Miracle-dz/UniFAR-FTUs huggingface dataset:
An Encounter Based Routing in Delay Tolerant Network (DTN): A Hybrid Approach

: Background: Delay Tolerant Network (DTN) is a new type of Mobile Ad hoc Networks(MANETs). Unlike MANETs, it is difficult to maintain stability in end to end networks due to DTN characteristics like long communication delay and high mobility of network etc. The Store and Carry mechanism used for the network, node can store and receive the messages in the buffer and wait for the opportunity to transmit them. Therefore, it is very important to define a new reliable and efficient routing strategy in DTN. Method/Statistical Analysis: In this paper, we propose a hybrid routing algorithm Spray and Wait with EBR (S&W with EBR) combination of both Encounter Based Routing (EBR) protocol and Spray and Wait Routing (S&W) protocol and compare with that of Source S&W and Binary S&W under different network size. Findings: Simulation results show that proposed routing scheme achieves better performance with respect to Delivery Probability, Overhead Ratio, Dropping Packets and Goodput.
Trade Imbalance and Entrepreneurial Activity: A Quantitative Panel Data Analysis

Shale Oil export from the United States overseas today depicts the need for the United States to reduce its negative trade balance sheet and Nigeria’s wish to improve agricultural exports reflects its willingness to reduce its problem of oil dependence. Net Savings accruing from exporting capabilities have strong consequences for trade and specifically for balance of payment and country specific trade account. Its positive effect on net trade is often affected by strong domestic consumption of foreign imports leading to trade imbalances, and capital flight. This study investigates the relationship between savings, exports and net trade using quantitative techniques by considering panel data for Nigeria and the United States, It was found that net savings from trade and exports promote net trade positively, and that imports affects net trade negatively since business were probably not importing to promote further production activities causing trade deficit and negative imbalance.
PREVALANCE OF LEFT VENTRICULAR HYPERTROPHY IN HYPERTENSIVE PATIENTS UNDERGOING ECHO CARIOGRAPHY

Left ventricular hypertrophy is an important predictor of cardiovascular risk, and its detection contributes to risk stratification. The aims of the study were to evaluate the prevalence of left ventricular hypertrophy in hypertensive patients and to assess the accuracy of electrocardiography in its diagnosis. Left ventricular hypertrophy (LVH) is an important predictor of cardiovascular risk, and its detection contributes to risk stratification. The aims of the present study were to estimate the prevalence of echocardiographic LVH and to evaluate the influence of echocardiography (ECHO) on cardiovascular risk stratification in hypertensive patients presenting in Khanaqin general hospital.
Evaluation of Nano-formulated Heteroleptic metal complexes as potential Antifungals against Fusarium oxysporum

The established antifungal moieties viz. 1,2,4-triazole, dithiocarbamate and phosphorous were brought in a single molecule to give a series of metal complexes ofcobalt, copper and iron. The synthesized derivatives were further improvised with an essence of nanotechnology for the better application of the non-soluble molecules to get nano-sized dispersion in water. The formulated target compounds were evaluated for their fungicidal potential against Fusarium oxysporum, by poisoned food technique. The overwhelming results were indicated by compound 5 (EC50 value 4.80 ppm).
Facial Expression Detection using Hidden Markov model

Face recognition has them ostrelevance in real life issues of security, criminal investigation, and verification intention. Thus it has broad range of applications. Three issues in the field of face recognition are: illumination variation, pose variation and more importantly expression variation which is the main focus of this paper. Human-Computer Interaction is an emerging field of Computer Science where, Computer Vision, especially facial expression recognition occupies an essential role. There are so many approaches to resolve this problem; among them HMM is a considerable one. In this paper, we study Hidden Markov Mode l(HMM) and KNearest Neighbor (KNN) classifiers ,and put forward a combined approach for facial expression recognition. The reared eight different facial expression classified here: angry, annoyed, disgusted, grumpy, happy, natural, sad and surprise. The basic idea of this approach is to employ the KNN and HMM classifiers in as sequential way. Experiment on faced at a bases how that the proposed method has encouraging recognition performance.
Pitch Angle Control of Wind Turbine using Fuzzy Logic

