Miracle-dz/UniFAR-FTUs huggingface dataset:
G-chitosan: Reduced Graphene Oxide Nanoplatelets Functionalized with Chitosan; GPSS: Reduced Graphene Oxide Nanoplatelets Functionalized with Poly(Styrenesulfonic Acid)

This work aims the functionalization of reduced graphene oxide nanoplatelets with chitosan (G-chitosan) and also with poly(styrenesulfonic acid) (GPSS), thus forming stable, dispersed aqueous solutions. G-chitosan and GPSS solutions allowed the layer-by-layer (LbL) film formation with glucose oxidase (GOx), establishing multilayered nanostructures with elevated control in thickness and morphology. The graphene nanoplatelets were characterized by UV-vis and FTIR spectroscopies, resulting in good adherence and linear deposition of the graphene nanoplatelets with GOx in the LbL structures. Cyclic voltammetry shows an enlargement in the current intensity with increasing number of deposited LbL layers, possibly owing to the formation of conducting paths by the graphene nanoplatelets in the tailored multilayer nanomaterial formed. Journal of Bioprocessing & Biotechniques J o u r n a l o f B iop roce ssing & Bitechn i q u e s
Literature Survey and detection of Road Safety Aspects on National Highways in India

As in most countries, traffic police are the source of official government statistics related with road traffic injuries in India. The main sources of traffic crash data at the national level are the annual reports published by the National Crime Record Bureau (Ministry of Home Affairs) and the annual publication of the Ministry of Road Transport & Highways titled Road Accidents In India. The basic information for both these reports comes from all the police stations in the country based on the cases reported to them. Recent studies that have estimated national road traffic deaths using data from the health sector suggest the possibility of higher underreporting by traffic police. The Global Burden of Disease (GBD) study estimates that there were 264,000 (95%CI: 214,000-321,000) deaths in India in 2013 almost twice the deaths reported by traffic police (GBD 2013 Mortality and Causes of Death Collaborators, 2015). In this paper, the author has studied the various similar type of road accidents and safety aspects on national highways in India.
Improving Shopping Experience of Customers using Trajectory Data Mining

The up-to-date tracking tools, such as RFID (Radio Frequency Identification), Wi-Fi sensing brought a tremendous breakthrough in business analytics. These current trends can be used to record the paths taken by shoppers in a supermarket which form a trajectory data. By mining these trajectories it is possible to uncover shopper’s behavior including how they move among shelves of different product types, the time they spend on specific shelves, and other information that can be used to make a product arrangement that improves customers’ shopping experience and hence attract customers. Trajectories of shoppers in a grocery store as recorded from RFID tags or with the records of attendant located on their shopping ride forms the basis for the analysis. By using a clustering algorithm, we can profile shopping paths by neighborhoods visited and then by time spent to uncover the common paths of different categories of shoppers such as those who are looking to grab a few important items and leave. The clustered shoppers’ trajectories of items uncover the customer behavior that can be used to sketch groups of shoppers based on their space use and assess the impact of the spatial configuration of a store layout on shoppers’ behavior. In this paper, we propose a novel method of shopping super market items of trajectory clustering algorithm which groups similar transactions of super market item sets (trajectory) for shop which elucidates customer shopping behavior. A new similarity measure between transaction trajectories of super market items to group market basket item sequences of trajectories is developed. Our proposed method can find the dominant super market shopping path sequences of item sets that are capable of identifying the hotspots where most of the customers’ visits are made and the least visited paths as well. This can understand shopper behavior in a store. We used the real dataset of a supermarket in Nellore to apply the proposed methodology, as case study, to demonstrate the advantages and usefulness of the method
EFFECTIVENESS OF EARTHWORM (LUMBRICUSRUBELLUS) SUBSTITUTION FLOUR IN FEED FORMULATION ON SPECIFIC GROWTH RATE, FEED CONVERSION RATIO AND FEED EFFICIENCY OF NILE TILAPIA (OREOCHROMIS NILOTICUS)

The production of Nile Tilapia (Oreochromis niloticus) is quite significant but the unstable quality of feed and the uncertain supply increase the demand of fish flour. The aim of this study is to find out the substitution of fish flour to earthworm (Lumbricusrubellus) flour on specific growth rate, feed conversion ratio and feed efficiency of Nile Tilapia. The study was experimental study using a completely randomized design (CRD) with five treatments and four replications. The concentration of worm flour was P0 (0%), P1 (30%), P2 (35%), P3 (40%), and P4 (45%). The parameters observed were specific growth rate, feed conversion ratio and feed efficiency. Data analysis used ANOVA. The results show that the addition of worm flour in feed formulations of Nile Tilapia for 45 days could increase specific growth rate, feed efficiency and could reduce feed conversion ratio. The fastest growth rate is in P4 treatment (mean = 2.31%) which was added of 45% worm flour. The lowest feed conversion ratio is in P4 treatment (1.26). The best feed efficiency is P4 treatment (79.06%). The substitution of fish flour into earthworm flour at a dose of 45% in fish rations can be used to increase the specific growth rate and feed efficiency and can reduce the feed conversion ratio.
A SURVEY ON TEXT CLASSIFICATION TECHNIQUES AND APPLICATIONS

