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At present municipal solid waste (MSW) has become one of the biggest national concerns because mismanagement of MSW deteriorates the purity and cleanliness of the environment. In this direction, this manuscript discusses the details of generation, characterization of MSW, and current practice of municipal solid waste management in Himachal Pradesh (HP), a state in the northern region of India. Himachal Pradesh generates approximately 342.35 tons per day (TPD). Thus, it is a massive challenge for the municipalities of HP to manage it in a hilly region. Hilly regions of HP are prone to rapid climate change i.e., rainfall and snowfall in winter and hence found to be one of the important factors that affect the collection and treatment process of waste management. Indeed, the generation of waste decisively depends upon the tourism business. Further, the tourism business also depends upon seasonal variation. Difficult terrain and socio-economic condition of local people make waste disposal and transportation more difficult for the appropriate planning of the management of municipal solid waste. The characterization studies show that the biodegradable fraction in MSW is more than 50% which indicates a significant energy potential. The manuscript covers issues and challenges in waste management due to climatic conditions in the hilly regions of HP and also recommends the best suitable remedial measures for the proper management of the existing MSW system and its appropriate treatment alternatives. Hence this manuscript provides a wholesome glimpse of the possibilities of energy, global warming potential, and the economic aspects of MSW in the regions of HP. The findings will help the stakeholders and policymakers in better decision-making.

Regression testing validates the modified software and safeguards against the introduction of new errors during modification. A number of test suite optimization techniques relying on meta-heuristic techniques have been proposed to find the minimal set of test cases to execute for regression purposes. This paper proposes a hybrid spider monkey optimization based regression test suite optimization approach and empirically compares its performance with three other approaches based on bat search, ant colony, and cuckoo search. The authors conducted an empirical study with various subjects retrieved from software artifact infrastructure repository. Fault coverage and execution time of algorithm are used as fitness measures to meet the optimization criteria. Extensive experiments are conducted to evaluate the performance of the proposed approach with other search-based approaches under study using various statistical tests like m-way ANOVA and post hoc tests including odds ratio. Results indicate the superiority of the proposed approach in most of the cases and comparable in others.

A field investigation on anaerobic digestion of food waste for 235 days in a 3000 L semi-continuous biogas reactor has been conducted in the hilly area of Solan (1544 m above mean sea level), Himachal Pradesh, India. To the best of our knowledge, this is the first study which optimized organic loading rate for food waste in ambient condition for summer (0.34 g VS/L/day) and winter season (0.24 g VS/L/day) in Himachal Pradesh, India. On the basis of results obtained from the 3,000L biogas reactor, a detailed investigation of energy potential, techno-economic feasibility and comparison of global warming potential due to landfill, composting and anaerobic digestion is conducted for all 11 hilly states of India. From the analysis, it is found that anaerobic digestion is the best method amongst these for managing food waste and has an approximate energy potential of 13,770 GWh in the next decade. From the techno-economic analysis, it is estimated that capital investment for anaerobic digestion process has a payback time of 5.9 years with a 4.6% internal rate of return and approximately 1400 million £ net profit value.

Regression testing is an activity of finding bugs in the modified parts of the software and releases the software versions timely to avoid further risks. Retesting of all existing test cases including obsolete and redundant test cases is increasing the cost and efforts of the overall process. In order to reduce this cost and time, optimization algorithms are playing a vital role. This paper focuses on the performance analysis of three recent metaheuristic algorithms: Cuckoo Search, Crow Search Algorithm, and Harris Hawks Optimization to solve the RTCS problem for selecting the test cases. Fault coverage and execution time parameters have been selected for performance evaluation. The experiments are performed and analyzed on standard SIR repository. The results and statistical tests show that Cuckoo Search and Crow Search Algorithm significantly give better results for different parameters of RTCS problem than Harris Hawks Optimization (HHO). The Cuckoo Search outperformed on fault coverage, and Crow Search Algorithm outperformed on time parameter.

