Improved Hybrid Deep Collaborative Filtering Approach for True Recommendations

Recommendation services become an essential and hot research topic for researchers nowadays.Social data such asReviews play an important role in the recommendation of the products.Improvement was achieved by deep learning approaches for capturing user and product information from a short text.However,such previously used approaches do not fairly and efficiently incorporate users’preferences and product characteristics.The proposed novel Hybrid Deep Collaborative Filtering(HDCF)model combines deep learning capabilities and deep interaction modeling with high performance for True Recommendations.To overcome the cold start problem,the new overall rating is generated by aggregating the Deep Multivariate Rating DMR(Votes,Likes,Stars,and Sentiment scores of reviews)from different external data sources because different sites have different rating scores about the same product that make confusion for the user to make a decision,either product is truly popular or not.The proposed novel HDCF model consists of four major modules such as User Product Attention,Deep Collaborative Filtering,Neural Sentiment Classifier,and Deep Multivariate Rating(UPA-DCF+NSC+DMR)to solve the addressed problems.Experimental results demonstrate that our novel model is outperforming state-of-the-art IMDb,Yelp2013,and Yelp2014 datasets for the true top-n recommendation of products using HDCF to increase the accuracy,confidence,and trust of recommendation services.

SDN Based DDos Mitigating Approach Using Traffic Entropy for IoT Network

The Internet of Things(IoT)has been widely adopted in various domains including smart cities,healthcare,smart factories,etc.In the last few years,the fitness industry has been reshaped by the introduction of smart fitness solutions for individuals as well as fitness gyms.The IoT fitness devices collect trainee data that is being used for various decision-making.However,it will face numerous security and privacy issues towards its realization.This work focuses on IoT security,especially DoS/DDoS attacks.In this paper,we have proposed a novel blockchain-enabled protocol(BEP)that uses the notion of a self-exposing node(SEN)approach for securing fitness IoT applications.The blockchain and SDN architectures are employed to enhance IoT security by a highly preventive security monitoring,analysis and response system.The proposed approach helps in detecting the DoS/DDoS attacks on the IoT fitness system and then mitigating the attacks.The BEP is used for handling Blockchain-related activities and SEN could be a sensor or actuator node within the fitness IoT system.SEN provides information about the inbound and outbound traffic to the BEP which is used to analyze the DoS/DDoS attacks on the fitness IoT system.The SENcalculates the inbound and outbound traffic features’entropies and transmits them to the Blockchain in the form of transaction blocks.The BEP picks the whole mined blocks’transactions and transfers them to the SDN controller node.The controller node correlates the entropies data of SENs and decides about the DoS or DDoS attack.So,there are two decision points,one is SEN,and another is the controller.To evaluate the performance of our proposed system,several experiments are performed and results concerning the entropy values and attack detection rate are obtained.The proposed approach has outperformed the other two approaches concerning the attack detection rate by an increase of 11%and 18%against Approach 1 and Approach 2 respectively.

Synthesis and characterization of poppy seed oil methyl esters

Response surface methodology(RSM) was used to determine the optimum conditions of the methanolysis of crude poppy seed oil using Na OCH3 as catalyst. The experiments were run according to five levels, four variable central composite rotatable design(CCRD) using RSM. The reaction variables, i.e., molar ratio of methanol/oil(3:1–9:1), catalyst concentration(0.5 wt%–1.25 wt% Na OCH3), reaction temperature(25–65 °C), and reaction time(20–90 min) were studied. We demonstrated that the molar ratio of methanol/oil, catalyst concentration,and reaction temperature were the significant parameters affecting the yield of poppy seed oil methyl esters(PSOMEs). The optimum transesterification reaction conditions, established using the RSM, which offered a89.35% PSOME yield, were found to be 7.5:1 molar ratio of methanol/oil, 0.75% catalyst concentration, 45 °C reaction temperature, and 90 min reaction time. The proposed process provided an average biodiesel yield of more than 85%. A linear correlation was constructed between the observed and predicted values of the yield.The gas chromatography(GC) analyses have shown that PSOMEs contain linoleic-, oleic-, palmitic-, and stearic-acids as main fatty acids. The FTIR spectrum of the PSOMEs was also analyzed to confirm the completion of the transesterification reaction. The fuel properties of the PSOMEs were discussed in light of biodiesel standards(ASTM D 6751 and EN 14214).

