Miracle-dz/UniFAR-FTUs huggingface dataset:
Identify Anomalies in Sensor Data using Big Data Analytics

: Sensor information established in enterprise and scientific investigation claims the place the information is produced with exceptional quantity and velocity. It is challenging to produce using on hand file administration tools or typical data handling applications. Big-data analytics furnish a good platform to support the addressing of this mission because it supplies a flexible load of massive computing, storage, and software services in a scalable way at lesser cost. However, these techniques will provide efficient support on speedy detection and locating of anomalies in big sensor data sets. For speedy anomaly detection in big sensor data sets, we toughen a novel data anomaly detection approach which exploits the full computation potential of big data platform. Firstly, sensor data sets are represented in the time series data format. These time series data are further decomp osed for faster identification of anomalies in sensor data. Specifically, in our proposed approach, the anomaly detection is based on the scale free network topology and most of the detection operations is conducted in SAX and Sequitur machine learning techniques . Hence the detection and location process can be dramatically enhanced.
Computational Study of Interaction between CYP450 Protein and Pyrethroids in the Cattle Tick, Rhipicephalus annulatus

The present work was carried out to examine the binding efficiency of pyrethroids-Cypermethrin, Flumethrin, and Deltamethrin on CYP41, encoding cytochrome P450 of Rhipicephalus annulatus by computational docking studies. The protein structure of CYP41 was predicted using Phyre2 web portal, and the structure validation was performed using SAVES4 server. The predicted structure was docked with different commonly used pyrethroids using GLIDE. Among the acaricides docked, Flumethrin showed the best binding energy. There are no considerable variations among the binding energy levels and scores of the acaricides with the target molecule. From the study, we inferred that CYP41 is an effective target for the selected pyrethroids.
IMPLEMENTING MODBUS PROTOCOL STACK WITH DETERMINASTIC INTRUSION DETECTION RULES

: The Technology seems to concern about connectivity these days. Using that connectivity, the data switching work can be done in more flexible ways with protocols like modbus. To use it in industry sectors and to have the complete robustness and reliability of modbus protocol, software protocol stack is necessary. The MODBUS protocol was not initially designed with keeping the security aspects in mind hence it lacks the mechanism to avoid the classical information security threats. For better commercial usage of the modbus, it should work efficiently in any adverse and challenging situations. This paper discussed simple, secure and practical means of communication which can be extended to the industrial automation field with the help of modbus stack implemented with Deterministic Intrusion Detection Rules [1].
Multi Target Optimization of Turbo Jet Engine with MOPSO Algorithm

In this paper, turbojet engine in ideal condition will be optimized by multi target genetic algorithm. The target functions are specific thrust (ST), specific fuel consumption (SFC) and thermal efficiency (ηt) that once will simultaneously be optimized by two by two way and the results will be revealed in the Pareto curves. For the second time these three objective functions will be optimized at the same time. At the end the findings of two by two ways will be compared with the results of three objective functions. Design variables are considered as Mach number and total compressor pressure ratio. The significant relation between objective functions is introduced according to Pareto points. There is no doubt that these functions without using methods are not considerable. KeywordsGenetic Algorithm, Pareto, Multi target optimization, Crossover, Mutation, Turbojet engine.
ASSOCIATION OF GAMMA GLUTAMYL TRANSFERASE AND BLOOD LIPID LEVELS IN TYPE 2 DIABETIC SUBJECTS