A wind turbine is a device that converts kinetic energy from the wind into electrical power. The speed control of wind turbine rotation is necessary for maximum energy capture and to keep the turbine components within designed speed and torque limits. In this paper, an advanced pitch angle control strategy based on fuzzy logic is proposed. The control input variables for the fuzzy logic controller are generator output power and wind speed and the output is pitch angle reference. A small change in pitch has effect on the extraction of available energy, reduction of torque and output power variation to the grid. The effectiveness of the proposed method is verified by simulation results for a 1.5MW induction generator wind turbine system.
EVALUATION OF TOKEN BASED TOOLS ON THE BASIS OF CLONE METRICS

— The area of clone detection has considerably evolved over the last decade, leading to approaches with better results. Since code clones are believed to reduce the maintainability of software, several code clone detection techniques and tools have been proposed. Token-by token matching technique is more expensive than line-by-line matching in terms of computing complexity since a single line is usually composed of several tokens. In this paper token based tools have been evaluated that is, CCfinder and PMD copy/paste detector on the basis of three types of metrics that is, clone set metrics , file metrics , line metrics to investigate the code clones in source files. The results of the analysis processes show that each tool has its own strengths and weaknesses and no single tool is able to identify all clones within the code.
Medical Diagnosis System based on Artificial Neural Network

- Nowadays, computerized systems are becoming very popular in medically related areas. One of the major problems in medical field is setting the diagnosis. Medical diagnosis system is a system which can diagnose diseases through checking out the input symptoms. In this paper, an intelligent medical diagnosis system for three diseases: diabetes mellitus, heart disease and liver disorder is presented by applying Back Propagation Neural Network Learning Algorithm. This system aims to effectively identify a disease as infected or non-infected according to user input data. The required data for the diagnosis system are obtained from UCI machine learning repository. The accuracy of the proposed system for diabetes mellitus, heart disease and liver disorder are 83%, 64% and 57% respectively.
The Bullwhip Effect — Impact of Lead Time , Information Quality , and Information Sharing

A simple system dynamics model of a traditional supply chain system is investigated. Particularly, the effect of lead time, information quality and information sharing also remanufacturing lead-time and the return rate on the inventory variance and the generation of bullwhip effect were studied. Our results clearly showed that the bullwhip in the closed loop supply chain is bigger than one in traditional supply chain and foreign to the collection rate and the inventory variance in every stage decrease when the quality of information and the information sharing is introduced into the traditional supply chain. Furthermore, we found that the bullwhip effect in the closed loop supply chain will increase when the short term lead time of remanufacture cycle time increase.
E^2ACM: Energy Efficient Adaptive Cluster based Multilevel Routing Protocol for Wireless Sensor Networks

a great challenge for designing a routing protocol that can maximize the network lifetime of Wireless Sensor Network (WSN), due to the limited energy of Sensor Node (SN). As a well-known hierarchical routing protocol in WSN, LEACH protocol could extend the WSN lifetime effectively. It assumes that all nodes can communicate with Base Station (BS) directly. With the expansion of WSN scale, the average distances between cluster head (CH) node and BS increase significantly, results in communication energy cost. For the large-scale WSN, this paper proposes a multimetric-based Energy Efficient Adaptive Cluster Based Multilevel (E 2 ACM) Routing Protocol. It regards the distance between CHs, nodes registered and residual energy of CH to construct a multihop path between CH and BS. Simulation results shows that proposed work significantly reduce the overall energy consumption of WSNs. KeywordsLEACH, Cluster based routing, Energy Efficiency.
Threshold Determination of SC-FDMA System using Resource Allocation

