Miracle-dz/UniFAR-FTUs huggingface dataset:
A Modified PSO Based Solution Approach for Economic Load Dispatch Problem in Power Systems

This paper presents a new algorithm that utilizes the PSO with double chaotic maps to solve the economic load dispatch problem with different cost functions. In proposed approach, we employ the PSO method that involves the alternating use of chaotic maps in estimating the velocity of the particle. Presently the PSO method has been widely used in complex designs problems with multiple variables where the optimization of a cost function is required. The use of the PSO method for the economic load dispatch problem is widely studies however the best solution may require higher number of iterations and at the worst it fails to achieve global best solution, hence to overcome the problem irregular velocity updates are performed by some kind of random function which force the particles to search greater space for best global solution. However the random function itself derived from a well-defined mathematical expression which limits its redundancy hence in the paper we are utilizing the two different chaotic maps which are used alternatively this mathematically increased the randomness of the function. The simulation of the algorithm verifies the effectiveness and superiority of the algorithm over standard PSO and single chaotic map based PSO.
A Review on Stress Detection Based on Social Media Interactions

— Psychological wellbeing conditions impact a significant dimension of the total populace each year. Mental stress is turning into a risk to individuals' well-being nowadays. With the fast pace of life, an ever-increasing number of individuals are getting affected by increasing stress level. Distinguishing the user stress at initial stage is an important yet difficult task. With the notoriety of electronic social platform, people are accustomed to sharing their day to day events and exercises and connecting with companions by means of online networking media stages, making it conceivable to utilize online social network information for stress detection. In this paper, we will discuss a various study conducted by different researchers.
Proﬁcient Analysis of Mining Big Data Using Map Reduce Framework

Information now streams from everyday life from telephones and charge cards and TVs and PCs; from the framework of urban areas from sensor-prepared structures, trains, transports, planes, extensions, and production lines. The information stream so quick that the aggregate gathering of the previous two years is currently a zettabyte. This colossal volume of information is known as large information. Huge Data alludes to advancements and activities that include information that is excessively various, quick-changing or gigantic for traditional advances, aptitudes, and framework to address productively. Said in an unexpected way, the volume, speed or assortment of information is excessively extraordinary. The volume of information with the speed it is created makes it troublesome for the present processing foundation to deal with enormous information. To conquer this downside, enormous information handling can be performed through a programming worldview known as MapReduce. Commonplace, execution of the MapReduce worldview requires arranged connected stockpiling and parallel preparing. Hadoop and HDFS by Apache are generally utilized for putting away and overseeing huge information. In this exploration paper, the creators recommend different strategies for taking into account the issues close by through MapReduce structure over HDFS. MapReduce strategy has been learned at in this paper which is required for actualizing Big Information examination utilizing HDFS and minimize time.
Development of Specific Area Intrusion Detection System using YOLO in CCTV Video

 Abstract : Recently, many things are monitored with CCTV. It needs manpower to monitor. Therefore, we propose a system that stores the object’s data when the object enters a specific area. Generally, You Only Look Once (YOLO) method is used for object detection. We propose a system that increases the recognition rate by using new dataset because the recognition rate may not be accurate when using existing VOC weight, and can apply to intrusion detection. The Proposed model with the training data created on the particular conditions precisely detects proper objects and reduces effect by a variance of frame and brightness. The object was found more precisely with newly trained weights instead of using VOC weight. The dataset is made to fit to the specific situation, and it can be used for genera situation. When using the VOC weight, object detection was affected by the frame change and the brightness change of the light, but the effect was reduced by using new weight.
Density Based Protocol For Head Selection In Wireless Sensor Networks

—In wireless sensor networks nodes have several limitations such as limited battery life, low computational capability, short radio transmission range and small memory space. However, the most severe constraint of the nodes is their limited energy resource because they cease to function when their battery has been depleted. To reduce energy usage in wireless sensor networks, many cluster-based algorithms have been proposed. Among those proposed, LEACH (Low Energy Adaptive Clustering Hierarchy) is a well-known cluster-based sensor network architecture . In this paper, subtractive clustering technique, which is an enhancement in the basic LEACH protocol to deal with its severe shortcomings with respect to handling of node‘s non-uniform and time variant energy distribution.
Influence of Synthesis Temperature on Growth of Silver Nanorods

