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Natural language processing (NLP) comprises of various techniques addressing language text. Few to mention are Part of Speech (POS) tagger, Chunker, Morphological Analyzer, Spell-Checkers, Grammar Checkers, Machine translator, Transliterator etc. POS tagging is the basic building block in language processing which assigns part of Speech (POS) tag which is a peculiar label assigned to each and every token (word) in a text corpus to indicate the part of speech such as verb, pronoun, noun, adjective etc. POS tagging is useful and significant in pre-processing phase especially in the area of information retrieval, text to speech processing, word sense disambiguation and information processing. The methods of POS tagging are classified as rule-based POS tagging, transformation-based tagging, and stochastic tagging. Recent research reports various methods and approaches like Markov Model (MM), SVM (Support Vector Machine), ME (Maximum Entropy) etc used for POS tagging tested on several Indic languages like Hindi, Bengali, Manipuri, Assamese, Telugu, Kannada, Malayalam, Tamil, Punjabi. Since the performance of POS taggers is specific to context and language, there is a pressing need to carry out exhaustive survey. . This paper highlights a comprehensive study on two indic languages i.e. Hindi and Bengali. POS taggers with various approaches along with performance are reported.

Ambiguity, Natural language processing (NLP), Named Entity Recognition (NER), Part of Speech(POS), Tagger

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Floyd Avina Fernandes, Kavita Asnani, "Parts of Speech Tagging for Indic Languages: A Survey," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.729-736, 2019.

Data science and machine learning are the key technologies when it comes to the processes and products with automatic learning and optimization to be used in the automotive industry of the future. This article defines the terms “data science” (also referred to as “data analytics”) and “machine learning” and how they are related. In addition, it defines the term “optimizing analytics” and illustrates the role of automatic optimization as a key technology in combination with data analytics. It also uses examples to explain the way that these technologies are currently being used in the automotive industry on the basis of the major sub-processes in the automotive value chain (development, procurement; logistics, production, marketing, sales and after-sales, connected customer). Since the industry is just starting to explore the broad range of potential uses for these technologies, visionary application examples are used to illustrate the revolutionary possibilities that they offer.

Data science, big data, machine learning, automatic optimization, optimizing analytics, automotive industry

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Mahesh Patidar, V. B. Gupta, Seema Patidar, "Optimizing Analytics of Artificial Intelligence and Data Science," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.736-740, 2019.

For the past few years reducing road accidents and controlling traffic by limiting the speed of vehicles has gained more importance. Most of the methods so far used are Doppler radar, IR or Laser sensor based speed calculation. All of them are very expensive and also their accuracy is not quite satisfactory. In this paper, a Camera-based Speed Calculation System(CSCS) is employed, CSCS uses image processing techniques and can process video stream in online or offline mode, CSCS has the ability to determine the speed with good accuracy but at relatively low cost. In this study, the acquired video is pre-processed to remove the redundant information, then foreground information is extracted from the video. After this noise and shadow are removed from the video. Moving vehicles are localized and centroid for them are found out. Region Of Interest(ROI) box was constructed for each lane. Speed is calculated with the help of Distance Speed Time formula by counting the number of frames taken by the vehicle to pass through the ROI box. A database in the form of the log file is created which contains vehicle speed, location(vehicle has passed from which CSCS system), time at which this speed was recorded and whether it has crossed the speed limit or not. CSCS was tested and has achieved satisfactory performance with an accuracy of 95.44%-99.64%.

Camera-based Speed Calculation System(CSCS), Background subtraction(BS), Localization, Centroid, Region of interest(ROI), Database, Automatic Number Plate Recognition(ANPR) system

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A. Raj, D. Dubey, A. Mishra, N. Chopda, N.M. Borkar, V.S. Lande, B.A. Neole, "Semi-Geometrical approach to estimate the speed of the vehicle through a surveillance video stream," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.741-748, 2019.

Data Mining is a way to extract information from large amount of data. It brings out one conclusion by applying its efficient techniques. In today’s world, it has helped many of the domains and growing its root by enhancing in its own way. In various data repositories, large medical datasets are available which are used in real world applications. Information is been generated by using various Data Mining techniques. Classification technique separates the information so as to generate useful content from it. It also helps in medical field to detect diseases such as diabetes which has affected various people from different countries. Insulin is main concept while taking into consideration the term ‘Diabetes’. Insulin acts as glucose for energy. It is a Gateway to body cells and controls glucose level in our body. Diabetes is a disease in which level of glucose in blood increases. To make it easy and recover from most early stages, prediction is necessary. It is been done with the help of data mining. This study is significant of predicting diabetes and helping medical industry to grow.

Health, Decision Tree, Diabetes, Prediction

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Data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR)
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Suhasini Vijaykumar, Manjiri Moghe, "Diabetes Prediction using Data Mining," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.749-753, 2019.

The glorious history of the dynasties is recorded within the variety of inscriptions/epigraphic records. The department of ancient history and Archaeology is exhuming new inscriptions and need for the automatic explanation of such inscriptions is increasing, that minimizes the work or eliminates the necessity of partner epigrapher in translating antiquated epigraphs. The ancient inscription on the rock, metal plates, cloth and other writing materials are the main sources to recreate the culture and history of Karnataka in India. The offline handwritten text recognition is one of the most challenging tasks in document image analysis; our aim is to recreate the cultural importance of the Kannada Language writing tradition through the historical degraded manuscripts. In the present digital era, we need to protect and digitize the resources of our Indian culture and heritage by digitizing those manuscripts which are losing its status; the degraded manuscripts are influenced by weather condition. In this paper, we have attempted to identify and recognise the historical Kannada handwritten scripts of various dynasties; namely, Vijayanagara dynasty (1460 AD), Mysore Wodeyar dynasty (1936 AD), Vijayanagara dynasty (1400 AD) and Hoysala dynasty (1340 AD) by using the improved seam carving text line segmentation method with GLCM features. The average classification accuracy for different dynasties is computed. The LDA classifier has yielded 86.5%, K-NN classifier has yielded 85.3% and SVM classifier has 85.6%. Based on the experimentation, the LDA classifier has recorded good classification performance comparatively K-NN and SVM classifiers for historical Kannada handwritten scripts.

