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Economic load dispatch (ELD) is one of the crucial optimization problems in power system planning and operation. The ELD problem with valve point loading (VPL) and multi-fuel options (MFO) is defined as a non-smooth and non-convex optimization problem with equality and inequality constraints, which obliges an efficient heuristic strategy to be addressed. The purpose of this study is to present a new and powerful heuristic optimization technique (HOT) named as squirrel search algorithm (SSA) to solve non-convex ELD problems of large-scale power plants.

The suggested SSA approach is aimed to minimize the total fuel cost consumption of power plant considering their generation values as decision variables while satisfying the problem constraints. It confers a solution to the ELD issue by anchoring with foraging behavior of squirrels based on the dynamic jumping and gliding strategies. Furthermore, a heuristic approach and selection rules are used in SSA to handle the constraints appropriately.

Empirical results authenticate the superior performance of SSA technique by validating on four different large-scale systems. Comparing SSA with other HOTs, numerical results depict its proficiencies with high-qualitative solution and by its excellent computational efficiency to solve the ELD problems with non-smooth fuel cost function addressing the VPL and MFO. Moreover, the non-parametric tests prove the robustness and efficacy of the suggested SSA and demonstrate that it can be used as a competent optimizer for solving the real-world large-scale non-convex ELD problems.

This study has compared various HOTs to determine optimal generation scheduling for large-scale ELD problems. Consequently, its comparative analysis will be beneficial to power engineers for accurate generation planning.

To the best of the authors’ knowledge, this manuscript is the first research work of using SSA approach for solving ELD problems. Consequently, the solution to this problem configures the key contribution of this paper.

This study aimed to developed a defect detection system for a segment-type display module panel.

The system included a data acquisition card, a video camera, a computer and a display module on a testing table. The video camera captured the display pattern of the display module and transferred it to the computer through the data acquisition card. The dynamic multi-thresholding method and analysis as well as back propagation neural network classification was used to classify the detected defects.

The threshold values for the brightness at different positions in the display module image were obtained using the neural network and then stored in the look-up table, using two to six matrixes.

The recognition speed was faster and the system was more flexible in comparison to the previous system. The proposed method, using unsophisticated and economical equipment, was also verified as providing highly accurate results with a low error rate.

Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power.

Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol.

Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes.

Other optimization techniques can be applied for WSN to analyze the performance.

Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes.

Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage.

Literature survey is carried out to find the methods which give better performance.

The 2008‐2009 global crisis was not only a financial calamity, but also a major ethical disaster. The purpose of this paper is to discuss the dharmic transgressions that took place in connection with the crisis using the philosophy of Bhagavan Sri Sathya Sai Baba, a world spiritual leader and teacher.

The paper initially gives a brief overview of the unfolding crisis, its devastation of the world economy and a review of related literature. The paper then outlines the concept of dharma which, as expounded by Bhagavan Baba, must ultimately result in social welfare. The paper goes on to analyze the factors that created, triggered and fuelled the crisis from this perspective. The paper also outlines solutions based on Baba's philosophy to prevent such a crisis from occurring in the future.

The fundamental finding of the paper is that the global financial crisis was triggered and fuelled by factors which were transgressions of dharma. Thus, the solution to prevent such a crisis is adherence to dharma.

The paper gives several recommendations to investors, institutions and regulators to act in a way to prevent such crises in the future.

If the principles of dharma are adhered to, they will not only prevent occurrence of financial crises, but will also make the financial system work for the welfare of the entire society.

The paper shows the relevance of the teachings of Bhagavan Baba which are quintessentially the philosophy of “Sanathana Dharma” (eternal dharma) in solving current economic problems and contributing to social welfare.

In class action antitrust litigation, the standards for acceptable economic analysis at class certification have continued to evolve. The most recent event in this evolution is the United States Supreme Court’s decision in Comcast Corp. v. Behrend, 133 S. Ct. 1435 (2013). The evolution of pre-Comcast law on this topic is presented, the Comcast decision is thoroughly assessed, as are the standards for developing reliable economic analysis. This article explains how economic evidence of both antitrust liability and damages ought to be developed in light of the teachings of Comcast, and how liability evidence can be used by economists to support a finding of common impact for certification purposes. In addition, the article addresses how statistical techniques such as averaging, price-dispersion analysis, and multiple regressions have and should be employed to establish common proof of damages.

In computer application scenario, data mining task is rarely utilized in power system, as an enhanced part, this work presented data mining task in power systems, to overcome frequency deviation issues. Load frequency control (LFC) is a primary challenging problem in an interconnected multi-area power system.

This paper adopts lion algorithm (LA) for the LFC of two area multi-source interconnected power systems. The LA calculates the optimal gains of the fractional order PI (FOPI) controller and hence the proposed LA-based FOPI controller (LFOPI) is developed.

For the performance analysis, the proposed algorithm compared with various algorithm is given as, 80.6% lesser than the FOPI algorithm, 2.5% lesser than the GWO algorithm, 2.5% lesser than the HSA algorithm, 4.7% lesser than the BBO algorithm, 1.6% lesser than PSO algorithm and 80.6% lesser than the GA algorithm.

The LFOPI controller is the proposed controlling method, which is nothing but the FOPI controller that gets the optimal gain using the LA. This method produces better performance in terms of converging behavior, optimization of controller gain, transient profile and steady-state response.