Silver nanorods (Ag NR) have been successfully synthesized by wet chemical method (seed-mediated growth) utilizing 10 nm silver nanospheres as a seed material and subsequent reduction of silver precursor with a weak reducing agent (ascorbic acid) along with a directing surfactant. The effect of synthesis temperature on the structure, morphology, composition and optical properties were investigated through X-ray diffraction analysis, scanning electron microscopy, transmission electron microscopy, energy dispersive spectroscopy, UV-Vis and FTIR spectroscopy. Both XRD and SAED patterns demonstrate that silver nanorods are crystallized in face centered cubic symmetry. The synthesis temperature significantly influences the morphology of the nanorods. Absorbance spectra confirm the nanorods formation with two SPR bands, one at lower wavelength side and another at higher wavelength side. The results show that increase of synthesis temperature led to decrease of aspect ratio of nanorods.
Numerical Solutions of Some Higher Order Fractional Integro-Differential Equations (FIDEs), Using Chebyshev Wavelet Method (CWM)

In this paper, the numerical solutions for some of the Integro-differential Equations are obtained, using Chebyshev Wavelet Method (CWM). The numerical simulations for integer and fractional orders are handled in a very efficient, simple and straight forward procedure. The numerical results of the proposed method are compared with the exact solutions of the problems. It is observed, that the solutions obtained by the present method have a strong agreement with the exact solutions of the problems. The solutions by this method have high degree of accuracy than any other numerical method. The numerical solutions of fractional order Integro-Differential Equations, shows convergence toward the integer order solutions.
What are the Prospects of Treating Neurodegenerative Diseases with Natural Products?

The aetiology of neurodegenerative diseases, such as Alzheimer’s and Parkinson’s diseases, is not fully understood. This is due to the fact that the development of such diseases is complex and multi-factorial. To date, several studies highlighted that one of the main mechanism of neuronal cell death is oxidative stress. This led researchers to investigate several naturally-occurring compounds, including dietary metabolites, and relate their mode of action to the oxidative stress mechanisms postulated in neuronal cells. In this review, we discuss the potential role of natural metabolites as candidates for the control and treatment of neurodegenerative disease, with a particular reference to Alzheimer’s disease and Parkinson’s disease.
TEXT EXTRACTION FROM VIDEO CONTAINING ARTIFICIAL IMAGES

— Videos contain a vast amount of information, which, if channelled properly can provide breakthrough in various research fields. Multimedia content retrieval is an important research field that aims in content based information indexing and retrieval, automatic annotation and structuring of video frames. Large amount of information is embedded in Natural Scene, which often requires automatic extraction and processing; Artificial Text can be termed as one of the important Multimedia content. In this Paper, it is attempted to accurately separate text content from multimedia objects by precisely localizing the text and extracting. Text detection in videos is an important step to achieve Multimedia content retrieval which plays an important part in fully understanding of the video clip. Object retrieval follows the general procedure involving detection, localization, tracking, extraction and enhancement of the text from a given image. The detection step roughly classifies text & non-text regions, the localization step determine accurate boundaries of the text string, the extraction step filters out background pixels in the text string
Physical and Mechanical Characterization of Aluminum Bronze (Cu-10%Al) Alloy with Tungsten

This paper investigates the addition of tungsten on the physical and mechanical properties of aluminium bronze. Despite some of the desirable characteristics most aluminium bronze exhibits, abysmally deficient responses in certain critical applications necessitate mechanical properties enhancement. The properties studied were electrorestivity, tensile strength, hardness and impact strength. Universal testing machine model 50kN were used to test for tensile strength, impact strength using charpy machine model IT-30 and Brinell tester model B 3000 (H). The specimens were prepared by modifying 0.5-5.0% tungsten into the aluminium bronze (Cu-10% Al) at interval of 0.5 percent. The specimens were prepared according to BS 131240 standards. Microstructure analysis was conducted using L2003A reflected light metallurgical microscope. Results show that optimum improved physical and mechanical properties were achieved at 3.0wt% tungsten addition with ultimate tensile strength (UTS) of 788MPa which represents 9.12% improvement over conventional aluminium-bronze. The alloy also demonstrated impact resilence of 89.27J and hardness value of 239 BHN and electrorestivity value of 5.58mm. Tungsten presence in the aluminium bronze system induced a stable reinforcing kappa phase by nucleation mechanism which resulted to enhancement of mechanical properties.
A Modified Congestion Control Algorithm for Evaluating High BDP Networks

Summary It is well known that the TCP congestion control algorithm has been remarkably successful in improving the current TCP/IP function better and efficiently. However, it can perform poorly in networks with high Bandwidth Delay Product (BDP) paths. This paper presents modification to a congestion control algorithm that may help the TCP better utilize the bandwidth provided by huge bandwidth long delay links. It also presents results to show a comparison of the original algorithm.
A Personalized News Recommendation using User Location and News Contents