— Text classification is the way of discovering knowledge from ubiquitous text data which are easily accessible over the Internet or the Intranet. Automated text classification has been considered as a vital method to manage and process a vast amount of documents in digital forms that are widespread and continuously increasing. In general, text classification plays an important role in information extraction and summarization, text retrieval, and question answering. This paper illustrates the text classification techniques and applications.
Duplicate Item Replacement Technique for High Aggregate Diversity in Recommender Systems

Many recommendation techniques have been developed over the past decade, and major efforts in both academia and industry have been made to improve recommendation accuracy. However, it has been increasingly noted that it is not sufficient to have accuracy as the sole criteria in measuring recommendation quality, and consider other important dimensions, such as diversity, confidence, and trust, to generate recommendations that are not only accurate but also useful to users. More diverse recommendations, presumably leading to more sales of long-tail items, could be beneficial for both individual users and some business models. The main aim of this paper is to find the best top-N recommendation lists for all users according to two measures, they are accuracy and diversity.
A N OVEL P ROCESSING C HAIN F OR S HADOW D ETECTION A ND R ECONSTRUCTION I N V HR I MAGES

Image may contain shadow, which can lead to serious problem for full exploitation of image. This paper proposes A Novel Processing Chain to solve this problem. The main aim of this chain process is not only detect shadow region form image but also remove shadow region and reconstruct shadow less image. In this chain process, initially we classified shadow vs. nonshadow region by using binary classification with the help of support vector machine (SVM). For proper edge detection of shadow and nonshadow region, we apply canny edge detection technique followed by image imposing. Finally shadow reconstruction, calculate mean and standard deviation for shadow and nonshadow region of image. Find out mean difference between shadow and nonshadow part of image and apply this difference to shadow part of image by normalization with help of standard deviation.
Detection of TV Commercials using SIFT & Phase Correlation

-Image matching is a fundamental aspect of many problems in computer vision including object or scene recognition. In this paper, Scale invariant feature transform (SIFT) algorithm and Phase correlation are used to detect the TV commercials and to switch from one recorded TV show to another recorded show. SIFT features are first extracted from set of reference video and stored in database. A database image or new image is matched by individually comparing each frame from the recorded video. SIFT is an image local feature description algorithm based on scale-space. Due to its strong matching ability, SIFT has many applications in different fields. Features of SIFT are also robust to change in invariance. Phase correlation is a method of image registration. This method helps in identifying the particular part of the image frame. Template matching is an efficient tool which is required for the image registration and the object tracking applications.
Parameters Optimization Development on Relative Density and Compression Strength of AlSi10Mg Sample Produced by Selective Laser Melting using Response Surface Method

This paper investigates the effect of main process parameters such as laser power, scanning speed and hatching distance of selective laser melting process via relative density and compression strength using response surface method. Central composite design with three factor and three level has been used to develop the mathematical models on the relative density and compression strength of AlSi10Mg samples. The maximum and minimum relative density value recorded from the experiment measurement were 99.4785% and 97.2807% which occurred at design level 16 and 2. Meanwhile the maximum and minimum value of compression strength recorded were 545.578 MPa and 456.432 MPa which occurred at design level 15 and 2. The adequacy of the suggested mathematical models were verified from the analysis of variance (ANOVA) method and used to determine the optimized results. The optimized results on relative density and compression strength from Design Expert software were 99.3547 % and 545.578MPa, respectively occurred at 348.14 watt of laser power, 1483.25 mm/s scan speed and 0.1207 mm hatch distance. The optimized parameters were confirmed with three fabricated samples with an average value of 98.1123 % relative density and 540.597 MPa. These values were within 95% confidence level and evidenced that the developed models were adequate for both experiments.
Node Deployment in Homogeneous and Heterogeneous Wireless Sensor Network

