Informatics Publishing Limited

K. S. Neelukumari ¹, A. Pavithra ¹, N. Saranya ¹, S. Vanitha ¹

Affiliations
1 P. A. College of Engineering and Technology, Pollachi-2, IN

Abstract

Test vector compression has been an active area of research, yielding a wide variety of techniques. A test pattern compression scheme is proposed in order to reduce test data volume and application time. The proposed scheme finds a set of compressed test vectors using the Viterbi algorithm instead of solving linear equations. By assigning a cost function to the branch metric of the Viterbi algorithm, an optimal compressed vector is selected among the possible solution set. This feature enables high flexibility to combine various test requirements such as low-power compression and/or improving capability to repeat test patterns. The proposed on chip decompressor follows the structure of Viterbi encoders which require only one input channel. Experimental results compared with the dictionary algorithm compression. Dictionary based compression techniques are also popular in embedded systems domain. Since they provide a dual advantage of good compression efficiency as well as fast decompression mechanism. Viterbi algorithm provides better compression ratio compared to dictionary algorithm.

Keywords

Test Data Compression, Viterbi, Dictionary, Compression Efficiency.

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A. Pavithra ¹, S. Dhanaraj ²

Affiliations
1 Department of Computer Science, Sree Saraswathi Thyagaraja College, Pollachi, IN
2 Department of Information Technology, Sree Saraswathi Thyagaraja College, Pollachi, IN

Abstract

Data mining practices expert procedures and methods to identify the tendencies and profiles concealed in data. Mining is an iterative process in a sequence. Different sources of data are stored in different databases. The mining depends on databases. This research is for various association rule mining applications of different databases. There are different databases in practice like large database, distributed database, medical database, relational database, spatial database. The process of mining these databases are carried out by different data mining techniques. For making decisions, association rule is most essential. They are associated with association rule mining techniques.

Keywords

Data Mining, Association Rule Mining, Spatial Data Mining, RDBMS, Medical Database, Large Database, Distributed Database.