: Personalized news article recommendation provides interesting articles to a speciﬁc user based on the preference of the user. With increasing use of hand-held devices, the interests of users are not inﬂuenced only by news contents, but also by their location. Therefore, in this paper, we propose a novel topic model to incorporate user location into a user preference for the location-based personalized news recommendation. The proposed model is Spatial Topical Preference Model (STPM). By representing the preference of a user differently according to the location of the user, the model recommends the user appropriate news articles to the user location. For this purpose, we represent geographical topic patterns with a Gaussian distribution. STPM is trained only with the news articles that the user actually reads. As a result, it shows poor performance, when the user reads just a few news articles. This problem of STPM is compensated for by LDA-based user proﬁle that is not affected by user location. Therefore, the ﬁnal proposed model is a combined model of STPM and LDA. In the evaluation of the proposed model, it is shown that STPM reﬂects user locations into news article recommendation well, and the combined model outperforms both STPM and LDA. These experimental results prove that the location-based user preference improves the performance of news article recommendation, and the proposed model incorporates the locational information of users into news recommendation effectively.
Object Detection Using Semantic Segmentation With Fisher Vector

: Image processing is an aspect of computer-science wherein one of the fundamental problems is that of object detection for a given set of images. There are number of existing works which are used for object detection using different methodology. Here in this work a method of segmentation using semantic rules along with feature extraction procedure is used. A separate training and testing phase is carried out wherein during training phase the SVM is trained for the images from the dataset and similarly in testing phase a test image is tested so as to determine the object of interest for given image. In order to detect the object more accurately semantic rules are applied both during training and testing stages
The Study of the Proteolysis of Milk Proteins Obtained By Thermal Calcium Coagulation

The article describes the results of the studies to determine the proteolytic activity of different Lactobacillus helveticus strains used to produce calcium-enriched milk protein concentrates (MPC). A high level of the extraand intracellular proteolytic activity of the crops under study has been established. It has been noted that hydrolysis by proteinases of different strains of Lactobacillus helveticus is almost equal in effectiveness to hydrolysis by the animal enzyme. The molecular weight distribution of the products of the hydrolysis of cow and goat milk proteins by proteolytic enzymes of lactic bacteria has been studied. It has been established that the MPC based on cow milk are split into 7 fractions, while the goat milk-based MPC into five factions. The fractions of αs1-casein and γ-casein are absent in the fermented goat milk-based MPC. It has been established that the Lactobacillus helveticus Н17-18 stain is superior to the Lactobacillus helveticus Н9 stain by proteolytic capacity. It has been noted that the largest number of low molecular weight peptides capable of binding calcium was found in fermented protein clumps based on goat milk.
Perception of Bank Customers towards Banking Corporate Social Responsibility in Vietnam

The financial crisis and consequences has significantly highlighted the need for integration of corporate social responsible (CSR) in the banking business. Banking industry allocates vast amount of funds to emphasis on various CSR strategies in the marketplace. However, there are just few studies investigate how retail bank customers response to different CSR initiatives. The study investigates ASEAN bank customers’ perception towards Corporate Social Responsibilities (CSR) initiatives among three stakeholder groups: customers themselves, community and environment. The sample includes 200 bank customers of major banks in Vietnam. Empirical survey and snowball sampling have been carried out to collect customers’ reactions. As a result, 190 valid questionnaires were employed in reliability test, exploratory factor analysis (EFA), multiple regression and analysis of variance (ANOVA) to examine customer attitude and behavioral intentions toward banking CSR and their choice of banking services. The analysis shows that banking customers are entirely in the favor of CSR initiatives in the banking industry with emphasis on customer centric initiatives.
Analysis of the diterpene rich essential oil of Nepeta clarkei Hooke

The essential oil of Nepeta clarkei obtained by hydrodistillation was analyzed by capillary Gas Chromatography-Mass Spectrometry (GC-MS). The analysis of the oil led to the identification of 20 chemical constituents accounting for 95.3% of the total oil composition. The oil composition was dominated by the presence of diterpenes constituting 74.2% of the total oil composition. The principal components were kaur-16-ene (36.6%), pimara7,15-dien-3-one (19.7%), caryophyllene oxide (14.1%), methyl abietate (5.3%) and manoyl oxide (4.4%).
A Survey Paper on Efficient Utilization of Shortest Path Computation

-Computing constrained shortest paths is fundamental to some important network functions such as QoS routing, which is to find the cheapest path that satisfies certain constraints. In particular, finding the cheapest delayconstrained path is critical for real-time data flows such as voice calls. Because it is NP-complete, much research has been designing heuristic al-gorithms that solve the ε-approximation of the problem with an adjustable accuracy. A common approach is to discretize (i.e., scale and round) the link delay or link cost, which transforms the original problem to a simpler one solvable in polynomial time. The efficiency of the algorithms directly relates to the magnitude of the errors introduced during discretization. In this paper, we propose two techniques that reduce the discretization errors, which allows faster algorithms to be designed. Reducing the overhead of the costly computation for constrained shortest paths is practically important for the design of a high-throughput QoS router, which is limited by both processing power and memory space. Our simulations show that the new algorithms reduce the execution time by an order of magnitude on power-law topologies with 1000 nodes. The reduction in memory space is similar. When there are multiple constraints, the improvement is more dramatic.
Determinants of Piggery Business in Kaduna State, Nigeria