Objective: The present study analyzed the correlation of Υ-glutamyl transferase (GGT) with the high density lipoprotein and low density lipoprotein in type 2 diabetics. Study Design: Case control study. Study setting & Duration: Department of MedicineLUMHS Jamshoro, from January 2016 to September 2016. Subjects & Methods: 100 type 2 diabetics and 100 controls were selected through non-probability (purposive) sampling. Clinical history, physical examination and blood biochemical findings were noted in proforma. Biochemical tests were performed as per standard criteria on Roche Hitachi Chemistry Analyzer. GGT was detected by IFCC method. Data was analyzed at 95% confidence interval on the statistical package SPSS 22.0 (IBM, Incorporation, USA) and Microsoft excel. Results: The GGT was noted as 20.44±5.71 and 39.5± 5.56 U/L (P=0.0001) and the HDLc as 49.15±3.67 and 30.19± 10.61 U/L in controls and cases respectively (P=0.0001). GGT showed positive correlation with systolic BP, diastolic BP, blood glucose, HbA1c, creatinine, cholesterol, triglycerides and LDLc. Negative correlation was found of GGT with the HDLc (r= 0.676, P=0.0001). Conclusion: The present study found negative correlation of GGT with HDLc but positive correlation with LDLc. Hence, the GGT may be exploited as a simple and inexpensive atherogenic biomarker instead of expensive lipid profile.
Study on Cryptanalysis of the Tiny Encryption Algorithm

— In this paper we present the Study on a Tiny Encryption Algorithm. There is a requirement to specify cryptographic strength in an objective manner rather than describing it using subjective descriptors such as weak, strong, acceptable etc. Such metrics are essential for describing the characteristics of cryptographic products and technologies. Towards this objective, we use two metrics called the Strict Plaintext Avalanche Criterion (SPAC) and the Strict Key Avalanche Criterion (SKAC) mentioned in our study that the strength of popular ciphers such as DES and TEA. A related issue of significance in the context of cryptographic applications is the quality of random number generators which need to pass certain tests. In this Paper, we expose DES and TEA to some of the standard random number generator tests.
Culturally-endorsed Leadership, Social cognition, and Entrepreneurial Orientation: An Empirical Inquiry

Entrepreneurial orientation can not only be influenced by leadership, culture, but also through social cognition induced through Job Demands and Resources. Moreover, higher Entrepreneurial orientation could further lead to job satisfaction. These intricate relationships were never explored before. Therefore, we proposed a theoretical framework combining (Stephan & Pathak, 2016) and (Ralph Kattenbach, 2018) models, and modifying them to include the concept of Job satisfaction. Stephan & Pathak (2016) investigated the impact of Culturally-endorsed implicit Leadership Theories (CLT) on individual entrepreneurship. CLTs is a concept of culture-level build on individual-level implicit leadership theory (ILT) proposed by (Robert G. Lord, 1991). (Ralph Kattenbach, 2018) modified (Bandura, 1997) social cognitive theory (SCT) to include Entrepreneurial orientation. SCT itself was a modified version of Job Demands-Resources Model proposed by (Demerouti, 2001). Empirical validity of the proposed theory was established by means of a survey based on close ended Likert scale type questionnaire that collected data from 200 corporate sector employees based in Karachi. It was later analyzed using structured equation modeling and confirmatory factor analysis. This result showed that both cultural factors i.e. Uncertainty Avoidance and Collectivism have a significant and positive influence on both Self-Protective and Charismatic leadership. However, the effect of leadership on entrepreneurial orientation (EI) was not empirically significant. Similarly, the effect of both social cognitive factors i.e. Job Demand and Job resource on EI was positive and significant. EI and job demand had an insignificant effect on job satisfaction. However, job resource has a significant positive impact. This imply that job resource factors have a direct influence on EI as well as Job Satisfaction. But EI itself has no direct link with job satisfaction of employees. Hence, mapping and evaluating a culture of organization in consolidation with its employees’ job demand and resource factors may lead to higher job satisfaction.
Estimating Willingness to Pay for Improving River Water Quality Using Contingent Valuation Method: A Conceptual Framework

This paper presents a conceptual framework to help in the interpretation or design of contingent valuation studies for improving river water quality in a developing country setting. An extensive literature review helped design this conceptual framework. Though the betterment of the river water quality has drawn the attention from various stakeholders, dearth of studies to deliver precise information about the value of the water quality appears a major drawback in developing countries to implement improvement plans. The major objective of this paper is to review the recent developments on non-market valuation e.g., contingent valuation method to design an appropriate economic valuation study for the river water quality. This study provides useful information which may help for further improvement of the water quality in an alike problem of developing countries. Future studies should validate empirically the proposed research framework.
Face Recognition Using Principal Component Analysis Based Feature Space By Incorporating With Probabilistic Neural Network