Optimal sensor deployment is necessary condition in homogeneous and heterogeneous wireless sensor network. Effective deployment of sensor nodes is a major point of concern as performance and lifetime of any WSN. Proposed sensor deployment in WSN explore every sensor node sends its data to the nearest sink node of the WSN. In addition to that system proposes a hexagonal cell based sensor deployment which leads to optimal sensor deployment for both homogeneous and heterogeneous sensor deployment. Wireless sensor networks are receiving significant concentration due to their potential applications ranging from surveillance to tracking domains. In limited communication range, a WSN is divided into several disconnected sub-graphs under certain conditions. We deploy sensor nodes at random locations so that it improves performance of the network.This paper aims to study, discuss and analyze various node deployment strategies and coverage problems for Homogeneous and Heterogeneous WSN.
A COMPARATIVE STUDY : BLOCK TRUNCATION CODING , WAVELET , EMBEDDED ZEROTREE AND FRACTAL IMAGE COMPRESSION ON COLOR IMAGE

We undertake a study of the performance difference of different transform coding techniques i.e. block truncation coding (BTC), wavelet, embedded zerotree transform and fractal image compression. This paper focuses important features of transform coding in compression of still images, including the extent to which the quality of image is degraded by the process of compression and decompression. The above techniques have been successfully used in many applications. The techniques are compared by using the performance parameters PSNR, CR and reduced size. Images obtained with those techniques yield very good results. Out of these techniques BTC and wavelet are symmetrical compression techniques, EZW and fractal are asymmetrical compression techniques. Symmetrical compression means encode time and decode time are same and almost negligible while in asymmetrical encode and decode time is different and it lake lot of seconds to compress the image.
To Develop and Implement Low Power, High Speed VLSI for Processing Signals using Multirate Techniques

:- Multirate technique is necessary for systems with different input and output sampling rates. Recent advances in mobile computing and communication applications demand low power and high speed VLSI DSP systems [4]. This Paper presents Multirate modules used for filtering to provide signal processing in wireless communication system. Many architecture developed for the design of low complexity, bit parallel Multiple Constant Multiplications operation which dominates the complexity of DSP systems. However, major drawbacks of present approaches are either too costly or not efficient enough. On the other hand, MCM and digit-serial adder offer alternative low complexity designs, since digit-serial architecture occupy less area and are independent of the data word length [1][10]. Multiple Constant Multiplications is efficient way to reduce the number of addition and subtraction in polyphase filter implementation. This Multirate design methodology is systematic and applicable to many problems. In this paper, attention has given to the MCM & digit serial architecture with shifting and adding techniques that offers alternative low complexity in operations. This paper also focused on Multirate Signal Processing Modules using Voltage and Technology scaling. Reduction of power consumption is important for VLSI system and also it becomes one of the most critical design parameter. Transistorized Multirate module which has full custom design with different circuit topology and optimization level simulated on cadence platform. Multirate modules are used AMI 0.6 um, TSMC 0.35 um, and TSMC 0.25 um technologies for different voltage scaling. The presented methodology provides a systematic way to derive circuit technique for high speed operation at a low supply voltage. Multirate polyphase interpolator and decimator are also designed and optimized at architectural level in order to analyze the terms power consumption, area and speed.
High Speed FSM-based programmable Memory Built-In Self-Test (MBIST) Controller

— This paper proposed a High speed FSM-based controller for programmable memory built-in self-test for testing memory devices. This technique is popular because of its flexibility of new test algorithms. The architecture of controller is designed to implement a new test algorithm has less number of operations and this algorithm emphasis testing of high density memory ICs either faulty or good . The components of controller is studied and designed using Verilog HDL. The analysis of the timing, logic area usage and speed are presented.
INFLUENCE OF MARKET ORIENTATION AND INNOVATION ON MARKETING PERFORMANCE IN SMALL INDUSTRY OF MALAY WOVEN TEXTILE, RIAU PROVINCE, INDONESIA

This research aimed to study on market orientation and performance of marketing innovation on a small industrial woven fabric wilt in Riau province, Indonesia and to obtain the test results and study on influence of market orientation on performance marketing through innovation in small industrial woven fabric has been conducted descriptive and verification by descriptive and explanatory survey in Riau province. The verification tool used in this research is Structural Equation Modeling (SEM) by using of Lisrel program. The analysis showed that the market orientation affects the marketing performance through innovations in small industrial woven fabric wilt in Riau province, Indonesia.
Improved Real-time Multiple Face Detection and Recognition from Multiple Angles