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J. Praveen ¹, P. O. Nameer ², Ashish Jha ³, Anish Aravind ⁴, K. G. Dilip ⁵, Dipu Karuthedathu ⁶, George Tom ¹, Hari Mavelikara ⁷, Harikumar Mannar ⁸, Jafer Palot ⁹, Jaichand Johnson ¹⁰, R. Jishnu ¹¹, K. Maxim Rodrigues ¹², P. M. Mujeeb ¹³, L. Namassivayan ¹⁴, Naveelal Payyeri ¹³, P. P. Nesrudheen ⁶, S. Prasanth Narayanan ⁸, S. S. Prasanth ⁶, M. C. Prashantha Krishna ¹², E. S. Praveen ¹⁵, Praveen Velayudhan ¹⁴, Premchand Reghuvaran ⁵, Raju Kidoor ¹², R. L. Rathish ¹⁶, R. Roshnath ¹⁷, C. Sashikumar ⁹, Satyan Meppayur ⁹, A. K. Sivakumar ¹⁰, A. K. Sreedevi ⁸, B. Sreekumar ⁸, E. R. Sreekumar ¹⁸, P. B. Sumesh ¹⁹, R. Venugopal ¹⁴, Vinod Venugopal ²⁰, C. K. Vishnudas ²¹, Vishnupriyan Kartha ⁵, Vivek Puliyeri ⁶, Suhel Quader ²², Abinand Reddy ²², Abdul Raheem Puthiyeri ⁹, K. Abdul Riyas ⁹, R. S. Abhijith ⁸, Abhijith Surendran ⁸, Abhin M. Sunil ¹⁸, Abhinand Chandran ¹³, C. Abhirami ¹⁸, Abhirami M. Jayakumar ¹⁸, Abhishek Sebastian Peter ¹⁰, N. V. Afreed Muhammed ²², Afthab Faisal Katakath ¹⁸, P. Ajai ⁸, Aju K. Raju ⁷, P. M. Akhil ¹⁴, U. S. Akhil ¹⁶, U. S. Amal ²³, Anamika Menon ²⁴, Anas Ibinu Ansari ¹⁵, K. S. Aneesh ¹⁰, S. Aneesh ⁷, C. Anjana Hari ¹⁸, R. Anjitha ¹², P. N. Anoop Raj ²⁵, Anu John ¹¹, Anuradha Varma ⁵, S. S. Anushreedha ¹⁰, C. K. Aravind ⁹, Arjun Ramachandran ¹⁸, B. Arun ⁶, Arun George ¹⁵, Arun P. Gopi ¹⁹, Arun Varghese ⁵, Arya Vinod ¹⁴, Ashley Shaji ¹⁰, V. M. Ashok Raj ⁶, Ashwin Viswanathan ²², Aslam Mohammed ⁹, A. Aswin ¹⁸, K. S. Aswin ¹⁸, A. Azhar Ali ¹⁸, P. B. Balaji ²⁶, M. Bibin Paul ¹⁶, J. Chaithra Shree ²⁶, Chandrasekaran Venkatraman ¹, K. Charutha ¹², Clareena T. Jose ¹⁸, Clince P. Jose ⁹, Dalip Singh ¹⁸, Devika Sanghamithra ¹⁸, Digvijay Singh Sikarwar ⁵, Divin Murukesh ⁶, V. Divin ¹, Fauzia Arief ⁵, Jaydev Mandal ²², P. J. Sarlin ¹⁰, A. Adil Nafar ⁶, K. H. Amitha Bachan ²⁷, V. Rejitha ⁷, R. S. Vishnu Dev ¹⁶, B. Elias Rowther ¹⁰, Firosh Raja ¹⁸, Geetha Iyer ¹, Ginu George ⁵, T. U. Gireesan ⁸, P. K. Girish Mohan ⁹, Glen Preetesh Dsouza ¹², G. Govind ¹⁰, P. Greeshma ¹⁵, P. M. Hari Prasad ⁸, T. V. Hariharan ⁹, A. Harith ¹⁰, C. Harith ¹², B. Hemanth ¹⁰, Ijaas Mohamed ⁵, J. Patrick David ⁵, P. K. Jain ²², P. Jameela ¹⁵, G. Jayakrishnan ⁸, K. Jishnu ⁹, M. O. Jismi ¹⁸, Jithin Johnson ⁵, C. Joel Soniya ¹⁰, Jose Rani Babu ¹⁸, Joseph Roy ¹⁰, Jyothish Nelson ⁸, M. Jyothi Krishnan ¹⁸, K. Pranav Bhandary ¹², K. M. Jamaludheen ⁵, Kavingal Ravi ¹⁴, Karthik Thrikkadeeri ¹⁴, Kausthubh K. Nair ⁵, B. S. Kiran ²¹, Kiran S. Kumar ¹⁰, D. Kishore Raj ¹⁰, Kishore Kumar Panaganti ²², M. Krishna Moorthy ¹⁴, R. Krishna Murthy ¹, M. R. Krishnanunni ¹⁸, Latha Prabhakaran ⁵, K. K. Lathika ⁶, Libin Abraham ⁷, G. Hari Narayanan ⁸, Madhumita Panigrahi ²⁸, S. Manav ¹⁴, Manoj Karingamadathil ¹⁵, T. R. Manoj ²⁶, Manu Thomas ¹⁰, P. P. Manuel ¹⁵, Mebin George Varghese ⁸, P. Megha Chandran ¹², M. Mohammad Sulaiman ¹⁴, Mohammed Ashif Madathil ⁶, V. K. Mohammed Hirash ⁹, K. Mohammed Ramees ¹⁰, M. Sadique Thirunnavaya ⁶, A. P. Muhammed Niyas ¹⁰, C. T. Muhasin ⁶, Mukundan Kizhakkemadham ⁵, Naseerudheen Abdul Azeez ¹⁴, P. V. Nikhil ¹⁰, C. Niranjana ²⁹, Nisha Mundekad ³⁰, Nithin Mohan ¹⁰, A. Pavithra ⁵, Poornima Viswanathan ⁹, P. Pramod ²⁸, G. Prakash ²⁶, S. Prasath ²⁶, Prasoon Prakash ¹⁰, N. Preethi ¹⁴, Rahul Rajeevan ²², M. Rajaguru ¹⁴, V. Rajarajan ¹, Raju Sankaran ¹⁵, K. Ratheesh ¹⁰, Rayan Pradeep Crasta ¹², Remya Mohan ¹⁴, Renju ¹⁹, Robin C. Koshy ⁷, Rohan Rai ¹², Roshin Tom ²², Sachin Chandran ⁹, M. V. Sachinkrishna ¹⁸, M. V. Saeed Anvar Ali ¹⁴, Sajitha Siril ¹⁸, D. D. Samarth Bharadwaj ²², Samuel George ²², Sancia Morris ¹⁰, Sandeep Augustine ⁵, Sandeep K. Das ⁵, Sandie Morris ¹⁰, P. R. Sandra ¹⁵, T. K. Sanuraj ¹², Saurabh Sawant ¹, Savio Morris ¹⁰, K. Selvaganesh ²⁰, K. Shahil ²², N. N. Shahina ¹⁸, Shahul Valasy ⁹, P. K. Siji ¹⁵, Siju Joseph ⁷, R. Sivashankar ¹⁵, Siyad A. Karim ⁷, Sreehari K. Mohan ¹⁸, Sreehari M. Pillai ¹¹, M. Sri Sowmiya ⁹, K. T. Srinila ⁶, K. S. Subin ¹⁵, V. G. Sujith ¹⁰, Suryamol Sukumaran ¹⁰, M. S. Syamili ¹⁸, Tarun Menon ¹⁴, Tejas Praveen ¹, S. A. Thilak ⁵, Tony Antony ³¹, U. R Ullas ³², Vinod Ooralath Sivaji ⁷, Vishnu Narayanan ¹⁰, M. Vishnu Sreejith ⁹, A. Vivek Chandran ¹⁵, Vivek Sudhakaran ¹⁴, R. Vridhi ¹⁵, Wahiba Irshad Humam ¹⁸, Yadukrishna J. Uchummal ²², M. A. Yathumon ⁹

