Miracle-dz/UniFAR-FTUs huggingface dataset:
Crime and Choice of Residence in Enugu, Southeast Nigeria: A Non-Parametric Analysis

Urban residential patterns are influenced by individual and family choices and preferences of housing locations. The economic, socio-cultural and physical environmental features of urban residential pattern may have some implication for type and rate of occurrence of crime and the reaction of residents to it as regards to where they choose to live. This study investigates the effect crime has on households choice of residential location decision in Enugu. Crime data from Nigerian police record and 400 questionnaires distributed to residents of Enugu were used for the study. This study showed that crime incidence is lowest in the medium density neighbourhoods of Enugu. Crime rate, rent and income are the major factors considered by households while taking decision on residential location in Enugu. The study also showed that awareness of crime in neighbourhood is associated with household choice of place of residence. Crime rates need to be reduced in all neighbourhoods to ensure even development of the urban space. Key words: crime, crime rate, crime occurrence, residential choice
Classification and Regression Tree Method for Forecasting

: Sentiment classification is a special task of text classification whose objective is to classify a text according to the sentimental polarities of opinions it contains e.g., favorable or unfavorable, positive or negative. This is especially a problem for the tweets sentiment analysis. Since the topics in Twitter are very diverse, it is impossible to train a universal classifier for all topics. Twitter is an online social networking service that enables users to send and read short 140-charcters messages called “tweets”. Moreover, compared to product review, Twitter lacks data labeling and a rating mechanism to acquire sentiment labels. The extremely sparse text of tweets also brings down the performance of a sentiment classifier. Twitter, attracts more people to post their feelings and opinions on various topics. The posting of sentiment contents cannot only give an emotional snapshot of the online but also have potential commercial, financial and sociological values. In social media, a Twitter user may have different opinions on different topics using a method called CART (classification and Regression Tree) method. CART analysis is a tree-building technique which is unlike traditional data analysis methods. Other factors which limit CART's general acceptability are the complexity of the analysis and, until recently, the software required to perform CART analysis was difficult to use.
New Cumulative Damage Models for Desynchronization Rate in Cell Populations by using Stochastic Processes as Initial Damage

We characterize the kinetics of two cancer cell lines: IGROV1 (ovarian carcinoma) and MOLT4 (leukemia). By means of flow cytometry, we selected two populations from exponentially growing in vitro cell lines, depending on the cell’s DNA synthesis activity during a preceding labeling period. In this paper based on generalized cumulative damage approach with a stochastic process describing initial damage for a material specimen, a broad class of statistical models for material strength is developed. The new distribution arrived can also be written as the inverse Gaussian-type distribution, which can be interpreted as the first passage of the accumulated damage past a damage threshold, resulting in material failure. For these populations we determined the time course of the cumulative damage of cells in different phases of the cycles, sampling every 9 hr for 63 hr, and connected with an interpreted real-situations.
A Hybrid Image Registration Algorithm and Change Detection for Remote Sensing Images

: Image registration enables the geometric alignment of two images and is widely used in various applications such as remote sensing, medical imaging etc. Due to repetitive patterns and gray level changes in the remote sensing images, feature point based registration method fails to determine every correctly matched points. The proposed method aims to develop a registration algorithm that exploits point structure information of the image. The method includes the combination of daisy descriptor and modified shape context for feature point extraction. To obtain robust matching point pairs, a daisy descriptor is combined with the modified shape context descriptor. Change in the multi temporal input image pair can be effectively detected using Discrete Wavelet Transform.
A Survey on CIBPRE -Cloud Email without Garbage Collection

: Recently, a number of extended Proxy Re-Encryptions (PRE), e.g. Conditional (CPRE), identity-based PRE (IPRE) and Broadcast PRE (BPRE), have been proposed for flexible applications. By incorporating CPRE, IPRE and BPRE, this paper proposes a versatile primitive referred to as conditional identity-based broadcast PRE (CIBPRE) and formalizes its semantic security. CIBPRE allows a sender to encrypt a message to multiple receivers by specifying these receivers’ identities, and the sender can delegate a re-encryption key to a proxy so that he can convert the initial cipher text into a new one to a new set of intended receivers. Moreover, the re-encryption key can be associated with a condition such that only the matching cipher texts can be re-encrypted, which allows the original sender to enforce access control over his remote cipher texts in a fine-grained manner. We propose an efficient CIBPRE scheme with provable security. In the instantiated scheme, the initial cipher text, the re-encrypted cipher text and the re-encryption key are all in constant size, and the parameters to generate a re-encryption key are independent of the original receivers of any initial cipher text. Finally, we show an application of our CIBPRE to secure cloud email system advantageous over existing secure email systems based on Pretty Good Privacy protocol or identity-based encryption. In this we can give the admin an extra provision to approve and reject the users on time of registration. It will bring more security to the system.
Analysis of Induction Motor with die cast rotor