– Communication signals over power-line channels can be affected greatly by impulsive noise (IN). The effect of this noise is commonly reduced with the application of a nonlinear preprocessor at the receiver such as blanking or clipping that blanks and/or clips the received signal when it exceeds a certain threshold. Erroneous blanking/clipping of the unaffected signals can lead to significant performance degradations. It is found that determining the optimal blanking/clipping threshold is the key for achieving best performance. In contract to these studies, we show in this paper that the performance of the nonlinear preprocessing-based method is impacted by the blanking threshold. In light of this and for more efficient IN cancellation, this paper proposes single-carrier FDMA (SC-FDMA).
A Survey Paper on Gender Identification System using Speech Signal

: Gender is a critical statistic characteristic of individuals. This paper provides a survey of automatic human gender identification using speech signal characteristics and classifiers. A review of approaches exploiting information from human speech presented. Here, highlights of selection of speech features, their processing and different classifiers used for this purpose are discussed. Based on the results discussed in the papers it can be stated as, accuracy of automatic gender identification system with any classifiers is better if speech dataset used for training and testing is taken/ recorded in the same environments. Pitch is the basic feature of speech which distinguishes between adult man and woman. Other features like MFCC, LPC, RASTA-PLP also used for automatic gender identification. Neural Network, Support Vector Machine (SVM), Random Forest etc. are used for automatic gender identification through speech signal. Till now, many challenges are still available here to identify gender with acceptable accuracy in real life environmental speech where noise is acoustically added with human speech.
Juvenile glaucoma: Long-term development of ocular hypertension in children

Aim: Study of the long-term development of children with treatment for ocular hypertension (OHT). Purpose: IOP development, to detect risk factors and clinical features in children with OHT. Method: A retrospective, descriptive and non-randomized study of 42 children treated for OHT, with a mean follow-up of 11.6 years. Results: Most common family history: glaucoma (58%) and myopia (23%). The most frequent systemic pathological history was of airways disease, related in many instances to the use of corticosteroids. The most prevalent refractive error was found to be myopia (55%). The most frequent reason for first time consultation was vision loss. The mean central corneal thickness found was 562 μm ± 41. The diagnosis of childhood glaucoma using campimetry is difficult, since it relies on patient cooperation. In most cases, optic disc assessment, both ophthalmoscopically and using OCT, was not found to be reliable. The mean age of suspected OHT is 11 years old, usually considering abnormal pressure above 18 mmHg, and initiating treatment at 22 mmHg. The mean decrease through topical hypotensive medication was 4.7 mmHg, with no significant adverse effects registered. Forty-six percent of children abandoned medical treatment, after several years of control, upon verifying that IOP was normal. Conclusions: Some children maintain high levels of IOP. Half of them will normalize their IOP around the age of 20, but others will maintain OHT being adults. The response to medical treatment was sufficient in all the cases. In the literature review, we did not find any series of children with OHT as extensive or over such a long period of time.
A Key Frame-based Depth Propagation for Semi-Automatic 2D-to-3D Video Conversion Using a Pair of Bilateral Filters

This study aims to propose a novel key frame-based depth propagation for semi-automatic 2D-to-3D video conversion. First, we set the depth resulted from the bilateral filtering through the previous frame color as a reference depth. We also used the color difference between the previous frame and the current frame for bilateral filtering of the depth and created the initial depth of the current frame. At all locations of initial depth, we looked for the location enough to be matched to a reference depth in order to estimate motion and did depth compensation for the previous frame to estimate the final depth of the current frame. At this time, we used the block-based matching as a matching method and applied the dynamic search area method considering the processing time. In this study, the proposed method can be used to estimate the depth as closely as possible even at the region where the values of color in object vs background are similar and the edge shapes are preserved well in the same depth as set in key frames by an operator. Our method having several actual image sequences suggested that the estimated depth map was similar to the original depth map, compared to the existing method.
Analysis and comparison of THD in Five Phase PWM Inverter drive using Resonant Filter