Blockchain Based Secured Load Balanced Task Scheduling Approach for Fitness Service

In recent times,the evolution of blockchain technology has got huge attention from the research community due to its versatile applications and unique security features.The IoT has shown wide adoption in various applications including smart cities,healthcare,trade,business,etc.Among these applications,fitness applications have been widely considered for smart fitness systems.The users of the fitness system are increasing at a high rate thus the gym providers are constantly extending the fitness facilities.Thus,scheduling such a huge number of requests for fitness exercise is a big challenge.Secondly,the user fitness data is critical thus securing the user fitness data from unauthorized access is also challenging.To overcome these issues,this work proposed a blockchain-based load-balanced task scheduling approach.A thorough analysis has been performed to investigate the applications of IoT in the fitness industry and various scheduling approaches.The proposed scheduling approach aims to schedule the requests of the fitness users in a load-balanced way that maximize the acceptance rate of the users’requests and improve resource utilization.The performance of the proposed task scheduling approach is compared with the state-of-the-art approaches concerning the average resource utilization and task rejection ratio.The obtained results confirm the efficiency of the proposed scheduling approach.For investigating the performance of the blockchain,various experiments are performed using the Hyperledger Caliper concerning latency,throughput,resource utilization.The Solo approach has shown an improvement of 32%and 26%in throughput as compared to Raft and Solo-Raft approaches respectively.The obtained results assert that the proposed architecture is applicable for resource-constrained IoT applications and is extensible for different IoT applications.

Effectively Handling Network Congestion and Load Balancing in Software-Defined Networking

The concept of Software-Defined Networking(SDN)evolves to overcome the drawbacks of the traditional networks with Internet Protocol(I.P.)packets sending and packets handling.The SDN structure is one of the critical advantages of efficiently separating the data plane from the control plane tomanage the network configurations and network management.Whenever there aremultiple sending devices inside the SDNnetwork,theOpenFlow switches are programmed to handle the limited number of requests for their interface.When the recommendations are exceeded from the specific threshold,the load on the switches also increases.This research article introduces a new approach named LBoBS to handle load balancing by adding the load balancing server to the SDN network.Besides,it is used to maximize SDN’s reliability and efficiency.It also works in coordination with the controller to effectively handle the load balancing policies.The load balancing server is implemented to manage the switches load effectively.Results are evaluated on the NS-3 simulator for packet delivery,bandwidth utilization,latency control,and packet decision ratios on the OpenFlow switches.It has been found that the proposed method improved SDN’s load balancing by 70%compared to the previous state-of-the-art methods.

OILCROP-SUN Model Relevance for Evaluation of Nitrogen Management of Sunflower Hybrids in Sargodha, Punjab

The experiments were conducted to evaluate the performance of crop system (DSSAT) OILCROP-SUN model simulating growth & development and achene yield of sunflower hybrids in response to nitrogen under irrigated conditions in semi arid environment, Sargodha, Punjab. The model was evaluated with observed data collected in trials which were conducted during spring season in 2010 and 2011 in Sargodha, Punjab, Pakistan. Split plot design was used in layout of experiment with three replications. The hybrids (Hysun-33 & S-278) and N levels (0, 75, 150 and 225 kg.ha-1) were allotted in main and sub plots, respectively. The OILCROP-SUN model showed that the model was able to simulate growth and yield of sunflower with an average of 10.44 error% between observed and simulated achene yield (AY). The results of simulation analysis indicated that nitrogen rate of 150 kg.N.ha-1 (N3) produced the highest yield as compared to other treatments. Furthermore, the economic analysis through mean Gini Dominance also showed the dominance of this treatment compared to other treatment combinations. Thus management strategy consisting?of treatment 150 kg.N.ha-1 was the best for high yield of sunflower hybrids.

Vertex-Edge Degree Based Indices of Honey Comb Derived Network

Chemical graph theory is a branch of mathematics which combines graph theory and chemistry.Chemical reaction network theory is a territory of applied mathematics that endeavors to display the conduct of genuine compound frameworks.It pulled the research community due to its applications in theoretical and organic chemistry since 1960.Additionally,it also increases the interest the mathematicians due to the interesting mathematical structures and problems are involved.The structure of an interconnection network can be represented by a graph.In the network,vertices represent the processor nodes and edges represent the links between the processor nodes.Graph invariants play a vital feature in graph theory and distinguish the structural properties of graphs and networks.In this paper,we determined the newly introduced topological indices namely,first ve-degree Zagreb?index,first ve-degree Zagreb?index,second ve-degree Zagreb index,ve-degree Randic index,ve-degree atom-bond connectivity index,ve-degree geometric-arithmetic index,ve-degree harmonic index and ve-degree sum-connectivity index for honey comb derived network.In the analysis of the quantitative structure property relationships(QSPRs)and the quantitative structure-activity relationships(QSARs),graph invariants are important tools to approximate and predicate the properties of the biological and chemical compounds.Also,we give the numerical and graphical representation of our outcomes.

