Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey of Vehicular Communication

: VANET ( VehicularAdHoc Network) used in vehicular communication which is trending area of research in the field of Automobile technology. Many companies ( Google, Uber, Ford, Mercedes Benzes, Toyota , General Motors etc.) are advancing their cars with such technology. Google launched its self-driving car project in 2009 under the leadership of Sebastian Thrun, a Stanford University professor who is lauded as the founder of the autonomous car. While at Google, Thrun led several projects at Google's X research lab, including Google Glass and Street View. Thrun first began his research on driverless vehicles at Stanford, leading a student and faculty team that designed the Stanley robot car. The car won a $2 million prize at the 2005 DARPA Grand Challenge for driving 132 miles in the desert on its own Google began its project with six Toyota Priuses and an Audi TT that drove through the streets of Mountain View, California. It hired a handful of people with perfect driving records to sit behind the wheel, a position it still hires for seven years later Google's cars use GPS, sensors, cameras, radar, and lasers to "see" the world around them. The sensors on the car can detect objects up to two football fields away, including people, vehicles, construction zones, birds, cyclists, and more. Google self-driving car project, is an autonomous car developer and an independent company under Alphabet IncIn 2015 the project completed its first driverless ride on public roads, giving a ride to a sole blind man in Austin, Texas in December 2016, Google transitioned the project into a new company called Waymo, housed under Google‟s parent company Alphabet. Alphabet describes Waymo as “a self-driving tech company with a mission to make it safe and easy for people and things to move around. ” The new company, which will be headed by long-time automotive executive John Krafcik, plans to make self-driving cars available to the public in 2020. The development of software and hardware in communication systems leads to the generation of new networks. Many researches and projects have been conducted in this area. Lots of government projects have been implemented in the USA, Japan and the European Union. New architectures, protocols and implementations of vehicular ad-hoc network (VANET) have been made in recent years to provide Intelligent Transportation Services. In this study, we survey the current issues like development, deployment, security challenges and about the current projects running in different countries. We also survey the mobility models and simulators required to implement VANET. We have also reviewed the emerging applications of VANET which provides services to the end users. At last, we have presented future research problems in VANET. The main motive of this survey is to explore the current ideas in vehicular communication and their Challenges.
Characterization of Mobile Radio Propagation Channel using Empirically based Pathloss Model for Suburban Environments in Nigeria

: This paper focused on characterizing mobile radio propagation channel using empirically based pathloss model for suburban environments in Nigeria. In this paper, field data were collected from a CDMA20001x network which included measurement of received signal strength over several distances from the transmitting base station. The averages of the measured data were used in determining the pathloss exponent of the propagation environment. Also, an empirical based pathloss model was developed for the testbed environment using the field data and the pathloss exponent. The developed pathloss model and the computed pathloss exponent of 3.63 were used in characterizing the testbed environment in order to determine the efficiency and link quality of the network under consideration
Transfer Learning for Image Classification and Plant Phenotyping

— Convolutional Neural Networks make effective use of multiple stacked layers to perform the task of Image Classification, but this implementation demands availability of considerable image data, high computation capability and significant time for training. Plant Phenotyping refers to the comprehensive assessment of complex plant traits. Due to restrictions in accessibility of extensive plant image data, Image-based Plant Phenotyping requires modifications to the implementation of Convolutional Neural Networks. We explore the process of Transfer Learning on the ‘Computer Vision Problems in Plant Phenotyping (CVPPP)’ database. We retrained the GoogLeNet Convolutional Neural Network model which was trained by Google Inc. on the ImageNet dataset. The ImageNet dataset comprises of approximately 100,000 images of 1000 classes. We demonstrate the fine-tuning of the GoogLeNet model to classify the Arabidopsis and Tobacco plants images from the CVPPP database which were originally not present in the ImageNet dataset. We achieved an overall accuracy of 98% on the retrained model using Transfer Learning by remodeling the final layers of the GoogleNet model. Further, we elaborate on the working of Transfer Learning in this use-case and the methodology we followed to accomplish our results.
IMPROVED IMAGE RE-SAMPLING DETECTION TECHNIQUE

: In this modern age in which we are living, digital images play a vital role in many application areas. But at the same time the image retouching techniques has also increased. To cope with this problem, the field of digital forensics and investigation emerged and provided some trust in digital images. In this paper we proposed a technique for image authentication that detects the manipulations that are done in the digital images. In most of the image forgeries such as copy-and-paste forgery, region duplication forgery, image splicing forgery etc basic image operations or manipulations are often involved. Thus if there exists the evidence for basic image alterations in digital images we can say that the image has been altered. Re-sampling (rotation, rescaling) operation is often done in forged images. The existing interpolation-related spectral signature method detects re-sampling and also estimates parameters such as rotated angle and rescaled factor effectively. But the re-sampling detection method detects some unaltered images as altered one when the images are JPEG compressed. We have overcome that problem by adding noise in the input images thus improving its performance. This work is tested in USC-SIPI database which consists of general unaltered images and we compared our results with the available re-sampling detection method.
Robot localization in a mapped environment using Adaptive Monte Carlo algorithm