Restoration, Seam carving, Line segmentation, Kannada, LDA, K-NN, SVM, Recognition, GLCM, handwritten script, historical documents, document image analysis

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Parashuram Bannigidad, Chandrashekar Gudada, "Identification and Classification of Historical Kannada Handwritten Scripts based on their Age-Type using Line Segmentation with GLCM features," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.754-763, 2019.

This work deals with performance analysis of Windows Operating System using VMware. The communication protocol RDP is implemented on different Windows Operating System and are compared based on various parameters. The first part consists of the technical background of RDP implementation. The second part is based on the methodologies designed for the comparison of the operating systems. The features of RDP Protocol are taken into consideration to design the methodologies and determining the results. Based on the user requirement, the methodologies are divided into low and high user requirement. A number of applications are used to analyze the performance of the operating systems in RDP Protocol. The tests vary from server loading performance to monitoring and mapping of data transmission time, bandwidth and response time of the different Windows Operating System. Windows X is used as the host for the other operating system and characteristics of RDP Protocol are analyzed for other Windows Operating System.

RDP protocol, Windows Operating System, virtualization, memory consumed bandwidth

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Mehnaz Nazneen Baig, Pragya Ram Nanwani, Nishi Yadav, "Performance Analysis of Different Operating System for Desktop Virtualization in Vmware Using Rdp Protocol," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.764-768, 2019.

PBL Problem-Based Learning (PBL) may be a method during which advanced real-world issues square measure is used as the vehicle to market student learning of ideas and principles as critical direct presentation of facts and ideas. In addition to the course content, PBL helps to market the event of essential thinking skills, problem-solving skills, and communication skills. It also can offer opportunities for operating in teams, finding and evaluating analysis materials, and life-long learning. PBL is powerfully fundamented in well outlined principles. On the opposite hand, several academics and students implement PBL, while not the mandatory theoretical and sensible base for the academic changes and acceptable technology resource support, creating it less economical. In short: PBL is all concerning you, your tutors are very approachable and you learn along in an exceedingly dynamic manner, serving to kind you into associate degree assertive skilled. This paper gift concerning PBL Guide that promote technological support to associate degree array of actions into the principles and characteristics originated from learning theories concerning PBL.

Problem-Based Learning ; Virtual Learning Environment ; Moodle ; Ubiquitous learning Environment ;PBL Guide ; E- Learning

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Safad Ismail, "Using a Virtual Learning Environment for Problem Based Learning (P.B.L)," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.769-773, 2019.

The demand of Machine Translation (MT) is increasing due to the increased rate of exchange of information around the globe. Considering Internet as the main channel of information sharing, the source of information is not confined to a specific geographical location and a specific language. MT is the way of translating from one language to another with the help of computer system. The text of source language fed to the system and the system translates it to the target language. Many approaches and tools for those approaches have been developed to achieve better performance in translation. In this paper an n-gram based statistical approach is discussed.

Machine Translation, Marie, SMT,n-gram

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Abdul Hannan, Shikhar Kr. Sarma, Zakir Hussain, "Marie: A Statistical Approach to Build a Machine Translation System for English Assamese Language Pair," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.774-779, 2019.

Nowadays, most of the accidents were related to driver fatigue, drowsiness and driver inattention caused by various distractions inside and outside the vehicle. Falling asleep while driving, is a major cause of road accidents. Car accidents associated with driver fatigue are more likely to be serious, leading to serious injuries and deaths. In this paper a vision-based driver fatigue detection system is proposed in which the system will directly give an indication of drowsiness to prevent accidents. The system tracks human eye and eyelid behavior, looking for the duration of blinks for detecting the drowsiness.

Driver Fatigue Detection, Face Detection, Eye Detection, SURF, SVM Classifier, Viola-Jones Face Detection

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Radhika Raj, Betsy Chacko, "Driver Fatigue Detection Using Image Processing," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.780-782, 2019.

Wireless sensor network (WSN) suffers the problem of battery consumption, which cannot be replaced in remote regions. Energy harvesting is a prominent technique for the above problem. Energy can be harvested from the external environment like solar energy, wind energy, thermal energy, RF energy, piezoelectric energy, etc. to recharge the batteries which subsequently increases the life of the network. These conventional sources of energy provide energy on a macro scale, but in relation to WSN they need to be carried out on a smaller scale. Energy harvesters may or may not provide the continuous energy to the networks. This area needs to be explored while keeping in mind issues and challenges to meet the requirements of the network. This paper discusses the limitations of WSN, energy harvesting techniques and the issues and challenges in implementing energy harvesting in WSN. Environment, design, size, reliability, performance, resource sharing, hybrid energy harvesting, battery issues, low power and security are some of the major issues and challenges in energy harvesting based WSN.

Wireless Sensor Network, Issues and Challenges, Limitations, Energy Harvesting, Solar harvesting, RF energy harvesting

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Meenakshi Sansoy, Avtar Singh Buttar, Rakesh Goyal, "Issues and Challenges in Energy Harvested based Wireless Sensor Network," International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.783-786, 2019.