On Edge Irregular Reflexive Labeling of Categorical Product of Two Paths

Among the huge diversity of ideas that show up while studying graph theory,one that has obtained a lot of popularity is the concept of labelings of graphs.Graph labelings give valuable mathematical models for a wide scope of applications in high technologies(cryptography,astronomy,data security,various coding theory problems,communication networks,etc.).A labeling or a valuation of a graph is any mapping that sends a certain set of graph elements to a certain set of numbers subject to certain conditions.Graph labeling is a mapping of elements of the graph,i.e.,vertex and for edges to a set of numbers(usually positive integers),called labels.If the domain is the vertex-set or the edge-set,the labelings are called vertex labelings or edge labelings respectively.Similarly,if the domain is V(G)[E(G)],then the labeling is called total labeling.A reflexive edge irregular k-labeling of graph introduced by Tanna et al.:A total labeling of graph such that for any two different edges ab and a'b'of the graph their weights has wt_(x)(ab)=x(a)+x(ab)+x(b) and wt_(x)(a'b')=x(a')+x(a'b')+x(b') are distinct.The smallest value of k for which such labeling exist is called the reflexive edge strength of the graph and is denoted by res(G).In this paper we have found the exact value of the reflexive edge irregularity strength of the categorical product of two paths (P_(a)×P_(b))for any choice of a≥3 and b≥3.

Unsteady Incompressible Couette Flow Problem for the Eyring-Powell Model with Porous Walls

This work is concerned with the influence of uniform suction or injection on unsteady incompressible Couette flow for the Eyring-Powell model. The resulting unsteady problem for horizontal velocity field is solved by means of homotopy analysis method (HAM). The characteristics of the horizontal velocity field and wall shear stress are analyzed and discussed. Pade approximants and Taylor polynomials are also found for velocity profile and are used to make the maximum error as small as possible. The graphs of the error for the Pade approximation and Taylor approximation are drawn and discussed. Convergence of the series solution is also discussed with the help of h-curve and interval of convergence is also found.

Biofunctional Mg coating on PEEK for improving bioactivity

High purity Mg was successfully coated on polyetheretherketone(PEEK)by vapor deposition method in order to improve the bioactivity including antibacterial property of PEEK implant.The morphology and elemental composition of the coating were characterized by scanning electron microscopy(SEM)and energy-dispersive spectroscopy(EDS),showing that the coating was mainly composed of Mg at deposition temperature of 175
C,185
C,200
C and 230
C.The higher the substrate temperature was,the larger the Mg particle size was.The coating degraded and gradually peeled off from the surface of PEEK after up to 21 days'immersion.It was found that the degradation of Mg coating could strongly kill Staphylococcus aureus with antibacterial rate reaching to 99%.Mg can be expected to be coated on those bio-inert biomaterials to offer specific bioactivities.

Modification of colorimetric method based digital soil test kit for determination of macronutrients in oil palm plantation

It is the need of time that oil palm farmers must perform the spatially planned soil analysis to know about the fertilizer sufficient and deficient zones of land.Colorimetric method is a suitable and fast solution of soil analysis for NPK determination using the digital soil test kit.NPK determination procedure with a digital soil test kit was undefined for oil palm.Furthermore,the digital soil test kit determines the passage of light through an opaque medium of soil solution with a specified reagent.Therefore,environmental light may interfere leading to wrong results of NPK measurement.Likewise,this equipment was non-incorporable with the controller of any VRT fertilizer applicator.In this research,these issues were addressed and the NPK measurement procedure was defined for oil palm plantation by modifying the‘soil to water’ratio in sample soil solution with an optimum environmental light range of 18-23 W/m^(2).‘Soil to water’ratios were found for nitrogen,phosphorus and potassium as 0.31 to 5.00,1.00 to 5.00 and 4.50 to 5.00,respectively to fit the requirement of NPK for oil palm in the prescribed range of the equipment.Validation study of modified digital soil test kit showed that 91.7%N,89.6%P and 93.8%K results of modified digital soil test kit were matched with analytical laboratory method.Thus,the reliability of NPK results using digital soil test kit was enhanced,making the kit incorporable with the controller of variable rate fertilizer applicator through remote monitoring based data acquisition system.The outcome of this research can be used in the development of an IoT network data fusion for dynamic assessment of the NPK variation in the soil and nutrient management in oil palm plantations.

Application of GIS for the identification and demarcation of selective heavy metal concentrations in the urban groundwater

Groundwater is the most appropriate and widely used source of drinking water, which is increasingly threatened by pollution from industrial and agricultural activities. To check the severity of the problem, 156 groundwater samples were collected from various depths （60-110 ft） of 52 different localities in Faisalabad city, the third largest metropolis in Pakistan, and analyzed for the metals （Zn, Cu, Cd, Ni, Pb, Mn and Fe） concentration in 2009. Quantification was done by using Flame Atomic Absorption Spectrophotometer technique and the results were compared with WHO standards for drinking water quality. Results showed that the levels of Cu, Mn and Fe were below the WHO standards while the concentrations of Zn, Cd, Ni and Pb were above the recommended levels of safe drinking water. Correlation analysis among the occurrence of these heavy metals revealed a highly significant and positive correlation of Mn with Zn and Fe. A significant and positive correlation of Cd was also found with Cu and groundwater depth showing that there is strong association between Cu-Cd pair and that the Cd concentration varies with depth of groundwater in the study area. Regional patterns of heavy metals occurrence were mapped using Geographical Information System （GIS） for the identification and demarcation of risk areas. The concentration maps may be used by policymakers of the city to mitigate groundwater pollution.