—Localization is the challenge of determining the robot’s pose in a mapped environment. This is done by implementing a probabilistic algorithm to ﬁlter noisy sensor measurements and track the robot’s position and orientation. This paper focuses on localizing a robot in a known mapped environment using Adaptive Monte Carlo Localization or Particle Filters method and send it to a goal state. ROS, Gazebo and RViz were used as the tools of the trade to simulate the environment and programming two robots for performing localization
International Financial Reporting Standards and Earnings Management Behaviour of Listed Deposit Money Banks in Nigeria

This paper investigates the effect of International Financial Reporting Standards adoption on earnings management behavior of listed deposit money banks in Nigeria. The study examines how the change in the recognition and measurement of banks’ loan loss provision, affects earnings management behaviour. A sample of 15 deposit money banks listed on the floor of the Nigerian Stock Exchange (NSE) was used. Financial data in respect of the periods before and after adoption of the IFRSs (i.e., 2004 to 2008 and 2009 to 2013) were used. The banks under investigation experience a significant growth of their loan portfolio, on average, 16.65 % (median 14.77 %) during IFRS period as compared to 10.12 % (8.79 %) before IFRS adoption. Non-performing loans ( NPLit-1 ) remain relatively stable over the whole time period, and represent, on average, 3.44 % (median 2.21 %) of loans before and 3.19 % (median 1.99 %) after IFRS adoption. Regulatory capital ratios ( RegCap it ) remain basically similar in both time periods. Earnings before taxes and loan loss provisions ( EBTLLP it ) increase slightly; however, this increase is statistically not significant. Besides the impressive loan growth the most significant change between the two time periods relates to our dependent variable the level of loan loss provisions ( LLPit ). LLPit decreases significantly from a mean of 0.72 % (median 0.54 %) to 0.49 % (median 0.32 %) after IFRS adoption. Taken the descriptive statistics together, the study concludes that the restriction to incurred losses under IFRS significantly reduces the ability of banks to engage in earnings management. Keywords: IFRS, IAS, financial reports, loan loss provisions, earnings management, non-performing loans, loss recognition, bank regulation, earnings before taxes and loan loss provisions.
Analyze The Effects of Quarantine And Vaccination on Malware Propagation in Wireless Sensor Network

Malware (worm, virus, malicious signals, etc.) propagation in Wireless Sensor Network (WSN) is one of the important concern. The WSN becomes unstable due to presence of malicious signals. Vulnerability of WSN is very high because of the structural constraint of sensor nodes. The attackers target a sensor node of WSN for malware attack. A single infected node starts to spread the malware in the entire network through neighbouring nodes. Therefore, for controlling of malware propagation in WSN a mathematical model is developed. The developed model is based on epidemic theory. The developed model consist of five states such as Susceptible-Infectious-Quarantine-Vaccination-Dead (SIQVD). The quarantine is a method through which to cease the infection spread in WSN. And through vaccination eliminate the malware from the network. The combination of quarantine and vaccination technique improves the network stability. This technique prevents malware propagation in WSN. The basic reproduction number ( ) of the model is deduced. The stability of the network depends on the value of basic reproduction number. It is found that if the value of is less than one the network system exist in malware-fee state, otherwise in endemic state. The equilibrium points of the system is obtained. The effects of quarantine and vaccination has been analyzed on system performance. The theoretical findings are verified by simulation results. Attack Epidemic model Equilibrium point Malware propagation Security Wireless Sensor Network
Energy Efficient Protocols in Wireless Sensor Networks: Energy Efficient Protocols in Wireless Sensor Networks: Energy Efficient Protocols in Wireless Sensor Networks: Energy Efficient Protocols in Wireless Sensor Networks: A A A A SurveySurveySurveySurvey

Wireless Sensor Networks (WSNs) consists of huge number of Sensor Nodes (SNs) with sensing, communication and processing capabilities. SNs have limited energy supply, storage and computational capacity. In recent years energy efficient computation is a major concern in WSN. The critical aspects include reduction in the energy consumption of SNs so that the network lifetime can be extended to reasonable times. For this purpose many novel innovative techniques based on energy efficient computation have been proposed. In this paper, we present a brief analysis on energy efficient computation protocols. We have also presented a comparison of these protocols.
INTRODUCTION TO MEMRISTOR AND ITS OVERALL REVIEW