This study aims to provide a secured data aggregation with reduced energy consumption in WSN. Data aggregation is the process of reducing communication overhead in wireless sensor networks (WSNs). Presently, securing data aggregation is an important research issue in WSNs due to two facts: sensor nodes deployed in the sensitive and open environment are easily targeted by adversaries, and the leakage of aggregated data causes damage in the networks, and these data cannot be retrieved in a short span of time. Most of the traditional cryptographic algorithms provide security for data aggregation, but they do not reduce energy consumption.

Nowadays, the homomorphic cryptosystem is used widely to provide security with low energy consumption, as the aggregation is performed on the ciphertext without decryption at the cluster head. In the present paper, the Paillier additive homomorphic cryptosystem and Boneh et al.’s aggregate signature method are used to encrypt and to verify aggregate data at the base station.

The combination of the two algorithms reduces computation time and energy consumption when compared with the state-of-the-art techniques.

The secured data aggregation is useful in health-related applications, military applications, etc.

The new combination of encryption and signature methods provides confidentiality and integrity. In addition, it consumes less computation time and energy consumption than existing methods.

The paper aims to discuss the management of financial market scandals using two different approaches – regulatory and values‐based.

The paper discusses the motivations behind financial scandals to occur and then explains in detail both the approaches. The paper first presents the elements of the regulatory approach. Using the teachings of Bhagavan Sri Sathya Sai Baba, the values‐based approach are delineated. The paper also compares the two approaches and identifies their respective utilities.

While both the regulatory and values based approaches have their own utilities; stressing the values‐based approach helps with preventing financial scandals on a sustainable basis.

The practical implication is that it is necessary to stress the evocation of human values among investors and capital market intermediaries so that scandals can be avoided.

The social implication of the paper is that values evocation is very important to tackle the behavioural motivations behind financial scandals. Unless values are evoked, the root causes of financial scandals will not be removed. In such cases, regulation will have only a limited effect.

The paper uses the philosophy and teachings of Bhagavan Sri Sathya Sai Baba to develop value guidelines to prevent financial scandals.

This study aims to examine the effects of various physical and chemical pre-treatments on antioxidant properties of tree bean (Parkia roxburghii G. Don) in combination with storage conditions.

The whole pods and seeds of tree bean were treated with gamma rays (γ-rays), sodium hypochlorite (NaOCl), chlorine dioxide (ClO₂) and hydrogen peroxide (H₂O₂) and stored at room temperature (RT, 25°C) for 30 days. The physical and chemical pre-treated seeds and pods were compared with the same stored at RT and refrigerated storage at 4°C and −20°C. During storage, physical (moisture content) and antioxidants like total phenolics, ascorbate content, reduced glutathione, total flavonoids, along with free radical scavenging activities (FRSA) were measured.

Chemical pre-treatments with NaOCl, ClO₂ and H₂O₂ significantly accelerated (p = 0.05) the total phenolics (1.9 mg/g FW in seeds and 2.4 mg/g FW in pods), flavonoids content (0.3 mg/g FW each in seeds and pods) and ABTS activities (73.3 per cent in seeds and 92.3 per cent in pods) at 30 days of storage. A significant decrease (p = 0.05) in ascorbate content (6.1 mg/g FW in seeds and 3.5 mg/g FW in pods), reduced glutathione (5.1 mg/g FW in seeds and 3.7 mg/g FW in pods), FRAP (0.3 mg equi Fe/g FW in seeds and 0.4 mg equi Fe/g FW in pods) and reducing power (1.8 mg/g FW in seeds and 3.7 mg/g FW in pods) was observed under all the treatments at 30 days of storage. However, DPPH increased under γ-irradiation and decreased under chemical pre-treatments, storage at RT and refrigerated storage. The overall result showed that pre-treatment of H₂O₂ at 10-20 mM maintains antioxidants and radical scavenging activities in tree bean during storage.

The application of H₂O₂ at 10-20 mM prior to storage of tree bean maintains the physical, antioxidant properties and FRSA in tree bean seeds and pods as compared to natural ambient conditions. Hence, this technique will help in improving the keeping quality of this legume and avoid spoilage after harvest for an extended period.

This study aims to explore the linkage between fluctuations in the global crude oil price and equity market in fast emerging economies of India and China.

The present research uses wavelet decomposition and maximal overlap discrete wavelet transform (MODWT), which decompose the time series into various frequencies of short, medium and long-term nature. The paper further uses continuous and cross wavelet transform to analyze the variance among the variables and wavelet coherence analysis and wavelet-based Granger causality analysis to examine the direction of causality between the variables.

The continuous wavelet transform indicates strong variance in WTIR (return series of West Texas Instrument crude oil price) in short, medium and long run at various time periods. The variance in CNX Nifty is observed in the short and medium run at various time periods. The Chinese stock index, i.e. SCIR, experiences very little variance in short run and significant variance in the long and medium run. The causality between the changes in crude oil price and CNX Nifty is insignificant and there exists a bi-directional causality between global crude oil price fluctuations and the Chinese equity market.

To the best of the authors’ knowledge, very limited work has been done where the researchers have analyzed the linkage between the equity market and crude oil price fluctuations under the framework of discrete wavelet transform, which overlooks the bottleneck of non-stationarity nature of the time series. To bridge this gap, the present research uses wavelet decomposition and MODWT, which decompose the time series into various frequencies of short, medium and long-term nature.