further, the crystallinity variations were also observed for the changes in the heating cycles during deposit formation. The gravimetric analysis of deposits in pre-age and post-age conditions helps in predicting the amount of deposits for transient load cycles.

The development of wireless sensor networks was motivated by military applications such as battlefield surveillance; today such networks are used in many industrial and consumer applications, such as industrial process monitoring and control, machine health monitoring, and so on. Wireless sensor Networks (WSNs), is one of the most rapidly growing scientific domain. This is because of the development of advanced sensor nodes with extremely low cost and the potential application of such sensor nodes are ever growing. One of the characteristic feature of WSNs compared to the traditional wireless communication networks, is the power awareness, due to the fact that the batteries of the sensor nodes have restricted lifetime and are difficult to be replaced. This is why we focus on power awareness, while the traditional wireless networks mainly focuses on the QOS. A typical sensor node consumes most of its energy during communication. However, energy expenditure takes place while performing sensing and data processing too. This work suggests the development of an advanced hierarchical routing technique, which gives improved performance over the existing techniques. Power consumption is highly reduced, thereby greatly reducing the cost of network and hence the lifetime of nodes can be greatly improved.