The concept of Memristor was first proposed with the mathematical proof by Prof. Leon Chua in his Research Proposal at IEEE Transaction on circuit theory based on the symmetric background. The relationship between four fundamental circuit variables, viz., voltage, current, charge and flux is given by using the concepts of resistance, capacitance and inductance. The concept which explains the relation between charge and flux linkage is the fourth fundamental element, Memristor which was proposed by Chua for the first time using the mathematical equations. The first nanoscale TiO2 based physical model of Memristor is proposed by Hewlett-Packard Laboratories in 2008. However fabrication of Memristor is at experimental level only. The research is in progress for making practically applicable physical model of Memristor. This is a review paper which explains the basic concept of Memristor, its properties, the modeling concepts of Memristor and a brief of its future applications. The challenges and the future scope of the Memristor have been discussed in the end.
Protective effect of PM pericarp extract on renal histological changes of alloxan-induced diabetes

Global prevalence of diabetes mellitus is increasing all over the world, resulting in higher prevalence of diabetic complication. Diabetic nephropathy is the most frequent complication suffered by diabetic patients. Phaleria macrocarpa (Scheff.) Boerl (PM) consist of active substance s which have antidiabetic properties. This study aims to evaluate the protective effect of PM pericarp extract on renal histological changes of alloxan-induced diabetes. Twenty five male albino (Sprague Dawley) rats were divided into five groups (of five each): normal control; diabetic; diabetic + metformin 100 mg/kgBW; diabetic + PM methanolic extract 250 mg/kgBW and diabetic + PM water extract 250 mg/kgBW. Diabetes was induced by alloxan monohydrate 150 mg/BW intraperitoneally. PM extract and metformin (as comparison group) was administered to diabetic rats for three weeks and at the end of the study, rats were sacrificed to obtain their kidneys for routine staining. Treatment with PM extracts (methanolic and water) and metformin significantly reduced glomerular hypertrophy, though the glomerular area of these groups was lower than that of the diabetic group (p < 0.01). Treatment with PM extract (methanolic and water) significantly reduced glomerulosclero sis, which showed a lower score of glomerulosclerosis degree (p< 0.01), and was still observed to be lower if compared with metformin (p < 0.01). It was concluded that PM extract re stored glomerular hypertrophy and improved glomerulosclerosis in alloxan -induced diabetes.
A Survey on Resource Allocation and Task Scheduling Algorithms in Cloud Environment

— Cloud computing is a computing service paradigm that charges under the basis of the amount of resources consumed i.e. pay per use constraint . One key characteristic that differentiate cloud computing from the other enterprises computing is that the infrastructure itself is programmable. An important issue faced by Infrastructure as a service (IaaS) in task scheduling and resource allocation is a NP-Complete problem. Although, there are various algorithms and methods were existing to solve the problem of resource allocation but none of these algorithms can be extended. The present study involves surveying the different task scheduling and resource allocation algorithms for cloud. Comparing the various algorithms, we conclude that various scheduling algorithms depend on the type of the task to be scheduled.
SCHEDULING OF INDOOR MOBILE ROBOT USING ULTRASONIC SENSORS

: This article proposes the scheduling scheme using ultrasonic beacons in a multi-block workspace. Indoor scheduling schemes using ultrasonic sensors have been widely studied due to their cheap price and high accuracy. However, ultrasonic sensors are susceptible to environmental noises from their propagation characteristics. On account of their decay phenomena when they are transmitted over a long distance, ultrasonic sensors are not suitable for application in large indoor environments. To overcome these shortages of ultrasonic sensors while emphasizing their advantages, a multi-block approach has been proposed by dividing the indoor space into several blocks with multiple beacons in each block. This approach, however, is hard to divide into several blocks when beacons are not installed in a certain pattern, and in case of having newly installed beacons, all blocks placement is reconstructed. Therefore, this is a real time localization scheme to estimate the position of mobile robot without effecting beacons placement. Beacon scheduling algorithm has been developed to select the optimal beacons according to robot position and beacon arrangement for the mobile robot navigation.
Bisphosphonate-Related Osteonecrosis of the Jaws [BRONJ]

Bisphosphonates are antiresorptive agents used to treat many systemic disorders like multiple myeloma, paget’s disease, osteoporosis, hypercalcaemia of malignancy and cancer metastasis. But the main adverse effect is the development of osteonecrosis of jaws. The objective of this article is to review the literature about chemistry, pharmacology and mechanism of action of bisphosphonates. Also literature is reviewed regarding etiopathogenesis, risk factors, prevention and treatment strategies for bisphosphonate related osteonecrosis of the jaws. Conclusion: Patients receiving high doses of nitrogen containing BP intravenously are at high risk of BRONJ development than when oral bisphosphonates are used. Dentists must be aware of this condition and all dental preventive measures must be taken to avoid complications of BRONJ before and during BP therapy. Therefore dental examination and treatment of all dental diseases is highly recommended prior to BP administration. Moreover, all patients taking BPs have to be informed of the benefits and risks of treatment and should be educated about this condition and encouraged to maintain an excellent level of dental hygiene and care and regular dental visits. Conservative approach is sufficient in treating most of the cases of BRONJ.
Low Cost Temperature Logging System using Raspberry Pi S.Natarajan1, A.Deepika2, I.Pradeeba3, R.Chandramohan4*

