Miracle-dz/UniFAR-FTUs huggingface dataset:
Fingerprint-based Difference-Means Algorithm for Indoor Positioning in Wi-Fi Environment

 Abstract: In this paper, we propose the fingerprint-based DIFFERENCE-MEANS algorithm (FBDMA) to improve the processing speed and the positioning accuracy in an indoor wireless-fidelity (Wi-Fi) environment. We have applied three design philosophies in the proposed algorithm: the consideration of volume of reference point (RP) in building up signals map, the increase of positioning accuracy by minimum Wi-Fi AP usage, and the increase of positioning accuracy in real-time processing. The architecture of the proposed algorithm consists of two steps: the fingerprint learning step and the indoor positioning step. The main performance metrics in the proposed algorithm are defined as the ratio of successful positioning, the error distances, and the measuring time. The results of the proposed algorithm are summarized as follows: 1) The average ratio of successful positioning in all 24 RPs in the proposed positioning algorithm is measured to 95.8%. This is higher than the 92.7% accuracy achieved by the fingerprint-based algorithm (FBA) and the 80.2% by the fingerprint-based Gaussian-distribution algorithm (FBGA). 2) The average distance of measured errors of the proposed FBDMA is 0.95m; it is less than FBA’s 1.52m and 1.63m of FBGA. 3) The average measuring time of the proposed algorithm is reduced by over 52.3% when compared with FBA and FBGA. In the future, we will upgrade the proposed algorithm that estimates the user trajectory moving continuously in the RPs of a more extended indoor environment, based on this paper, and confirm the predefined performance metrics.
Multicasting Routing Protocols in Wireless Ad hoc Network – A Comprehensive Survey

— Wireless ad hoc networks and devices are becoming widespread as they support enormous applications anywhere and anytime. In wireless mobile communications, the mobile node is the only one hop away from base stations. The type of Mobile Ad Hoc Network (MANET) has no constant structure or fundamental supervision. A network is required to guarantee a set of measurable pre specified service attributes to applications in terms of end-to-end performance using certain Quality of Service (QoS) parameters such as delay, bandwidth, and jitter. This paper reviews the various kinds of multicasting types and routing protocols in MANET.
Mini Sacharias Part Time Ph

www.worldwidejournals. com 3 Dr. A Celine Rani Professor, Department Of Political Science And Development Administration, Gandhigram Rural Institute, Tamil Nadu, India. Sl. No. Type of Family Frequency Percent 1 2 3 Nuclear Joint Extended 352 306 22 51.8 45.0 3.2 Total 680 100 Sl. No. Place of Residence Frequency Percent 1 2 Rural Urban 574 106 84.4 15.6
Sentiment Analysis Based on Dictionary Approach

: Sentiment analysis has become upcoming topic in recent years, and sentiment dictionaries are essential for research in this field. Consumers regularly face the trade-off in purchase decisions so nowadays if one wants to buy a consumer product one prefer user reviews and discussion in public forums on web about the product. Many consumers use reviews posted by other consumers before making their purchase decisions. People have a tendency to express their opinion on various entities. As a result opinion mining has gained importance. Sentiment Analysis deals with evaluating whether this expressed opinion about the entity has a positive or a negative orientation. Consumers need to decide what subset of available information to use. Graphical analysis is a better option for this decision as they provide a quick indication of a review. However there are cases where such graphical representation are not available or detailed enough. Sentiment analysis text analysis techniques that automatically detect the polarity of text can help in these situations with more refined analysis.
Design and Implementation of Symmetric Multilevel Inverter

In this paper, an advanced configuration for a symmetric multilevel voltage source inverter is proposed. The proposed inverter is able to generate the nine levels using a lower number of circuit devices, including power semiconductor switches. Moreover, the reduced amount of on-state switches in the suggested configuration decreases voltage drops. Power losses are diminished. The given simulation results confirm the feasibility of the proposed configuration. To approve the practicability of the proposed inverter, a prototype of the proposed topology has been implemented. Finally, simulation results show that the obtained results are in good agreement. As a result, the total cost is considerably reduced, and the control scheme gets simpler. Keyword: Higher efficiency; Multilevel voltage source inverter (MVSI); power losses; reduction of circuit components; symmetric inverter; voltage drop;
Solving the Graph Partitioning based on Cuckoo Optimization Algorithm (COA)