Affiliations
1 KeralaBirder, Ambadi, Kunnathurmedu, Palakkad 678 013, India, IN
2 College of Climate Change and Environmental Science, Kerala Agricultural University, Thrissur 680 656, India; Department of Wildlife Science, College of Forestry, Kerala Agricultural University, Thrissur 680 656, India, IN
3 College of Climate Change and Environmental Science, Kerala Agricultural University, Thrissur 680 656, India, IN
4 Cochin Natural History Society, Revathi Bhavan, Edathala P. O., Aluva 683 561, India; Kottayam Nature Society, Sri Nilayam, Near Union Club, Kottayam 686 001, India, IN
5 Cochin Natural History Society, Revathi Bhavan, Edathala P. O., Aluva 683 561, India, IN
6 Malappuram Birders, Tirur, Malappuram 676 101, India, IN
7 Pathanamthitta Birders, Pathanamthitta 689 645, India, IN
8 Kottayam Nature Society, Sri Nilayam, Near Union Club, Kottayam 686 001, India, IN
9 Malabar Natural History Society, Susheela Mandir, B.G. Road, Nadakkavu P.O., Kozhikode, 673 011, India, IN
10 WWF-India, CO Madhavan Road, Ayyankali Nagar, Kunnukuzhy, Thiruvananthapuram 695 035, India, IN
11 Kollam Birding Battalion, Kollam 691 010, India, IN
12 Kasaragod Birders, Kasaragod 671 121, India, IN
13 Malabar Natural History Society, Susheela Mandir, B.G. Road, Nadakkavu P.O., Kozhikode, 673 011, India; Calicut Birders Club, Bellevue Dental Muthappan Complex, Patteri, Kozhikode 673 016, India, IN
14 Natural History Society of Palakkad, Palakkad 678 001, India, IN
15 Kole Birders Collective, Thrissur 680 555, India, IN
16 Kerala Veterinary and Animal Sciences University, Pookode, Wayanad 673 576, India, IN
17 Malabar Awareness and Rescue Centre For Wildlife, Chettipedika, Kannur 670 004, India, IN
18 Department of Wildlife Science, College of Forestry, Kerala Agricultural University, Thrissur 680 656, India, IN
19 Birders Ezhupunna, Puthiyaparambil (H), Ezhupunna South P. O, Cherthala. Alappuzha 688 537, India, IN
20 Young Birders Club, Palakkad 678 001, India, IN
21 Hume Centre for Ecology and Wildlife Biology, 4th Cross Rd, Subhash Nagar, Kalpetta, Wayanad 673 121, India, IN
22 Nature Conservation Foundation, 1311, ‘Amritha’, 12th Main, Vijayanagar 1st Stage, Mysuru 570 002, India, IN
23 Kollam Birding Battalion, Kollam 691 010, India; Department of Wildlife Science, College of Forestry, Kerala Agricultural University, Thrissur 680 656, India, IN
24 WWF-India, CO Madhavan Road, Ayyankali Nagar, Kunnukuzhy, Thiruvananthapuram 695 035, India; Department of Wildlife Science, College of Forestry, Kerala Agricultural University, Thrissur 680 656, India, IN
25 Natural History Society of Palakkad, Palakkad 678 001, India; Sálim Ali Centre for Ornithology and Natural History, Anaikatty (Post), Coimbatore 641 108, India, IN
26 Sálim Ali Nature Forum, Coimbatore 641 108, India, IN
27 Western Ghats Hornbill Foundation, Extension Centre, MES Asmabi College, P. Vemballur, Thrissur 680 691, India, IN
28 Sálim Ali Nature Forum, Coimbatore 641 108, India; Sálim Ali Centre for Ornithology and Natural History, Anaikatty (Post), Coimbatore 641 108, India, IN
29 Natural History Society of Palakkad, Palakkad 678 001, India; Department of Wildlife Science, College of Forestry, Kerala Agricultural University, Thrissur 680 656, India, IN
30 Cochin Natural History Society, Revathi Bhavan, Edathala P. O., Aluva 683 561, India; Malappuram Birders, Tirur, Malappuram 676 101, India, IN
31 Pathanamthitta Birders, Pathanamthitta 689 645, India; Kottayam Nature Society, Sri Nilayam, Near Union Club, Kottayam 686 001, India, IN
32 WWF-India, CO Madhavan Road, Ayyankali Nagar, Kunnukuzhy, Thiruvananthapuram 695 035, India; Kole Birders Collective, Thrissur 680 555, India, IN