Abstract: All laboratories needs temperature measurement and monitoring system. Instead of noting down every reading using an analog device, the implementation of digital data logging is a better and in-situ way. The temperature data is read from the sensor and it is been logged into an Excel file. In our lab this setup provides very good alternative for existing analog thermometers. The Raspberry Pi Temperature sensor kit provides low cost, and consistent temperature measuring solution.
Enhancing Forensic Service in Distributed Cloud Computing

: - The Internet is growing explosively, as is the number of crime The Internet is growing explosively, as is the number of crimes committed against or using computers. As a response to the growth of computer crime, the field of computer forensics has emerged. Computer forensics involves carefully collecting examining electronic evidence that not only assesses the damage to a computer as a result of an electronic attack, but also to recover lost Information from such a system to prosecute a criminal. With the growing importance of computer security today and the seriousness of cyber crime, it is important for computer professionals to understand the technology that is used in computer forensics. It promotes the idea that the competent practice of computer forensic and awareness of applicable laws is essential for today’s organization.
IMPLEMENTATION OF SHORTEST PATH FOR NETWORKS TOPOLOGY USING MATLAB

Communication on interconnection networks is a fundamental problem that has to be solved optimally in order to optimize the usage of a parallel computer. One of the basic communication problems is k - k routing, in which every processing unit, PU, sends and receives exactly k packets. If the distribution of the destinations is homogeneous, then generally it is quite easy to perform the routing efficiently, but if the source/destination pattern is irregular, then trivial strategies may be lead to the congestion during the routing, resulting in packets getting delayed and overflowing buffers. The shortest path problem is concerned with finding the shortest path from a specified origin to a specified destination in a given network while minimizing the total cost associated with the path. The shortest path problem is an archetypical combinatorial optimization problem having widespread applications in a variety of settings. The shortest path problem has been investigated extensively. This paper develops the GUI based upon Dijkstra Algorithm for fast convergence of results. The proposed algorithm results are relatively independent of problem types (network sizes and topologies) for almost all source–destination pairs. Furthermore, The MATLAB simulation is carried for standard networks topologies varies from 4 to 30 nodes taken from IEEE and results were found to be very encouraging.
of Stable Methods In Unstructured Network For Routing Queries

- In an unstructured peer-to-peer network searching the document is very difficult problem because of more topologies and different processing capacity. In this system we propose a query routing approach which overcomes that problem. In this system the technique shown to be stabilize the query load subject to a grade of service constraint. In this system we introduce a query routing methods that works for arbitrary overlay topologies, nodes with heterogeneous processing capacity by using this technique. We get a result which further shows the proposed technique with decreasing complexity, estimation parameters and traffic load will be decreased. An explicit property of the region of system is given and mathematically compared to that associated with random walk based searches. One of the basic functions of this system is conveniently resolving queries or identifying files/resources.
AN ANALYSIS OF IMPACT OF JITTER ON WIRELESS & MOBILE NETWORKS

: Wireless communication networks have spread widely today. Numbers of services running on these networks have increased rapidly to meet the requests of modern users. Network operators have to provide services in the most cost-effective way while dealing with the fast changes of technologies and increasing traffic growth. The dramatic increase of multimedia application shave resulted in explosion of data usage. To offer services, a tab must be kept on delay, throughput and jitter. Applications such as digital audio and video have synchronization requirements and limits on Jitter. In this study, we have discussed in brief about the jitter, types of jitter and impact of jitter based techniques on various wireless networks. Also, we focus on video streaming traffic to evaluate the packet level and call-level performance of a multipath transmission scheme, which sends video traffic bursts over multiple available channels in a probabilistic manner.
Image Retrievals based on Statistical Modeling and Cosine Similarity

: The technological evolution encompassed drastic updates in the field of technology and communication. This technological updates have facilitated to pool variety of data ranging from text to videos. Therefore a repository of data is built indirectly and mining from these heterogeneous groups relevant information is a challenging task. This article addresses the concept of retrieving the images using statistical approaches together with cosine similarity.
Game Theoretic Approach for Cognitive Radio Networks

— Cognitive radio is a promising approach to make efficient use of spectrum by rapidly adapting the changes in wireless environment. In such networks, nodes are expected to be aware of their environment and must be able to learn from the outcomes of past decisions. Game theory which comprise of analytical tools designed to study interactive decision-making processes can be applied effectively to solve some of such complex problems. This paper discusses the significance of using game theory for cognitive radio networks and resource allocation, and various game theoretic approaches used for it