This paper presents the choice between the utilizing a lower cost die cast or fabricated aluminium rotor versus the more expensive copper bar rotor. In industrialized countries Induction motors account for approximately 50% of the overall electricity use. In every field whether it is agricultural sector or the economical sector. The power consumption by a.c motors is quite enough. On an average the cost of energy consumed by the motor is nearly 60-100 times the initial cost of the motor. So the efficiency of motor is of great importance whether during the selection or during the operation. Small increase in motor efficiency can make an overall big difference between the total electricity consumption. Using copper in place of aluminium would result in a motor efficiency higher than that of the original aluminium-based motor. Consequently, the motor can then be scaled down in size, thus decreasing the individual costs of many other steps in the manufacturing process and theoretically lowering motor cost as a whole. This paper discusses the implementation of Die cast rotors, Motor efficiency, and increasing the prospect of the country by using DCR technology.
A New Approach to Detect Clone Attack in WSN

Wireless Sensor Network (WSN) has wide range of applications from defense purpose to general purpose. Because of low cost, small size and compactness of sensors, they can be deployed anywhere for important tasks. Wireless sensor networks are often deployed in the areas where they cannot be monitored easily, and they are left unattended for long time. This makes wireless sensor networks prone to different types of attacks. One of them is Clone attack. In this attack, the adversary captures and compromises legitimate node and makes the clones or replicas. Then adversary inserts those nodes inside the network. Sometimes the sensors carry confidential data with it. If these clone nodes are not quickly detected, an adversary can be further mount a variety of internal attacks. As a result, the various protocols and sensor applications get deteriorated. Several protocols have been proposed in the literature to tackle the crucial problem of clone detection, which are not satisfactory as they have some serious drawbacks. In this paper we propose a new distributed protocol called Neighbor Division Random Walk (ND-RAWL) for Clone attack detection in static WSNs. It is based on claimer-reporter-witness framework. ND-RAWL detects clone nodes with the help of a claimer-reporter-witness framework and a random walk is used within each area for the selection of witness nodes. Our simulation results show that ND-RAWL do better than the existing witness node based strategies with moderate communication overhead.
Implementation of Area-Efficient and Low Power OFDM Architecture

: Fast Fourier Transform (FFT) algorithm is extensively used in numerous signal processing and communication systems. Due to its rigorous computational requirements, it occupies large area and consumes high power if implemented in hardware. By using the FFT concepts we are certainly in emerging efficient architectures for wireless networks which are common in universally now-a-days. The SDC processing engine (PE) is proposed to achieve 100% hardware resource utilization by sharing the common arithmetic resource in the time-multiplexed approach, including both adders and multipliers.
Approaches for Generating Test Cases Automatically to Test the Software

-Testing the software is very important phase in software development life cycle. So to test the software automatically is the best way to test the software because it consume less time where testing software manually is consuming process. To test the software automatically, test case generation is the best way. One way to generate the test cases is with the help of UML diagrams. In this paper we study the various techniques to generate the test cases from the UML diagrams to test the software automatically. Different tools are used to generate the UML diagrams. A new method is also proposed which will help in testing software automatically by generating test cases. Techniques in which different approaches are used like model based approach, novel approach. approach in which genetic algorithm is implemented as data mining technique are used to generate the test cases automatically, function minimization technique used for finding the minimum predicate function. The different tools like AGEDIS, TGV and GOTCHA are used for test generation. These approaches have been proposed to bring out all possible test cases of given object diagram.
MINI REVIEW ON LC/MS TECHNIQUES

Liquid Chromatography/Mass Spectrometry (LC/MS) is fast becoming the preferred tool of liquid chromatographers. It is a powerful analytical technique that combines the resolving power of liquid chromatography with the detection specificity of mass spectrometry. Liquid chromatography (LC) separates the sample components and then introduces them to the mass spectrometer (MS). The MS creates and detects charged ions. The LC/MS data may be used to provide information about the molecular weight, structure, identity and quantity of specific sample components. KEYWORD: Liquid Chromatography/Mass Spectrometry, mass spectrometer components.
A Study on FPGA Based Digital Modulators

