A Review of Real World Big Data Processing Structure: Problems and Solutions

Information sort and sum in human culture is developing in astonishing pace which is brought about by rising new administrations as distributed computing, web of things and area-based administrations, the time of enormous information has arrived. As information, has been principal asset, how to oversee and use enormous information better has pulled in much consideration. Particularly, with the advancement of web of things, how to handling huge sum continuous information has turned into an extraordinary test in research and applications. As of late, distributed computing innovation has pulled in much consideration with elite, yet how to utilize distributed computing innovation for substantial scale ongoing information preparing has not been contemplated. This paper concentrated the difficulties of huge information firstly and finishes up every one of these difficulties into six issues. Keeping in mind the end goal to enhance the execution of constant handling of substantial information, this paper manufactures a sort of real-time big data processing (RTDP) design considering the distributed computing innovation and after that proposed the four layers of the engineering, and various leveled figuring model. This paper proposed a multi-level stockpiling model and the LMA-based application organization technique to meet the continuous and heterogeneity necessities of RTDP framework. We utilize DSMS, CEP, group-basedMap Reduce and other handling mode and FPGA, GPU, CPU, ASIC advancements contrastingly to preparing the information at the terminal of information gathering. We organized the information and afterward transfer to the cloud server and Map Reduce the information consolidated with the effective processing abilities cloud design. This paper brings up the general structure for future RTDP framework and computation techniques, is right now the general strategy RTDP framework outline

Secure digital voting system based on blockchain technology

Electronic voting or e-voting has been used in varying forms since 1970s with fundamental benefits over paper based systems such as increased efficiency and reduced errors. However, there remain challenges to achieve wide spread adoption of such systems especially with respect to improving their resilience against potential faults. Blockchain is a disruptive technology of current era and promises to improve the overall resilience of e-voting systems. This paper presents an effort to leverage benefits of blockchain such as cryptographic foundations and transparency to achieve an effective scheme for e-voting. The proposed scheme conforms to the fundamental requirements for e-voting schemes and achieves end-to-end verifiability. The paper presents details of the proposed e-voting scheme along with its implementation using Multichain platform. The paper presents in-depth evaluation of the scheme which successfully demonstrates its effectiveness to achieve an end-to-end verifiable e-voting scheme

Peritumoral cystic meningioma

A case of 39 years old male is described who presented with headache, right-sided focal fits and decreased power in the right hand. CT scan brain showed a left fronto-parietal cystic lesion with centrolateral intramural nodule with homogenous enhancement. At surgery, the extra-axial lesion with cyst containing xanthochromic fluid had a well-defined capsule that could easily be separated from the peri-lesional cortical surface. The dural-based nodule with its cyst wall was resected in toto. The histopathology of mural nodule was reported as meningioma while the cyst wall histology revealed meningothelial cells

Clustering VoIP caller for SPIT identification

The number of unsolicited and advertisement telephony calls over traditional and Internet telephony has rapidly increased over recent few years. Every year, the telecommunication regulators, law enforcement agencies and telecommunication operators receive a very large number of complaints against these unsolicited, unwanted calls. These unwanted calls not only bring financial loss to the users of the telephony but also annoy them with unwanted ringing alerts. Therefore, it is important for the operators to block telephony spammers at the edge of the network so to gain trust of their customers. In this paper, we propose a novel spam detection system by incorporating different social network features for combating unwanted callers at the edge of the network. To this extent the reputation of each caller is computed by processing call detailed records of user using three social network features that are the frequency of the calls between caller and the callee, the duration between caller and the callee and the number of outgoing partners associated with the caller. Once the reputation of the caller is computed, the caller is then places in a spam and non-spam clusters using unsupervised machine learning. The performance of the proposed approach is evaluated using a synthetic dataset generated by simulating the social behaviour of the spammers and the non-spammers. The evaluation results reveal that the proposed approach is highly effective in blocking spammer with 2% false positive rate under a large number of spammers. Moreover, the proposed approach does not require any change in the underlying VoIP network architecture, and also does not introduce any additional signalling delay in a call set-up phase

The financial analysis of nitrogen fertilizers and planting systems and its implications on maize agribusiness: Evidence from Peshawar, Pakistan