: In this paper a new efficient approach to solving the balanced connected partitioning is presented. The graph partitioning problem has been used in many areas of computer science like LSI design; electrical power networks (EPNs) and ect. The problem aims to obtaining sub graphs of a graph which include balance connected vertices. The proposed solution is based on Cuckoo Optimization Algorithm (COA) that is a novel evolutionary optimization algorithm. This method is inspired by the life structure of a bird family which is called cuckoo. To prove the performance of this approach two hardness instances are used.
A comparative study on gender difference in attemted suicide on basis of personality traits, emotional maturit,and depression

The purpose of the study is to explore gender difference in attempted suicide on basis of personality traits, emotional maturity and depression. The sample consisted of two groups where number of participants are ( n=20) in each group. The target groups were males and females who had attempted suicide at least once. The mean age for males ( x= 24.45) and the mean age for female ( x= 24.35). Both the personality questionnaire ( EPQ-R), Emotional maturity scale ( EMS), and Becks depression inventory ( BDI).
Remote Sensing Monitoring Shows that Climate Change has a Significant Impact on Vegetation Ecosystem in Central Asia

The arid regions of Central Asia are one of the most representative arid regions in the northern mid-latitudes, which includes Kazakhstan, Uzbekistan, Kyrgyzstan, Turkmenistan, Tajikistan and Xinjiang in China, with a total area of 6 million km2, more than 80% of the worldâ€™s temperate deserts are located and has formed a unique temperate desert landscape pattern. Studies have shown that in the past three decades, the temperature in Central Asia rises by 0. 4Â°C per decade, which is significantly higher than the average of the northern hemisphere and surrounding areas (0.3Â°C / 10a). During the end 30 years in the late 20th century, severe drought occurred in the northwestern region of Central Asia, while precipitation in Xinjiang in the eastern part of Central Asia increased significantly. The precipitation in this region showed strong spatial heterogeneity and significant chronological fluctuations.
An FPGA-based implementation of a vector coprocessor for control applications

The vector coprocessor (VP) is taken as a potential solution for control applications because of its low power consumption and internal feedback network. Due to partial re-programmability and hardware sharing, field programmable gate array (FPGA) offers a novel platform to implement it. Architecture is presented for simultaneous detection of the desired non-overlap n-binary control vectors of a constant length of m-bit with reduced hardware requirement. Finite state machine (FSM) has been investigated for designing the proposed detector. Within a bit stream, which is generated by central processor unit (CPU), it provides a single output or user defined output combinations for desired control vectors. The reduced state table for its FSM implementation is obtained without using state diagram and state reduction techniques. A formula has been developed for calculation of an approximate number of memory elements required for implementation of the proposed detector. One of its application is also conferred to add new devices to any existing digital system or to modify its features. It provides adaptability in three aspects i.e. the length of sequences, the number of sequences and user defined output combinations.
Software Defect Prediction using Boosting Techniques

Identification and removal of software defects is tedious and time consuming for software development. Improperly planned projects could have defects and the time spent to spot and fix them requires more than the code development time. A reverse engineering sub-area is identification of modules necessitating re-engineering, focusing on faulty modules prediction based on existing information sources like documentation and source code. Predicting defective module is essential in maintenance and reuse by simplifying system working with information and reusable parts localization. In software defect prediction, predictive models estimation is based on code attributes to assess software modules containing errors likelihood. In this paper, the classification accuracy of Boosting techniques for software defect prediction based on the KC1 dataset is investigated.
Human Face Recognition and Face Detection using Skin Colour Model

As one of the most successful applications of image analysis and understanding, face recognition has recently gained significant attention, especially during the past several years. Human face recognition play important roles in many applications such as video surveillance and face image database management. In this project, we have worked on face recognition techniques and developed algorithms for them. In face recognition the algorithm used is PCA (principal component analysis) using eigen faces in which we recognize an unknown test image by comparing it with the known training images stored in the database as well as display information of the person detected. This algorithms give different rates of accuracy under different conditions as experimentally observed. In face detection, we have developed an algorithm that can detect human faces from an image. We have taken skin colour as a tool for detection. This technique works well for Indian faces which have a specific complexion varying under certain range. We have taken real life examples and simulated the algorithms in MATLAB successfully.
Comparison of BER Performance & Capacity Analysis of MIMO System with STBC & MRC to improve Link Performance in Fading Environment