: This paper presents a study on different digital modulation techniques based on FPGA and their Bit Rate Error. Digital modulation represents the transfer of the digital bit stream from the transmitter to the receiver via the analog channels. The information signal modifies one or more carrier parameters, leading to shift keying techniques during the modulation process. Various DSP based data compression, encoding/decoding algorithms, and noise filtering techniques have been developed to achieve effective and efficient data transmission with the help of FPGAs for hardware implementation. Modulators were designed using VHSIC (Very High Speed Integrated Circuit) Hardware Description Language (VHDL) was realized on high speed FPGA (Field Program Programmable Gate Array). Data rate transfer is fairly important in wireless communication systems. BER (Bit Error Rate) of different digital modulators was compared. From literature survey it was found that design employs the minimum number of blocks necessary for achieving different digital modulation. The functionality of these digital modulators will be demonstrated through simulations using Xilinx 13.2.
Design and Analysis of Winglet for Low Subsonic Speeds

Winglets are vertical or angled extension devices attached at the wingtips. They improve the aerodynamic efficiency by reducing the induced drag caused by wingtip vortices.This paper describes a wingtip analysis that is performed on a rectangular wing of NACA 2412 cross sectional airfoil. The objective of the proposed paper is to compare maximum aerodynamic efficiency of the wings with winglet and without winglet at low subsonic speeds. A rectangular wing with and without winglet is studied. In this investigation a wing of constant wing span, aspect ratio, chord and wing area is analyzed under idea flow conditions for reduction in induced drag. XFLR5 software is used for the analysis. Vortex lattice method is used in this software to solve the equations in the assumed inviscid flow.
Multimodal image registration of UAV and Satellite images using Mutual Information

: In this paper we have developed a multimodal image registration system for Unmanned Aerial Vehicle (UAV) image and Google Satellite image. This method uses a small number of automatically extracted scale invariant salient region features, whose interior intensities can be matched using robust similarity measures and mutual information to refine registration between UAV image and Google satellite image. The step involved in this method are orthorectification, feature detection, feature matching, RANSAC (model fitting) and transformation. This method gives more accuracy than the conventional image registration methods.
Estimation Word and Target Extraction from Customer Reviews with Learning of Collective Behavior

: The main intension of opinion mining is collecting the online reviews about the product, social networks informal text. A rec ent approach is based on the partially supervised alignment model for identifying the opinion relations as an alignment process has been to satisfy the long span relations. To accurately mine the opinion relations among words, the Word Alignment Model (WAM) and is used and to progress the error propagation, the graph based co-ranking algorithm is motivated. The study of collective behavior is to understand how individuals behave in a social networking environment. As we come across, Oceans of data generated by social media like WhatsApp, Facebook, Twitter, Flickr, Instagram , Hike and YouTube present opportunities and challenges to study collective behavior on a large scale data. In this work, we aim to learn to predict collective behavior in social media.
A Closed Loop Hybrid Phase Shift Controlled Dual Active Bridge Converter with Dynamic Input Voltage Change

In this paper we introduce a novel closed loop hybrid phase shift control for a dual active bridge converter with variable input voltage. By keeping an inductor between the transformer middle tap and the midpoint of two split capacitors in DAB topology, this paper proposes an adjusted DAB converter for input applications. A closed loop HPS control plot is proposed to permit all power changes to get ZVS over the full working extent; accordingly, fundamentally limiting the losses and lightening electromagnetic interference. In addition, the proposed control plot does not fundamentally build the conduction losses in correlation with the expanded EPS control. In this way, the modified DAB can work efficiently. The topology deduction are first known. At that point, the EPS and TPS regulations are connected, and the comparing working standards and qualities, including the switching, power transfer, and root-mean-square current, are investigated in detail with the help of MATLAB Simulink software with complete results with dynamic response.
Machine Learning Approach for User Account Identification with Unwanted Information and Data

achine Learning used for many real time issues in many organizations and for the purpose of social media analytics machine learning models is used most prominently and to identify the genuine accounts and the information in the social media we are her with a new pattern of identification. In this pattern of model we are proposing some words which are hidden to identify the accounts with fake data and the some of the steps we are proposing will be help to identify the fake and unwanted accounts in Facebook in an efficient manner. Clustering in machine learning will be used and in prior to that we are proposing an efficient architecture and the process flow which can identify the fake and suspicious accounts in the social media. This article will be on machine learning implementations and will be working on OSN (online social networks). Our work will be more on Facebook which is maintaining more amount of accounts and identifying which are over ruling the rules of privacy and protection of the user content. Machine learning supervised models will be used for text classification and the image classification is performed by CNN of unsupervised learning and the explanation will be given in the implementation phase. There are large
Wildcard Encryption System Using RSA Algorithm with K2C