— The proposed thesis is a real-time multiple face recognition system from an uncontrolled domain such as a surveillance camera or drone camera. The traditional methods make use of edge detection for face detection and pixel matching for recognition. These methods produce a lot of false positives. For accurate detection, Artificial neural networks are used. These techniques require more resources and is slower since convolutions has to be applied to every pixel subset. The proposed method uses a combination of Viola Jones algorithm to detect faces and Convolutional Neural network to refine the detected faces by removing false positives. The method is more accurate than traditional methods and faster than Artificial Neural Networks since only the detected subset is subjected to ANN. The ROI is automatically detected for all faces Each detected face is then recognized using eigen face recognition method. The proposed method can also learn similar faces automatically by referring previous frames. Each time a face is not recognized by the system in an angle yet it is known in other angles, the system auto learns the face to be the frequently recognized face. The sys-tem is built on Emgu CV and C# which makes it highly reliable and faster in Microsoft Platforms.
EMOTION RECOGNITION FROM SPEECH WITH GAUSSIAN MIXTURE MODELS AND VIA BOOSTED GMM

Speech has several endowment features such as naturalness and efficient, which makes it as winsome interface medium. It is possible to express emotions and attitudes via speech. In human machine interface application emotion recognition from the speech signal has been prevailing topic of research. Speech emotion recognition is an important issue which affects the human machine intercommunication. Automatic recognition of human emotion in speech angles at recognizing the primitive emotional state of a speaker from the speech signal. Gaussian mixture models (GMMs) and the scintilla error rate classifier (i.e. Bayesian optimal classifier) is embraced and effective tools for speech emotion recognition. Typically, GMMs are used to model the class-conditional distributions of acoustic visage and their parameters are outlined by the expectation maximization (EM) algorithm based on a training data set. Then, classification is performed to minimize the classification error w.r. t. the judged class conditional distributions. This method is called the EM-GMM algorithm. In this paper, we discuss about boosting algorithm for reliably and accurately estimating the class-conditional GMMs. The resulting algorithm is named the Boosted-GMM algorithm. This speech recognition experiment shows better results than the prior algorithms available update. This is due to the fact that the boosting algorithm can lead to more scrupulous estimates of the class-conditional GMMs, namely the class-conditional dispersions of acoustic features.
Michael porter's five competitive forces and generetic strategies, market segmentation strategy and case study of competition in global smartphone manufacturing industry

As per Porters five competitive strategies, to sustainably operate profitably, it is necessary for organizations to strategically deal with competition from both direct and indirect competitors who can affect the organization like influential customers, influential suppliers, new entrants, and substitute products. Market segmentation has proved to be an effective strategy in marketing of technology based products like smartphones. It was observed that the smartphone industry has a few players in manufacturing and with heavy capital costs limiting entry. The market is characterized by plenty of innovation through research and development which also increases the entry costs and harden exit for the players, the manufacturers are relatively few but competition can be said to be falling between intense and low. The suppliers have generally a lower bargaining power except for the software suppliers like google who have higher bargaining power. Smartphone manufacturers develop wide range of products targeting different market segments and in some cases phones with unique features are developed by various manufacturers as well as smartphones with different prices to suit different market segments. An analysis of the smartphone market shows that the market is approaching saturation in developed countries which also provide market for most of the smartphone sales but the developing countries like India and China have huge and fast market growth rates making the smartphone market growth to remain high globally. A combination of these factors and competitive forces show that the smartphone market is of moderate rivalry intensity and manufacturers can use a combination of different strategies to remain competitive. Market segmentation can facilitate implementation of the Porters generic strategies by smartphone manufacturers.
Free vibration analysis on FRP bridges

Fibre Reinforced Polymer Composites (FRP) are gradually gaining acceptance from civil engineers, mainly in the field of bridge engineering. The dynamic amplification factor is related to the fundamental frequency of the bridge. The study of free vibration is therefore, important to check whether the bridge will be safe under traffic induced vibrations. The paper presents the free vibration analysis of an FRP box girder bridge using the finite element software, ABAQUS. The bridge model consists of 18mm thick laminated FRP box girders with an outer layer of laminate winding all the box girders together. The deck of the bridge made of chopped FRP is supported on the girders. It was found that the natural frequency of the FRP bridge and the vehicular induced vibrations may cause possibility of resonance. Therefore, it is always significant to carry out the free vibration analysis of FRP bridge for its design.
Real Time Vehicle Accident Detection and Tracking Using GPS and GSM

-This paper presents review on the accident detection techniques and some future possibilities in this field. Now-a-days lots of accidents happen on highways due to increase in traffic and also due to rash driving of the drivers. And in many situations the family members or the ambulance and police authority is not informed in time. This result in delaying the help reached to the person suffered due to accident.Road accidents constitute the major part of the accident . The purpose of the project is to find the vehicle where it is and locate the vehicle by means of sending a message using a system which is placed inside of vehicle system Most of the times we may not be able to find accident location because we don’t know where accident will happen. Our project Real Time Vehicle Tracking and Accident Detection with GPS is designed to avoid such situations.