MIMO (Multiple-input Multiple-output) systems are used in wireless communications to ensure high reliability, high data-rate & high capacity transmission. STBCs (Space-Time Block Coding) used in MIMO systems for increasing diversity gain. In MIMO system, high-data rates are obtained through Spatial multiplexing which also helps in combatting the effect of multipath fading. For SIMO (Single-input Multiple-output) schemes, MRC receiver is used to handle same information signal over two or more fading channel. In this paper, we investigate the Ergodic Capacity of different MIMO & SIMO systems & comparison of Bit Error Rate performance of un-coded coherent BPSK employing Alamouti STBC as transmit diversity & MRC (Maximal Ratio combining) as receiving diversity in Rayleigh fading channel.
A NOVEL APPROACH FOR PRIVACY PRESERVING PUBLIC AUDITING TO CLOUD DATA STORAGE WITH REGENERATING –CODE BASED APPROACH

Cloud Computing is one of the practices of using a network of remote servers hosted on internet to store, access, and retrieve data from remote machines not from local machines. As the cloud is used mainly for storing the data on remote servers it has various services like PaaS, IaaS, SaaS, DaaS and so on. Here each and every service has its own advantages and limitations due to its hardware and software usage. In this cloud the users who are placing the data in the cloud are known as Data Owners and the user who is accessing that file is known as Data users. As the data is been placed on remote system not on our local machines data integrity plays a very important role for both data owners and data users, these two users need to have audit for the cloud data without retrieving the entire data. The data audit should be commonly applied for both public and private cloud users. Till now there are many audit mechanisms in the cloud servers which were not at all achieved total data integrity as they have failed in some instances. Now a day’s one of the new technique like regenerating codes have gained more popularity due to their low repair bandwidth which has fault tolerance as its inbuilt property. In the existing remote methods for regenerating the coded data they use to stay online all the time and they used to handle auditing. But now there is no need to stay in the online while conducting the data auditing the data stored by owners and users. In this paper, we have designed a novel public auditing scheme for the regenerating-code-based cloud storage. In order to solve or overcome the problem that occur with the failed authenticators at the time of data owner absence, we have introduced a new layer in our proposed model like a proxy, which is a privilege to regenerate the authenticators, into the traditional public auditing system model. Along with this we have proposed a public verifiable authenticator, which is formed by combining a couple of keys and in turn regenerated using a partial keys.As an extension we have also implemented the proposed concept on a live cloud Server like DROPBOX by creating a public account for data storage and data auditing. By conducting various experiments on this proposed new approach we finally came to a conclusion that this proposed cloud approach have more effectiveness and when auditing shared data integrity.
Review Persual in a Crosslanguage Framework

THE world is a fast moving vehicle. In this vehicle there different people belonging to different strata of life. All of them work very hard to live a standard life. People how work so hard spend their money very carefully so before buying any commodity they like to take opinion of various people. The existing system helps to convert the English comment regarding the good they buy into Chinese language which very familiar for the people how stay in that region. But the proposed system helps us to overcome this obstacle by converting the comment regarding the object tor good they require. This required opinion help people to take the right decision about what they want to buy or purchase. The propose system make pos tags for each word of the sentence which make the conversion of the corpus easy and give an accurate result. The word from the original language are added with the pos tags and these words are then compared with sum of word which is obtained by adding the pos tad and word meaning of the translated word. This system results in making the choice of the people easy and also show the percentage of positive, negative or neutral comments about the good they want to purchase. This helps the customer to make a satisfying choice of the good to which there emotions are attached. The sentimental value attached with the product can be analyzed as positive, negative, neutral. It helps to improve the quality of the product and raise it market value .
Modelling of Malaria Risk Factors in the Mpohor District of Ghana using Logistic Regression

This study was aimed at assessing and deriving a predictive model for the relationship between malaria prevalence and malaria causing factors (covariates) in the Mpohor District (which is located in the Western Region of Ghana) by logistic regression. Risk factors such as seasonality (wet or dry), altitude, mining community, proximity of water body, vegetation proximity and clinic proximity were assessed using logistic regression. Collinearity test was performed to avoid information duplicate and multicolinearity by examining the Variance Inflation Factor (VIF) of each covariate. The relationship between malaria and its underlying factors was analysed through stepwise logistic regression where the wald statistics and odds ratio (OR) proved their significance. The results showed that the risk factors such as altitude, seasonality, water body proximity, vegetation proximity and mining community were significant predictors of malaria morbidity in the District . However, it was found that proximity of health facility to community was not a good malaria morbidity predictor. It was recommended among other things, that further research involving more communities in the District and including other known malaria factors be carried out to provide complete and more reliable information that is useful in malaria control. Keywords: Mslaria prevalence, modelling ,odds ratio
Clustering Among Multi-Posture Based Correspondence Compute