Maize is one of the staple foods that supply the world's food demand. The research aims to determine financial analysis of nitrogen fertilizers and planting systems and its implications on maize agribusiness. The research was conducted in experimental design with a split-plot arrangement comprising four replications. Maize plant density as a system treatment was allocated to main plots (65,000; 75,000; and 85,000 plant per ha). Integrated nitrogen was assigned to sub-plots: control; 0% yard manure (YM) + 100% urea; 100% YM + 0% urea; 50% YM + 50% urea; 75% YM + 25% urea; and 25% YM + 75% urea. Data were recorded on plant harvest, harvest index, and R/C ratio. The result showed that integrated N of 50% Farm Yard Manure + 50% urea in 85,000 plant per ha resulted in a higher harvest index of 31.5% and the highest R/C ratio of 6.2 and enhanced yield of 4,219 kg per ha. This yield almost meets the government's expectations. Total cost was 36,961 PKR, total income was 227,941 PKR, and economic net return reached 190,980 PKR. The government can support the maize crops farmers to activate decomposition household's waste to be organic fertilizer in their house and provide the place for decomposition activity in the crops field to fulfill production government target, food security, and environmental health.JEL Classification:  Q01; Q12; Q1

A Process Model for Developing Semantic Web Systems

Abstract: Before the Web era various software development methodologies have been proposed for the development of software applications for different domains. The main objectives of those methodologies were to meet user's requirements, find out means to suggest a systematic software development and reduce the maintenance cost of the developed software. On the emergence of the Web and to develop the web-based software systems, some existing methodologies have been extended. Also, new approaches (or informal methodologies) are introduced for the development of web-based systems because the development process for these systems is not considered as an extension of the classical software engineering, although both development processes for web-based systems and non web-based systems have the same basic objective which is software development. Of course, the development of the web-based systems needs a new kind of development methodologies which should meet and capture their unique and different requirements. Currently available software development methodologies are inappropriate and unsuitable to use for the development of web-based software systems, especially for the third generation web, called Semantic Web. In this paper, we present a brief review of the existing software development methodologies for the development of web-based systems. Some informal software development methodologies (or approaches) for the semantic web are also reviewed. Then, based on this analytical review, we propose a model for the development of semantic web systems. This model can be used as a benchmark to propose formal methodologies for the development of the semantic web systems

A privacy-preserving framework for smart context-aware healthcare applications

Smart connected devices are widely used in healthcare to achieve improved well-being, quality of life, and security of citizens. While improving quality of healthcare, such devices generate data containing sensitive patient information where unauthorized access constitutes breach of privacy leading to catastrophic outcomes for an individual as well as financial loss to the governing body via regulations such as the General Data Protection Regulation. Furthermore, while mobility afforded by smart devices enables ease of monitoring, portability, and pervasive processing, it introduces challenges with respect to scalability, reliability, and context awareness. This paper is focused on privacy preservation within smart context-aware healthcare emphasizing privacy assurance challenges within Electronic Transfer of Prescription. We present a case for a comprehensive, coherent, and dynamic privacy-preserving system for smart healthcare to protect sensitive user data. Based on a thorough analysis of existing privacy preservation models, we propose an enhancement to the widely used Salford model to achieve privacy preservation against masquerading and impersonation threats. The proposed model therefore improves privacy assurance for smart healthcare while addressing unique challenges with respect to context-aware mobility of such applications. © 2019 John Wiley & Sons, Ltd

A novel framework for collaborative intrusion detection for M2M networks

The proliferation of sensor devices has introduced exciting possibilities such as the Internet of Things (IoT). Machine to Machine (M2M) communication underpins efficient interactions within such infrastructures. The resource constraints and ad-hoc nature of these networks have significant implications for security in general and with respect to intrusion detection in particular. Consequently, contemporary solutions mandating a stable infrastructure are inadequate to fulfill these defining characteristics of M2M networks. In this paper, we present COLIDE (COLlaborative Intrusion Detection Engine) a novel framework for effective intrusion detection in the M2M networks without incurring high energy and communication cost on the participating host and edge nodes. The framework is envisioned to address challenges such as flexibility, resource constraints, and the collaborative nature of the M2M networks. The paper presents a detailed system description along with its formal and empirical evaluation using Contiki OS. Our evaluation for different communication scenarios demonstrates that the proposed approach has limited overhead in terms of energy utilization and memory consumption