Face recognition is one of the highly focused area for the researchers due to its persistent and reliable features. In this paper, we propose a reliable and computational efficient model for face recognition. Principal component analysis ( PCA ) is used to collect statistical based features from sub region of the face images. Different nature classification learners such as Probabilistic Neural Networks (PNN), support Vector Machine (SVM) and Random forest (RF) are utilized to measure the performance of the proposed system. 10-folds cross validation test is employed to assess the prediction rate. After empirical investigation, it is observed that PNN has considerably enhanced the success rates of the proposed model. Our proposed model might be useful and helpful in security related applications.
Optimal Placement and Sizing of Solar Constructed DG Using SSO Technique

ISSN: 2347-8578 www.ijcstjournal. org Page 333 Optimal Placement and Sizing of Solar Constructed DG Using SSO Technique Vijay R [1], Antrut Jaffrin R [2], Ravichandran CS [3] Assistant Professor , PG Scholar [2] Electrical and Electronics Engineering, Anna University Regional Campus, Coimbatore Professor & Dean , Electrical and Electronics Engineering (PG) Sri Ramakrishna Engineering College, Coimbatore Tamil Nadu India ABSTRACT Proper placement of Distributed Generation (DG) in distribution system is still very challenging issue for obtaining their maximum potential benefits. This paper proposes a constrained multi objective Social spider optimization (SSO) based performance model of photovoltaic (PV) array placement approach for power loss reduction and voltage stability improvement of radial distribution system. The paper reflects the effectiveness of PV array performance models in DG placement problem formulation. Voltage Stability Factor (VSF) has been used in this paper which can quantify voltage stability levels of buses in the system. Opt imal placement and sizing of Solar based DG tested on15-bus system. The results clear that the proposed SSO outperforms than the other methods.
CM-Based Blind Equalization for Time-Varying MIMO-FIR Channels with Single Pulsation

— The constant modulus (CM) property of source signal can be mostly utilized to equalize the single-input multiple-output and finite impulse response (FIR) channels. In existing, the channels are blindly equalized and the equalization methods are based on higher order statistics that estimates all non-zero channel pulsation under time-invariance assumption. However, the assumption cannot be satisfied time varying multiple input multiple output (MIMO) applications ex. Mobile communication. In this paper, the proposed algorithm which extends the CM criterion to blind equalization using complex exponential basic expansion model (CE-BEM) and the channel is assumed as time varying MIMO-FIR. The method only employ the Second order statistics (SOS) and finally, it estimates only one pulsation. In this way, the system increases the SNR of the transmitted symbols and yield most beneficial result in time-varying channels. The fast convergence is also achieved through zero forcing equalization.
Lifetime Extension of Wireless Sensor Network Using Harmony Search Algorithm

– The lifetime of wireless sensor networks could be extended and it could cover all targets is based on memetic algorithm approach. Darwinian evolutionary and Lamarckian enhancement uses memetic algorithm. This algorithm also gives better solution than any other algorithms. Many Task Assignment Problems(TAP) and particle swarm optimization techniques formulated this harmony search algorithm. The harmony search algorithm performs certain steps. Firstly, show the WSN creation in MATLAB. Placing the nodes and sensor covers up which targets at a particular sensing range. Initially we will be generating the values using random permutation. We can also find the simulation with different sensing ranges and different population. It holds certain memetic algorithm processes such as Representation, fitness function, selection, crossover, mutation and compact operator. SET K-cover is initialized with harmony search, where cover forms a major advantage. Each covers plays a vital role in energy efficiency. Active and inactive state performs the usage of sensors and when it is not in use it will be inactive state which in turn helps us for conserving the energy. It also has been optimization techniques such as LP,NLP,DP. The improvisation of music player is named as harmony search.
FPGA IMPLEMENTATION OF A DISTRIBUTED CANNY EDGE DETECTOR