Test suite optimization is an ever-demanded approach for regression test cost reduction. Regression testing is conducted to identify any adverse effects of maintenance activity on previously working versions of the software. It consumes almost seventy percent of the overall software development lifecycle budget. Regression test cost reduction is therefore of vital importance. Test suite optimization is the most explored approach to reduce the test suite size to re-execute. This article focuses on test suite optimization as a regression test case selection, which is a proven N-P hard combinatorial optimization problem. The authors have proposed an almost safe regression test case selection approach using a Hybrid Whale Optimization Algorithm and empirically evaluated the same on subject programs retrieved from the Software Artifact Infrastructure Repository with Bat Search and ACO-based regression test case selection approaches. The analyses of the obtained results indicate an improvement in the fault detection ability of the proposed approach over the compared ones with significant reduction in test suite size.

Wireless Sensor Network (WSN) is an interconnected system of sensors capable of sensing environmental changes and communicating these perceived changes to a centralized location, where this sensed data can be processed for further decision-making purposes. This makes it suitable for WSNs to be successfully deployed in various domains like home monitoring, vehicle tracking, environmental monitoring, agricultural field monitoring, military applications, and many more. For successful deployment, efficiency is one of the critical terms that remain associated with WSNs, and along with other factors, efficiency largely depends on the routing protocols used to deploy WSNs. The hierarchical routing protocol is one of the routing strategies used for this, others being location-based and the traditional Flat routing protocol. This paper talks about the well-established and appreciated hierarchical routing protocols and also discusses the results of the two main hierarchical routing protocols, namely Low-Energy Adaptive Clustering Hierarchy (LEACH) and Power-Efficient Gathering in Sensor Information System (PEGASIS). The paper will help budding researchers gain a quick insight into the discussed protocols to investigate further.

In modern era, industries demand for innovative and reliable software solutions. To maintain the reliability level of softwares various software reliability growth models were proposed in last four decades. These models performance relies on parameter estimation approaches utilized to find the optimum values of their unknown model parameters. But, developing an approach that provides the perfect optimum parameter for software reliability growth models (SRGMs) has been the issue of concern within the research community over the decades. This paper adopted the Improved Grey Wolf Optimizer (IGWO) for parameter estimation and compares its accuracy with existing approach Grey Wolf Optimizer (GWO) in estimating the optimum parameters for software reliability growth models. GWO imitates the social leadership pyramid and the hunting methods adopted by grey wolves; IGWO was later proposed to resolve the deficiencies observed in GWO for improved performance. Seven real world failure datasets have been utilized to measure and evaluate the performance of the proposed approach against the existing approach. The results indicate that proposed approach (IGWO) outperform the existing one (GWO).

In this study, the municipal solid waste methane emission, energy, and global warming potential inventory for 2005–2030 is estimated at both national and state level for India using the In...

This study reports the sustainability of a large semicontinuous anaerobic reactor (3,000 L) for biogas production from food wastes for a period of 324 days. The methane potential ranged fro...

This work describes mainly the optical absorption, photoluminescence (PL) and decay spectral properties of Sm3+ ions doped borate glasses to understand their possible usage in tricolor w-LEDs and lasers.The XRD spectrum recorded for an un-doped glass confirms glassy nature of the as prepared glass. The Judd-Ofelt (J-O) intensity parameters evaluated from experimental oscillator strengths were used in estimating the various radiative parameters. Under 402 nm excitation, the PL spectra exhibit intense emission at 600 nm for which the decay spectral profiles were recorded.The decay profiles are converting from single exponential to non-exponential with increase in Sm3+ ion concentration ensuing decrease in experimental lifetimes which may be attributed to the efficient energy transfer through cross-relaxation process. The non-exponential decay curves fitted to I-H model reveals the interaction between the Sm3+ ions as dipole-dipole in nature. From the evaluated emission cross-sections, quantum efficiency, branching ratios and CIE co-ordinates, it is concluded that 1 mol% Sm3+ ions in these glasses are aptly suitable to fabricate reddish-orange luminescent devices.