Logistic Regression Trust–A Trust Model for Internet-of-Things Using Regression Analysis

Internet of Things(IoT)is a popular social network in which devices are virtually connected for communicating and sharing information.This is applied greatly in business enterprises and government sectors for delivering the services to their customers,clients and citizens.But,the interaction is success-ful only based on the trust that each device has on another.Thus trust is very much essential for a social network.As Internet of Things have access over sen-sitive information,it urges to many threats that lead data management to risk.This issue is addressed by trust management that help to take decision about trust-worthiness of requestor and provider before communication and sharing.Several trust-based systems are existing for different domain using Dynamic weight meth-od,Fuzzy classification,Bayes inference and very few Regression analysis for IoT.The proposed algorithm is based on Logistic Regression,which provide strong statistical background to trust prediction.To make our stand strong on regression support to trust,we have compared the performance with equivalent sound Bayes analysis using Beta distribution.The performance is studied in simu-lated IoT setup with Quality of Service(QoS)and Social parameters for the nodes.The proposed model performs better in terms of various metrics.An IoT connects heterogeneous devices such as tags and sensor devices for sharing of information and avail different application services.The most salient features of IoT system is to design it with scalability,extendibility,compatibility and resiliency against attack.The existing worksfinds a way to integrate direct and indirect trust to con-verge quickly and estimate the bias due to attacks in addition to the above features.

SNCDM: Spinal Tumor Detection from MRI Images Using Optimized Super-Pixel Segmentation

Conferring to the American Association of Neurological Surgeons(AANS)survey,85%to 99%of people are affected by spinal cord tumors.The symptoms are varied depending on the tumor’s location and size.Up-to-the-min-ute,back pain is one of the essential symptoms,but it does not have a specific symptom to recognize at the earlier stage.Numerous significant research studies have been conducted to improve spine tumor recognition accuracy.Nevertheless,the traditional systems are consuming high time to extract the specific region and features.Improper identification of the tumor region affects the predictive tumor rate and causes the maximum error-classification problem.Consequently,in this work,Super-pixel analytics Numerical Characteristics Disintegration Model(SNCDM)is used to segment the tumor affected region.Estimating the super-pix-els of the affected region by this method reduces the variance between the iden-tified pixels.Further,the super-pixels are selected according to the optimized convolution network that effectively extracts the vertebral super-pixels features.Derived super-pixels improve the network learning and training process,which minimizes the maximum error classification problem also the efficiency of the system was evaluated using experimental results and analysis.

Sliding wear characteristics of solid lubricant coating on titanium alloy surface modified by laser texturing and ternary hard coatings

Titanium alloys are poor in wear resistance and it is not suitable under sliding conditions even with lubrication because ofits severe adhesive wear tendency.The surface modifications through texturing and surface coating were used to enhance the surfaceproperties of the titanium alloy substrate.Hard and wear resistant coatings such as TiAlN and AlCrN were applied over texturedtitanium alloy surfaces with chromium as interlayer.To improve the friction and wear resisting performance of hard coatings further,solid lubricant,molybdenum disulphide(MoS2),was deposited on dimples made over hard coatings.Unidirectional sliding weartests were performed with pin on disc contact geometry,to evaluate the tribological performance of coated substrates.The tests wereperformed under three different normal loads for a period of40min at sliding velocity of2m/s.The tribological behaviours ofmulti-layer coatings such as coating structure,friction coefficient and specific wear rate were investigated and analyzed.The lowerfriction coefficient of approximately0.1was found at the early sliding stage,which reduces the material transfer and increases thewear life.Although,the friction coefficient increased to high values after MoS2coating was partially removed,substrate was stillprotected against wear by underlying hard composite layer.

User Centric Block-Level Attribute Based Encryption in Cloud Using Blockchains

Cloud computing is a collection of distributed storage Network which can provide various services and store the data in the efficient manner.The advantages of cloud computing is its remote access where data can accessed in real time using Remote Method Innovation(RMI).The problem of data security in cloud environment is a major concern since the data can be accessed by any time by any user.Due to the lack of providing the efficient security the cloud computing they fail to achieve higher performance in providing the efficient service.To improve the performance in data security,the block chains are used for securing the data in the cloud environment.However,the traditional block chain technique are not suitable to provide efficient security to the cloud data stored in the cloud.In this paper,an efficient user centric block level Attribute Based Encryption(UCBL-ABE)scheme is presented to provide the efficient security of cloud data in cloud environment.The proposed approach performs data transaction by employing the block chain.The proposed system provides efficient privacy with access control to the user access according to the behavior of cloud user using Data Level Access Trust(DLAT).Based on DLAT,the user access has been restricted in the cloud environment.The proposed protocol is implemented in real time using Java programming language and uses IBM cloud.The implementation results justifies that the proposed system can able to provide efficient security to the data present in and cloud and also enhances the cloud performance.