—Edges represent the significant local changes in the intensity of an image. Image Edge detection significantly reduces the amount of data and filters out useless information, while preserving the important structural properties of an image. A distributed canny edge detection algorithm is used which results in the reduced memory requirements, decreased latency and increased throughput with no loss in the performance of the edge detection, when compared to that of the original Canny algorithm. An FPGA-based hardware architecture of the proposed algorithm is synthesized on Xilinx virtex-2 pro.
Peer Ranking in P2P Integration System on Inconsistent Data Sources

: A query processor of an integration system of P2P should be able to deal with inconsistencies emerging while responding to a query. One way to deal with inconsistency of integration systems of P2P is to express the system’s semantics through Intensional logic in which each peer is considered to be as an entirely independent entity, results of which cannot cause inconsistency in another peer. Mapping semantics between peers creates a connection structure whereby each peer’s credit can be calculated based on the others. In this study, we have employed a crediting method to peers within the network using this connection structure of peers to one another so that the tuples of answers for a query can be credited. In order to calculate this credit, the proposed idea on Page Rank algorithm was used. Each peer’s calculated credit is the probability for tuple to be a valid response for the query.
Effect of Salesperson Consultation on Situational and Individual Motivators on Consumer Behavior

The purpose of this research is to investigate whether consulting with salespeople would enhance store performance or not. And if so what salesperson should do to increase the number of shoppers seeking salesperson consultation. In this study questionnaires were distributed among 402 respondents that were customers of hypermarket in Iran. Results of the research shows that purchase uncertainty, disposition to ward salespeople, efficiency orientation and shopping enjoyment leads to consultation with salesperson and as a result the buying behavior is affected. Keywords— Consumer behavior; Personal selling; Retailing; Salesperson consultation.
Design and Implementation of Job Scheduling in Grid Environment over IPv6

: In this paper we are going to design and implement the job scheduling algorithm for Grid environment using IPv6. We are establishing a cross regional scheduling mechanism to accomplish the job scheduling and job management, that chooses the operating location and mode automatically through the scheduling system and users request, due to which in grid computing the resources of will be used more efficiently and more reasonably The idea is that Grid technology managing this large and heterogeneous environment will allow an easy access to its resources for various users, by means of allowing them to submit their jobs into the system, guaranteeing them nontrivial Quality of Service (QoS) while hiding the complexity of the system itself by providing powerful but simple interfaces for the end user of the Grid. A grid environment is of two types: Data grids and Computing grids. Load Balancing is a technique in which the workload is distributed equally across multiple computers so that resource utilization is enhanced and the response time in grid environment get reduced. Main goal of load balancing is balancing load across all the processors which improves the throughput of grid resources. A good Scheduling algorithm works as it should balance the system load and assign jobs to resources efficiently. Hierarchical Load Balanced Algorithm is used to solve the problem in grid environment. The proposed system Enhanced Hierarchical Load Balance Algorithm is designed to schedule the jobs and also to improve the overall performance of the system in terms of resource utilization and user satisfaction. We will be using First Come First Serve(FCFS) approach so as to achieve the most efficient and optimized solution for our problem definition.
Tumor Suppressor Modulates Invasion via Smad 2 Signal in Breast Cancer

TGF-β elicits tumor promoting effects through its ability to induce EMT which enhances invasiveness and metastasis, the perturbations of TGF-β/Smad signaling are central to carcinogenesis in most of organs. A shift in Smad2/3 phosphorylation from the carboxy terminus to linker sites is a key event determining biological function of TGF-β. Here, we showed that let-7 was associated with breast cancer development and progression by directly targeted Smad2, suggesting a tumor suppressor role of let-7 and its target Smad2 is critical regulators of TGF-β signaling in breast cancer. *Corresponding author: Chuanliang Liu, Department of Health Care, The People’s Hospital of Weifang City, Shanddong Provence, China. E-mail: chuanliang_liu@163.com
Effects of Hypoplastic Fetal Umbilical Artery on Doppler Findings For Common Iliac Arteries