Abstract

Citizen-science driven exercises (e.g. bird surveys) and online platforms (e.g. eBird) provide voluminous data on bird occurrence. However, the semi-structured nature of their data collection makes it difficult to compare bird distribution across space and time. Bird atlases are based on standardized surveys and des­cribe the distribution of bird species over a predefined region and have fewer biases, and thus are better suited for use in research. The recently concluded Kerala Bird Atlas (henceforth KBA) is Asia’s largest bird atlas in terms of geographical extent, sampling effort and species coverage. The entire state of Kerala was systematically surveyed twice a year during 2015–20 and over 0.3 million records of 380 species from 25,000 checklists were aggregated. The dataset was filtered and various metrics were estimated. A total of 915 cells were laid out for systematic surveys, of which 888 were surveyed in either or both the seasons – dry season (January–March) and wet season (July–September); 27 cells could not be surveyed in either of the seasons due to logistical constraints. However, this variation in sampling effort had a minimal effect on survey completeness. The slope of the species accumulation curve suggested near-complete species sampling in over 70% of the cells. After eliminating nocturnal and pelagic species, data from 361 species were analysed. Species count was higher in the dry season than in the wet season. Species richness (count) and evenness were higher in the northern and central districts than in the southern districts. High elevation regions of the southern Western Ghats were the largest contiguous areas lacking sufficient sampling. We found that most of the endemics were concentrated in the Western Ghats, but threatened species were as likely to occur along the coasts as in the Ghats. The KBA dataset is a valuable resource for testing various ecological hypotheses and suggesting science-backed conservation measures. KBA model could be replicated for similar atlases in other states or biogeographic regions of India

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