Power Converters and Power Inverters are widely used in distributive generation system, the problem of injected harmonics are critical, total harmonic distortion (THD) increases the rms current that flows from a source to a load. Most of the harmonic currents/voltages flows in the load are frequencies which are higher than the fundamental supply frequencies, it generates more heat and increase the possibility of equipment may break. Harmonics are the additional current and voltages doesn’t contribute any mechanical force to the motors, instead it is simply dissipated as heat in the load, this may cause premature equipment failure and can cause equipment malfunction. In order to mitigate these harmonic problems a LCL filter is proposed in this paper. Harmonics in five phase PWM Inverter is studied using simulation and results will be presented.
Mining Interaction Patterns among Brain Regions by Clustering Based Interaction K-means

—Functional magnetic resonance imaging (fMRI) provides the potential to study brain function in a non-invasive way. Massive in volume and complex in terms of the information content, fMRI data requires effective, and efficient data mining techniques. Recent results from neuroscience suggest a modular organization of the brain. To understand the complex interaction patterns among brain regions we propose a novel clustering technique. We model each subject as multivariate time series, where the single dimensions represent the fMRI signal at different anatomical regions. In contrast to previous approaches, we base our cluster notion on the interactions between the univariate time series within a data object. Our objective is to assign objects exhibiting a similar intrinsic interaction pattern to a common cluster. To formalize this idea, we define a cluster by a set of mathematical models describing the cluster-specific interaction patterns. Based on this novel cluster notion, we propose interaction K-means (IKM), an efficient algorithm for partitioning clustering. An extensive experimental evaluation on benchmark data demonstrates the effectiveness and efficiency of our approach. The results on two real fMRI studies demonstrate the potential of IKM to contribute to a better understanding of normal brain function and the alternations characteristic for psychiatric disorders.
A HIGH GAIN & HIGH STABILITY OPERATIONAL AMPLIFIER FOR THE CAPACITANCE TO VOLTAGE CONVERTORS AT 180 NM TECHNOLOGY

This research work is done with an aim to illustrate the design of high open loop DC gain operational amplifiers showing relatively high open loop gain and high open loop stability. So a standard open loop/DC gain of the designed operationalamplifiers (op amps) of more than 75 Decibels (dB) is taken with the value of Phase margin more than 60 0 but less than 90 0 . The Unity Gain Bandwidth (UGB) of the op amp designed for the Capacitance to Voltage Convertor circuit should comprise a value greater than 10MHz. After designing the operational amplifier (op amp) the UGB value comes out to be 90 MHz (Mega Hertz) with the numerical of Phase Margin (PM) equivalent to 71 0 and the excellent DC gain value equals 80.12 decibels (dB). The operational amplifier worked with a reference or bias current of 12 uA. This reference current is same as that of the DC current applied to the operational amplifier. The operational amplifier is designed using the 180 nm technology. Further the operational amplifier is implemented using the Miller Compensation technique having two stages. High gain enables the operational amplifier to work efficiently and the high bandwidth enables it to be able to work at higher speed application. The whole design works on the +5V supply with the load Capacitance value 10pF and compensation Capacitance value 2.4pF with excellent input linearity.
SLAM Based Autonomous Mobile Robot Navigation using Stereo Vision

- In this manuscript, we present an autonomous navigation of a mobile robot using SLAM, while relying on an active stereo vision. We show a framework of low-level software coding which is necessary when the vision is used for multiple purposes such as obstacle discovery. The system was implemented and tested on a mobile robot platform, and perform an experiment of autonomous navigation in an indoor environment.
Functional and Nutritional Properties of Kenaf Seed