Background: The umbilical cord contains two arteries and one vein. Normally, the diameters of umbilical arteries are close in size, but this may vary, as one umbilical artery may be considerably smaller or more hypoplastic than the other. Objectives: This study aimed to investigate the effect of hypoplastic umbilical arteries on Doppler ultrasonography (US) findings for the common iliac arteries (CIAs), such as the pulsatility index (PI) and resistive index (RI) values, and to investigate the associations between hypoplastic fetal umbilical arteries and placental, umbilical cord, and fetal pathologies. Patients and Methods: Doppler US was performed on 165 pregnant women between 18 and 22 weeks of gestation, and again between 27 and 37 weeks of gestation. The umbilical artery diameters and both CIA flow parameters (PI and RI) were measured during these visits. The presence of a diameter difference of greater than 25% (95th percentile) between the two umbilical arteries was accepted as a hypoplastic umbilical artery. Results: Eleven of the 165 patients (6.7%) demonstrated a hypoplastic umbilical artery. Second-trimester US showed median dominant and non-dominant CIA PI values of 1.43 and 1.60 (P = 0.062), respectively, and median dominant and non-dominant CIA RI values of 0.80 and 0.85 (P < 0.001), respectively, in the hypoplastic umbilical artery group. Third-trimester US showed median dominant and non-dominant CIA PI values of 1.24 and 1.66 (P = 0.062), respectively, and median dominant and non-dominant CIA RI values of 0.73 and 0.82 (P = 0.002), respectively, in the hypoplastic umbilical artery group. We did not observe an association between hypoplastic umbilical arteries and placental, umbilical cord, or fetal pathologies. Conclusion: Our study revealed that the hypoplastic umbilical artery group’s non-dominant CIA had higher RI values than the contralateral dominant CIA.
Multimodal Biometric Authentication For Automated Teller Machine

— In the world of computer science & information technology security is essential and important issue. Identification and Authentication Techniques plays an important role while dealing with security and integrity . The human physical characteristics like fingerprints, face, hand geometry, voice and iris are known as biometrics. These features are used to provide an authentication for computer based security systems. Biometrics is the science and technology of measuring and analyzing biological data of human body, extracting a feature set from the acquired data, and comparing this set against to the template set in the database. As single security measures are easily prone to the attacks to break through the security system. The future in system security seems to belong to the combinational biometrics (a biometric system using more than one biometric feature) as a single biometric system (biometric system using single biometric feature) followed by the PIN (Personal Identification Number) has to contend with a number of problems.
Testing Complexity in Component based Software Engineering

The Component Based software development which reduces the time, budget and efforts compare to the traditional software development. The components are reusable, developed by third parties and available at Commercial-Of-The Self (COTS). Most recent technologies such embedded systems, mobile phones, control systems and other paradigms are developed with this concept. Software researchers should pay more attention on testing of Component Based technology. The software testing is the most commonly used technique for validating the product quality. It is something different from the traditional software development, due to the invisible source code and design make it very difficult to trace the faults. Software testing strategy is road map integrates test case design methods into well planned series of steps for successful construction of software. The selection right strategy at the right time will make the software product as robust. This paper highlights the various software testing challenges, difficulties, strategies and techniques in perspective of Component Based Software Development
Feature Subset Evaluation and Classification using Naive Bayes Classifier

– Feature Reduction is the reduction of features. Most of the intrusion detection approaches focused on feature selection issues such as irrelevancy, redundancy and length of detection process. These issues will degrade the performance of system. The performance of the system is improved by three feature selection methods involving correlation based feature selection, Gain Ratio and Information Gain. The threshold based Naive feature reduction algorithm is used to reduce the features. The reduced features are further classified by Naive Bayes classifier to produce best performance to design Intrusion Detection System.