The objective of the study was to examine pig business in Kaduna State, Nigeria. Multi stage and purposive sampling techniques were used in selecting a random sample size of hundred (100) pig producers for the research. A structured questionnaire was administered on respondents for information. Data were analysed using descriptive statistics such as percentages, frequency, gross margin model and Cobb Douglas production function. The result revealed that majority (57%) of respondents involved in pig business were females.Pig business was profitable with a return per naira invested of 0.69 kobo and gross margin of N8,426.30 per pig. The ttest confirmed that pig business was profitable and significant at 1% level. Pig business operated at stage ii of the production function, indicating a decreasing return to scale with summed coefficients of 0.823. The study recommended that government should intervene through the provision of extension services and access to credit facilities.
Experimental Investigation into the Resistance Components of Displacement Trimaran at Various Lateral Spacings

An investigation into the breakdown of resistance components of a displacement trimaran was carried out experimentally using a towing tank. A trimaran model consisting of one main-hull with length of 1.2m and two symmetric side-hulls with length of 0.5m was tested at various configurations between Froude numbers of 0.15 and 0.27 at various lateral spacing (S/L) between 0.2 and 0.5. The experimental investigation was conducted using a towing tank belongs to Institute of Technology Sepuluh Nopember (ITS) at Surabaya. Individual test on each part of trimaran hull was also carried out in order to clarify the interference phenomena between the hulls more clearly. Overall results indicated that the wider the hull separation, the smaller the interference between the hulls. The widest separation (S/L=0.5) indicated that there is nointerference between the hulls and this is in good agremeent with individual test of each hull when interference is neglected. Keywords— trimaran, resistance, tank test, CFD, separation, interference
Effect of Exposure to Mobile Phone Radiations on Human Health-a Review

Widespread utilization of mobile phones and other wireless devices raise the concern about potential health effects related to their uses. It is therefore, required to conduct researches to find out the possible biological health effects due to exposure of cell phone radiations. This review summarizes the health issues based on mobile phone radiations and concludes that regular and long term usage of mobile phone can have bad impact upon biological tissues especially of head and brain.
Object and Feature-Based Scene Classification

— Multimedia is a growing technology which nowadays is applied in our daily lives e.g. in entertainment, news bulletin, military, hospital and many areas of applications. Another aspect is the fast growing trends on machine learning, Nowadays machine are taking over from human and are becoming intelligent day in day out by the changing trends on how we do the retrieval and classification gave us a great urge to explore more on how to classify scenes in the field of object recognition. We propose the use of support vector machine working together with DeCAF [1], this way we will be able to ease the complexity of dealing with big scene categorization. The process of achieving this was by, getting the features of the scene, then do various training by using LSVM (Linear support vector machine) we display our results by using MIT database with several images. Our approach shows it is better than the previous existing ones.
Self monitoring of blood glucose (SMBG) cannot replace HbA1c

The management of diabetes has focussed on achieving normal or nearnormal glycemia, by a multitude of methods, including diet, exercise, oral drugs and insulin. Monitoring of glycemia can be done by checking urine sugar blood glucose through office /laboratory measurements or SMBG, as well as by assessing markers such as hemoglobin A1c (HbA1c), fructosamine or 1,5 anhydroglucitol. This article assesses the advantages of HbA1c as a monitoring tool in diabetes, while highlighting the limitations and short comings of SMBG.
Network Traffic Control Using Distributed Control Plane of Software Defined Networks

The SDN layer generally works as a virtual software switch or router in place of (or in conjunction with) the physical network devices. Traditionally job of managing the traffic is perfo rmed by software embedded in the routers and switches, in SDN it is performed by software from outside the devices. For large scale network environment, centralized control of Software Defined Network (SDN) having a single controller has several issues associated with it such as single point failure, computational complexity growth, reliability and scalability. To solve these issues multi-controller implementation of Software Defined Network has been introduced. In proposed system SDN controllers are deployed in (distributed) tree like structure such that lower level controller is controlled by upper level controller so that all the network is controlled by single SDN controller centrally. Making possible to centralized control over the global view of network with improved architecture will be considered. Distributed control plane architecture equally distributes overall loads among all controllers arranged in distributed manner. It solves single point failure problem.