— All clustering models have to presuppose several cluster liaisons among the information substance that they are practical on. Comparison connecting a brace of substance can be distinct moreover unequivocally or unreservedly. In this paper, we bring in a narrative multi-posture based correspondence compute and two allied clustering models. The foremost divergence among a customary divergence/correspondence gauge and ours is that the former uses only a single stance, which is the derivation, while the concluding utilizes many diverse postures, which are substance, implicit to not be in the same cluster with the two substances being deliberate. Using multiple postures, additional revealing judgment of comparison could be achieved. Theoretical investigation and experimental cram are conducted to sustain this claim. Two norm functions for manuscript clustering are projected based on this new gauge. We evaluate them with numerous familiar clustering algorithms that use other admired resemblance procedures on various manuscript collections to validate the compensation of our suggestion.
Macroeconomic Indicators and their Impact on Stock Market Performance: (Comparative Study between Pakistan and India)

This study examines the performance of different macroeconomic indicators, their fluctuations between stock indexes in Pakistan Stock Exchange (PSX) and Bombay Stock Exchange (BSX) also comparative study between them. This data is collected on eight specified macroeconomic variables which are: interest rate (IR), inflations (IF), GDP growth, export (EXP), import (IMP), unemployment(UR), (BSX) and (PSX) index. In this research paper, a comparative study has been developed between India and Pakistan with using estimation strategy. Regression analysis and correlations must be used. Data collected from WDI and describe through descriptive statistics. E-views, State software used for analysis. Secondary data must be drawn from Pakistan and India and every economy factors as describing the Indian and Pakistan economy. The empirical results indicate that there is a significant pricing relationship between PSX and BSX 100 indexes and the tested macroeconomic variables; have a significant in explaining the stock market fluctuations in various portfolios. The paper conclusively established that indexes fluctuations are depend upon the change of economic indicators both India and Pakistan. This is helpful for investors, financial management consultants, and policy makers for decision making. Due to limitation of time, data size is kept small. The only data used for analysis is from 1990-2016. Results help the employees and over the counter investor for understanding about macroeconomic indicators rates and stock market pricing fluctuations effected on economy as well as constructions about stock market performance. Additionally, this study adds value to the literature by exploring interest regarding economy conditions.
A 65-nm CMOS Implementation of Efficient PLL Using Self - Healing Prescalar

: Nanometre scale technology introduces several issues in CMOS technology such as variability and leakage current that significantly affect the circuit performance. Devices performances plunge when variability is introduced inadvertently due to process variations causing device mismatching. Leakage currents are the main cause of malfunction of circuits at nano scale; they also degrade accuracy of analog circuits and make digital circuits to malfunction. Phase Lock Loops which are widely used in different application when made at 65nm technology face several functional and performance issues due to leakage currents which alter the states of digital systems and make analog systems less accurate. Calibrated Charge Pump, self healing prescaler self healing VCO are used in Phase locked loop to overcome above issues. In 65nm technology of CMOS with an active area of 0.0182 mm2 PLL is fabricated.
Optimization of k -Nearest Neighbour classifier for dealing with secure encrypted rational data

Data could be facts, numbers, statics or figures accumulated to be followed by several operations to give a certain result. To do that kind of operations data meant to be organized in a way which enables the developer inject several operations to get the desired result. So here it comes the term “Database “ a database is a place meant to organize and sort the data to get easily for it the right data . Several database models has been created to do the work like hierarchical Database model, Network data model, relational database, etc. But one of the most important objectives of IT-Administrators, software Developers, Networks Developers is to maintain these Data secured during the time being transferred, which shouldn’t be revealed or hacked easily. One of the ways was invented to maintain a secured is to encrypt these data before being sent to the server in the database itself [9]. So the Cloud is considered as a computation server which is built, held and supplied by the platform of cloud over the net, what does cloud servers do is that they process and display the same type of competencies plus activity to a normal server but are reached remotely from a cloud service supplier. the main issue behind using cloud is that when the sender uploads the encrypted data, [1, 5, 6], the receiver has decrypt the data before downloading them in order to conduct few operations on the data itself , this kind of decryption may expose the data to be hacked easily in the server itself by other intruders. So this paper proposes to benefit the data mining strategies, by using the k-nearest classification method to help the receiver get the desired data without the need of decrypting data and exposing them to be hacked easily.