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A new record of monogeneric family Vietnamellidae (Insecta: Ephemeroptera) from India
C. Selvakumar,Bikramjit Sinha,M. Vasanth,K.A. Subramanian,K.G. Sivaramakrishnan 한국응용곤충학회 2018 Journal of Asia-Pacific Entomology Vol.21 No.3
A new record of monogeneric family Vietnamellidae (Insecta: Ephemeroptera) is established for India with Vietnamella sp. A described based on the larvae from Arunachal Pradesh, India. This species can be distinguished from other known species of this genus in the larval stage by the following combination of characters: (i) outer pair of projections in head large and stout, triangular, cone-shaped with serrated spines; (ii) posterolateral angles of abdominal terga 2–9 extended into sharp projections; (iii) caudal filaments pale yellowish brown with dense lateral setae on inner and outer margins of middle part; (iv) femora of mid- and hind-legs broader; and (v) second segment of the maxillary palpi shorter than first segment.
( Gopal Selvakumar ),( Pyoung Ho Yi ),( Seong Eun Lee ),( Charlotte C. Shagol ),( Seung Gab Han ),( Tongmin Sa ),( Bong Nam Chung ) 한국균학회 2018 Mycobiology Vol.46 No.2
Arbuscular mycorrhizal fungi (AMF) are well-known for their ability to improve plant growth and help plants withstand abiotic stress conditions. Unlike other fungi and bacteria, AMF cannot be stored, as they are obligate biotrophs. Long-term preservation of AMF spores is challenging and may lead to the loss of viability and efficiency. This study aimed to understand the effect of prolonged subculture of AMF species on the growth and glomalin-related soil protein (GRSP) from red pepper (Capsicum annuum L.). AMF spores were mass-produced using different techniques and subcultured in pots with sorghum sudangrass as the host plant for 3 years. Experimental soil samples were collected from natural grassland. Five different AMF inocula were used in triplicate as treatments. After 70 days of growth, red pepper plants were harvested and plant dry weight, plant nutrient content, mycorrhizal colonization, AMF spore count, and soil glomalin content were determined. AMF-treated plants displayed higher dry weight than controls, with only fruit dry weight being significantly different. Similarly, significant differences in phosphorous and potassium contents of the above-ground plant parts were observed between mycorrhizal and control treatments. In addition, soil GRSP content was significantly higher in plants inoculated with Rhizophagus sp. and Gigaspora margarita. The increased plant growth and GRSP content suggest that AMF can be maintained for 3 years without losing their efficiency if subcultured regularly with different symbiotic host plants.
Venkatesan, K.,Selvakumar, G.,Rajan, C. Christober Asir The Korean Institute of Electrical Engineers 2014 Journal of Electrical Engineering & Technology Vol.9 No.2
This paper presents a new approach to solve the multi area unit commitment problem (MAUCP) using an evolutionary programming based particle swarm optimization (EPPSO) method. The objective of this paper is to determine the optimal or near optimal commitment schedule for generating units located in multiple areas that are interconnected via tie lines. The evolutionary programming based particle swarm optimization method is used to solve multi area unit commitment problem, allocated generation for each area and find the operating cost of generation for each hour. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. Case study of four areas with different load pattern each containing 7 units (NTPS) and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the operating cost using evolutionary programming-based particle swarm optimization method with conventional dynamic programming (DP), evolutionary programming (EP), and particle swarm optimization (PSO) method. Experimental results show that the application of this evolutionary programming based particle swarm optimization method has the potential to solve multi area unit commitment problem with lesser computation time.
Google Play Malware Detection based on Search Rank Fraud Approach
Fareena N,Yogesh C,Selvakumar K,Sai Ramesh L 한국인터넷정보학회 2022 KSII Transactions on Internet and Information Syst Vol.16 No.11
Google Play is one of the largest Android phone app markets and it contains both free and paid apps. It provides a variety of categories for every target user who has different needs and purposes. The customer's rate every product based on their experience of apps and based on the average rating the position of an app in these arch varies. Fraudulent behaviors emerge in those apps which incorporate search rank maltreatment and malware proliferation. To distinguish the fraudulent behavior, a novel framework is structured that finds and uses follows left behind by fraudsters, to identify both malware and applications exposed to the search rank fraud method. This strategy correlates survey exercises and remarkably joins identified review relations with semantic and behavioral signals produced from Google Play application information, to distinguish dubious applications. The proposed model accomplishes 90% precision in grouping gathered informational indexes of malware, fakes, and authentic apps. It finds many fraudulent applications that right now avoid Google Bouncers recognition technology. It also helped the discovery of fake reviews using the reviewer relationship amount of reviews which are forced as positive reviews for each reviewed Google play the android app.
K. Venkatesan,G. Selvakumar,C. Christober Asir Rajan 대한전기학회 2014 Journal of Electrical Engineering & Technology Vol.9 No.2
This paper presents a new approach to solve the multi area unit commitment problem (MAUCP) using an evolutionary programming based particle swarm optimization (EPPSO) method. The objective of this paper is to determine the optimal or near optimal commitment schedule for generating units located in multiple areas that are interconnected via tie lines. The evolutionary programming based particle swarm optimization method is used to solve multi area unit commitment problem, allocated generation for each area and find the operating cost of generation for each hour. Joint operation of generation resources can result in significant operational cost savings. Power transfer between the areas through the tie lines depends upon the operating cost of generation at each hour and tie line transfer limits. Case study of four areas with different load pattern each containing 7 units (NTPS) and 26 units connected via tie lines have been taken for analysis. Numerical results showed comparing the operating cost using evolutionary programming-based particle swarm optimization method with conventional dynamic programming (DP), evolutionary programming (EP), and particle swarm optimization (PSO) method. Experimental results show that the application of this evolutionary programming based particle swarm optimization method has the potential to solve multi area unit commitment problem with lesser computation time.