Structure and regeneration status of mangrove patches along the estuarine and coastal stretches of Kerala, India

This study presents the structural characteristics and regeneration potential of mangrove patches in the estuarine and coastal areas of Kerala, a tropical maritime state in India. Field surveys were carried out at 46 selected sites during August 2015 to May 2016. In each site, the vegetative structure and regeneration status were assessed using the quadrat method. Altogether 219 quadrates were laid out and a total of 13 true mangrove species, belonging to 5 families and 8 genera, were recorded. The total tree density and stand basal area of the study region was1678.08/ha and 20.33 m^2/ha respectively. The low basal areas indicate the reduced structural development in mangroves. Of the 13 tree species, Avicennia constitutes 56%of the total Important Value Index(IVI) and Avicennia officinalis represents 41% of the IVI in Kerala, followed by Avicennia marina(15%), Rhizophora mucronata(15%),Sonneratia alba(8%) Rhizophora apiculata(7%) and Excoecaria agallocha(7%). The diameter at breast height(DBH) in the study area revealed that 47% of the tree species came under the 1–10 cm DBH class. Total sapling and seedling density in Kerala was 2238.35 and 3232.42 individuals/ha respectively. Density of young plants(seedlings ? saplings) was only 31% greater of tree density and varied from 3–63%, which indicates poor regeneration potential. The Maturity index value(MIV) and complexity index(Ic) value of mangroves were 18.30 and 109.81 respectively. However, the low Ic value(\ 10) observed in seven out of ten coastal districts indicated poor structural development of mangroves in Kerala. Therefore, locationspecific conservation and management measures, guided by the knowledge on spatial distribution and habitat requirements of mangrove varieties should be taken to preserve the mangrove diversity of Kerala.

对印度马德拉斯市污染湿地甲烷排放的人为影响

湿地是大气中甲烷最大的自然来源。科研人员采用密闭室技术,在一年的时间内对马德拉斯(Madras)市被污染的热带海岸湿地的甲烷排放进行了测量。由于污染程度的差异,使得被观测湿地在甲烷排放上表现出了各自的时空变化特性。硫酸盐和盐度对甲烷产生的抑制作用也是本研究项目的内容。研究发现,土壤温度、沉积物含水量、盐度及硫酸盐是影响甲烷排放率的关键自然因素。研究表明,由于Adyar河口生态系统受到人为扰动,使得该地区平均甲烷排放水平约为15.58mg/m^2·h,这明显高于未污染湿地的同类指标(约6.02mg/m^2·h)。在Adyar河汇入孟加拉湾处,由于受到海水的影响,排放指标明显降低(3.27mg/m^2·h)。

Optimization of piezoelectric MEMS process on Sr and La co-doped PZT thin films

Doped lead-zirconate-titanate(PZT)thin films are preferred for the development of micro-electro-mechanical systems(MEMS)-based acoustic sensors because of their inherent higher dielectric and piezoelectric coefficients.Patterning process is used to develop such MEMS devices which is highly complex even for undoped PZT thin films;therefore,the problem is further cumbersome for doped PZT thin films due to the presence of added dopant elements and their associated chemistry.This paper presents patterning of strontium(Sr)and lanthanum(La)co-doped PZT thin film(PSLZT)deposited on platinized silicon substrate using wet and dry etching processes for fabricating a diaphragm structure with thickness of 15-25μm and diameter of 1.4-2 mm,suitable for acoustic sensing applications.The effects of various etching conditions have been studied and the results are reported.It is found that the dry etching is the most suited process for realizing the piezoelectric MEMS structure due to its higher etching resolution.An appreciable etching rate of 260-270 nm/min with smooth vertical sidewalls is achieved.The silicon diaphragm with patterned PSLZT thin film is found to retain more than 80%of its dielectric and piezoelectric coefficients and has a resonance of 1.43 MHz.

An approach to operational risk modeling and estimation of safety levels for deep water work class remotely operated vehicle-A case study with reference to ROSUB 6000

This paper presents a quantitative approach to operational risk modeling and estimation of safety integrity levels,required for the deep water electric work class remotely operated vehicle with reference to ROSUB6000 developed by the National Institute of Ocean Technology,India.ROSUB6000 is used for carrying out bathymetric surveys,gas hydrate surveys,poly-metallic nodule exploration,salvage operations,and meeting emergency response situations.The system is expected to be in operation for a period of 300 h per year,and has to be extremely safe and reliable.Methods and models for the quantitative assessment of operational safety and estimation of safety integrity levels for ROV are seldom available in the deep water intervention industry.The safety instrumented functions implemented in the ROV should be able to meet the SIL requirements of specific mission.This study indicates that the required safety factors are implemented into the design of the state-of-the-art ROV ROSUB 6000,considering IEC 61508/61511 recommendations on Health,Safety and Environment and it is found that the system is able to meet the required SIL for seven identified functions.This paper gives the design and safety engineers in the ROV industry,an overview of the numerical operational risk assessment methods and safety-centered ROV engineering.