: Searching is one of the major task in today’s internet. Many Search Engines are designed to enable this searching process. The search results are based on the word or phrase given for searching. The results have the content matching the pattern or phrases of the search input. But, today the world demands for a better search results, which is given by the new searching mechanism called the Wildcard Searching Technique. The Wildcard search is a technique which matches the entire character rather than only a normal string. The Wildcard Searchable Encryption Technique provides confidentiality and privacy of data. At present Paillier Homomorphic encryption has been used for wildcard search. Some disadvantages have been analyzed in its performance level like key size and its encrypted file size. In this paper, we proposed to implement RSA Algorithm, so as to increase the efficiency and performance of wildcard search.
HMM-based Speech Synthesis with Multiple Individual Voices using Exemplar-based Voice Conversion

Traditional text-to-speech (TTS) systems can synthesize only single individual voice. When we need to synthesize other individual voices, we have to train the system again with the new voices. The training process normally requires a huge amount of data that is usually available with a few specific voices existed in the database. The state of the art TTS using Hidden Markov Model (HMM), called as HMM-based TTS, can synthesize speech with various voice personality characteristics by using speaker adaptation methods. However, both of the voices synthesized and adapted by HMM-based TTS are “over-smooth”. When these voices are over-smooth, the detail structures clearly linked to speaker individuality may be missing. We can also synthesize multiple voices by using some voice conversion (VC) methods combined with HMM-based TTS. However, current voice conversions still cannot synthesize target speech while keeping the detail information related to speaker individuality of the target voice and just using limited amount data of target voices. In this paper, we proposed to use exemplar-based voice conversion combined with HMM-based TTS to synthesize multiple high-quality individual voices with a few amount of target data. The evaluation results using the English data corpus CSTR confirmed the advantages of the proposed method.
Innovation Culture among Women Entrepreneurs in India

A woman in business is a recent phenomenon in India. By and large they had confined themselves to small business and tiny cottage industries. A sense towards independent decision-making on their life and career is the motivational factor behind this urge. Women Entrepreneurs may be defined as the women or a group of women who initiate, organize and operate a business enterprise. They should explore the prospects of starting new enterprise, undertake risks, introduction of new innovations, coordination, administration and control of business and providing effective leadership in all aspects of business. In India compared to men, Women Entrepreneurs face more peculiar problems like the tradition, customs, sociocultural values, ethics, family needs, hard work areas, feeling of insecurity, etc when they enter into entrepreneurship. As such there is a need for Practice of Innovation culture among Women Entrepreneurs to overcome the challenges faced by them. A successful innovation culture embraces all aspects of a business and should be managed as effectively and efficiently where all ideas and innovations are collated and coordinated for the success of business. In this regard a research study was carried out with an objective to measure the Innovation Culture among Women Entrepreneurs in India with a sample size of 300 with key metrics as Strategic thinking, Ideation and Innovation Development.
Sentiment Analysis for Tweets using Patterns and Strategies to Detect the Genuineness of Tweets

Sentiment analysis related with distinguishing and classifying opinions or sentiments expressed in given text. Social media is completing a colossal quality of wealthy knowledge within the type of tweets, standing updates, diary posts etc. Sentiment analysis of this user generated knowledge is incredibly helpful in knowing the opinion of the gang. Twitter sentiment analysis is troublesome compared to general sentiment analysis thanks to the presence of slang words and misspellings. Knowledge base approach and Machine learning approach square measure the 2 methods used for analyzing sentiments from the text. Public and private opinion a few wide range of subjects’ square measure expressed and unfold frequently via numerous social media. Twitter offers organizations quick and effective thanks to analyze customers' view toward the crucial to success within the market place. Developing a program for sentiment analysis is an approach to be accustomed computationally live customers' perceptions. This project cognitive content together with varied patterns for tweets along a side multiple strategies to discover the sentiment class expressed in a very tweet and if a tweet is real or not. We proposed work to classify sentiments of tweets from people to determine if people are happy, sad, angry, etc. about particular topic. Also the purpose of the work is to check genuineness of tweets so that rumors about any topics can be detected and mitigated. This approach can be used in various fields further as like detecting people sentiment about particular social issues. Also fake tweets and rumors which may further exploit to social issues like riots, religion complexities can be removed. To achieve these goals and fetch tweets we used Twit4j API and various techniques such as NLP, TF-IDF, and Sentiment Classifications are applied to get results accordingly. We had maintained our own database of words for dictionary purpose as well as have been used OpenApache NLP with their predefined dictionaries