This study investigated the functional and nutritional properties of Kenaf seed. Kenaf seed powder was subjected to nutritional and biochemical analyses. The results showed that Kenaf seed contained 24.93% crude protein, 18.94% fat, 13.45% fibre, 4.5% ash, 5.01% moisture and 33.1% carbohydrate. Kenaf seed recorded appreciable level of Na, Ca, Mg, P, and Fe. The kenaf seed extract had appreciable reducing potential. Kenaf seed contained 1.3% flavonoid and 381mg GAE/g total phenol. The observations of this study present Kenaf seed as a source of antioxidants. Therefore, agro wastes such as Kenaf seed can be harnessed into valuable products.
Harmonizing User Search Data with Efficient Query Clustering

In this paper we proposed a web based searching techniques. The World Wide Web has become a new communication medium with Web information access. This incorporates with informational, cultural, social and evidential values to be specific. Present search engines generally handle search queries or keywords without considering user preferences or contexts in which users submit their queries. At times, user also fails to use proper keywords that represent their information need accurately. Ambiguous keywords, different needs of users at different times, and the limited ability of user to precisely express what they need have been widely recognized as one of the challenging obstacle in improving search results. Web based applications are at full stretch in today world. For a small piece of info we can easily find it on web with the help of search engine to us on web. Arrangements of the travel oriented phenomena, financial management, online purchases respectively we are dependent on web. To properly guide the users for their information quests on the web, search engines keep track of their queries and clicks while searching online. In this paper we are proposing a dynamic clustering algorithm will help us to group related queries together in such a way that the user can have faster access to their required links and the computational time is lesser.
Video Surveillance Technique for Marking Online Attendance in a Classroom

-The proposed system is concerned with automated video surveillance that observes the number of students sitting within a classroom. Video surveillance is a procedure of capturing and processing the still images. It can also be used in future evidences and analysis. Basically the idea is to implement a technique using video surveillance that automatically marks attendance of a student sitting in the order of their roll number in front of a personal computer. It also counts the overall strength of students present in a classroom and uploads the online attendance in each student’s account on University management system.
A Review on Document Privilege Access

— Cloud storage is an efficient way to store and maintain user’s data. With data storage cloud provides appropriate storage management, data sharing, data maintenance etc. Recently, users survived from cloud misbehave services as it breaks the organization bounds. Due to this user loses control over their data & it raises the security issues which slow down the confirmation of cloud computing. In this paper we presents SecRBAC
Enhanced Wireless Transmitted Message Security By Encrypted Complex Transformation

—Wireless communications faces less hacking immunity than wired communications. With the increase of dependability on wireless data transfer and calling, the need to develop new rigid algorithm is needed to add more levels of security on the wireless data. In the fact, the effort that is continuously putted in hacking the wireless transmitted data is more than the effort that is putted in building secure communication channels. This paper presents a packet transfer security model for wireless communication by the mean of cryptography and complex transformation. A secret key encryption / decryption algorithm was invented and presented in this paper. The encryption algorithm is demonstrated to decrypt the message and convert it to meaningless rapish data. The cryptographic encryption / decryption of the wireless packet is a first level security procedure, while the second level of security is being added by sending not the encrypted packet itself, but the complex transformation of that packet. This paper compares two reliable transforms; discrete cosine transforms (DCT) and discrete wavelet transform (DWT). The comparison between those two transforms is made, and conclusion is shown in the last.
Sockets digital design of aboveknee prosthetic for mass customization

Aiming at two main problems of designing prosthetic sockets time consuming and high cost, a digital design method of prosthetic sockets in mass customization for above-knee amputees is presented. Firstly, the numerical data representing the stump were obtained by the coordinate measuring machine (CMM). Then, feature points of the sockets were got by intersecting a set of rays with triangle patches to establish the master models of key modules. With these master models, the primary structure of above-knee prosthetic socket was made up. Finally, corresponding modules can be selected and configured to get a new individual prosthetic socket for an aboveknee amputee according to users specific body parameters information to meet different amputees requirements. Via this way, traditional individual design can be transfer to modularization design and design time and cost can be saved apparently.  2013 Trade Science Inc. INDIA