We are living in an era of big data, where the process of generating data is continuously been taking place with each coming second. Data that is more varied and extremely complex in structure (unstructured/semi-structured) with problems of indexing, sorting, searching, analyzing and visualizing are major challenges of today's organizations. Big data is always defined by its 5-v characteristics which are Volume, Velocity, Veracity, Variety, and Value. Almost each data model comprising big data is dependent on these 5-v characteristics. A large number of researches have been done on velocity and volume, but the complete and efficient solution for the variety is still not available in the markets. Traditional solutions provided by DBMS generally use multidimensional data type. However, many new data types cannot be compatible with these traditional systems. Big Data is a general problem affecting different fields, whether it is business, economic, social security or scientific research. To analyze huge data sets in order to get insights and find patterns in data is called big data analytics. Big data analytics is the need of every corporate and state of the art organization to look forward and make useful decisions. This paper comprises of discussion on current issues, opportunities, trends, and challenges of big data aimed to discuss variety in more detail. An efficient solution for the big data variety problem will be discussed.

In recent past years, Deep Learning presented an excellent performance in different areas like image recognition, pattern matching, and even in cybersecurity. The Deep Learning has numerous advantages including fast solving complex problems, huge automation, maximum application of unstructured data, ability to give high quality of results, reduction of high costs, no need for data labeling, and identification of complex interactions, but it also has limitations like opaqueness, computationally intensive, need for abundant data, and more complex algorithms. In our daily life, we used many applications that use Deep Learning models to make decisions based on predictions, and if Deep Learning models became the cause of misprediction due to internal/external malicious effects, it may create difficulties in our real life. Furthermore, the Deep Learning training models often have sensitive information of the users and those models should not be vulnerable and expose security and privacy. The algorithms of Deep Learning and machine learning are still vulnerable to different types of security threats and risks. Therefore, it is necessary to call the attention of the industry in respect of security threats and related countermeasures techniques for Deep Learning, which motivated the authors to perform a comprehensive survey of Deep Learning security and privacy security challenges and countermeasures in this paper. We also discussed the open challenges and current issues.

Cloud Technology is a most challenging modern area in the field of modern technologies in which assets (e.g., CPU and capacity) can be rented and discharged by the clients through internet on-demand basis. The cloud computing has been giving virtual computing services to a little, medium and extensive industries, and services, for example, infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Cloud computing has a great combination with the agile software development as a research area. Many researchers worked in Agile Cloud field. The software industries are using the agile methodology for efficient software development need some platform to get quick feedback from the client. Therefore, the agile-cloud is a great combination for it but due to security reasons that directly influence the less adoption of cloud in software industries. This paper reports the survey results of software industries. The total of seven IT industries and many professionals was involved in this paper. However, this paper also contributes and reveals how existing issues can affect agile-cloud adoption for efficient software development. Furthermore, we do not find any type of survey conducted in Pakistan's software industries-related to cloud-agile adoption.INDEX TERMS Agile-cloud computing, industries adoption, challenges and future directions.

With the advent of cloud computing and wireless sensor networks, the number of cyberattacks has rapidly increased. Therefore, the proportionate security of networks has become a challenge for organizations. Information security advisors of organizations face difficult and complex decisions in the evaluation and selection of information security controls that permit the defense of their resources and assets. Information security controls must be selected based on an appropriate level of security. However, their selection needs intensive investigation regarding vulnerabilities, risks, and threats prevailing in the organization as well as consideration of the implementation, mitigation, and budgetary constraints of the organization. The goal of this paper was to improve the information security control analysis method by proposing a formalized approach, i.e., fuzzy Analytical Hierarchy Process (AHP). This approach was used to prioritize and select the most relevant set of information security controls to satisfy the information security requirements of an organization. We argue that the prioritization of the information security controls using fuzzy AHP leads to an efficient and cost-effective assessment and evaluation of information security controls for an organization in order to select the most appropriate ones. The proposed formalized approach and prioritization processes are based on International Organization for Standardization and the International Electrotechnical Commission (ISO/IEC) 27001:2013. But in practice, organizations may apply this approach to any information security baseline manual. Under many contradictory obstacles, the decisions made by humans are not reliable, because the human brain is only capable of evaluating and acting on a limited amount of information at any given moment [17]. To help decision makers solve actual problems for organizations, Thomas Sati (1980) [23] introduced the Analytical Hierarchy Process (AHP). This approach is based on the comparison of pairs between an alternative and a best possible alternative. The strength of the AHP lies in its neutral and logical classification and its flexibility to integrate various functions such as the deployment of quality functions, linear programming, and fuzzy. The benefit of the AHP methodology in conjunction with fuzzy logic is called fuzzy AHP which is the most important method of the multi-criteria decision-making methodology for various types of applications [24]. The fuzzy AHP approach helps to make decisions with various inclinations, fuzziness, and vulnerability. Research has shown the fuzzy AHP philosophy and furthered the supreme utilization of it [25]. It is practical for dealing with uncertainty, complexity, and decision making for complex issues of a controversial nature [26].The structure of the article is as follows: Section 2 is related to the integration of wireless sensor networks with cloud computing. Section 3 reviews previous approaches for the selection of ISCs in organizations. Section 4 presents the AHP, and...

The progress of membrane technology with the development of membranes with controlled parameters led to porous membranes. These membranes can be formed using different methods and have numerous applications in science and technology. Anodization of aluminum in this aspect is an electro-synthetic process that changes the surface of the metal through oxidation to deliver an anodic oxide layer. This process results in a self-coordinated, exceptional cluster of round and hollow formed pores with controllable pore widths, periodicity, and thickness. Categorization in barrier type and porous type films, and different methods for the preparation of membranes, have been discussed. After the initial introduction, the paper proceeds with a brief overview of anodizing process. That engages anodic aluminum oxide (AAO) layers to be used as formats in various nanotechnology applications without the necessity for expensive lithographical systems. This review article surveys the current status of the investigation on AAO membranes. A comprehensive analysis is performed on AAO membranes in applications; filtration, sensors, drug delivery, template-assisted growth of various nanostructures. Their multiple usages in nanotechnology have also been discussed to gather nanomaterials and devices or unite them into specific applications, such as nano-electronic gadgets, channel layers, and clinical platforms tissue designing. From this review, the fact that the specified enhancement of properties of AAO can be done by varying geometric parameters of AAO has been highlighted. No review paper focused on a detailed discussion of multiple applications of AAO with prospects and challenges. Also, it is a challenge for the research community to compare results reported in the literature. This paper provides tables for easy comparison of reported applications with membrane parameters. This review paper represents the formation, properties, applications with objective consideration of the prospects and challenges of AAO applications. The prospects may appeal to researchers to promote the development of unique membranes with functionalization and controlled geometric parameters and check the feasibility of the AAO membranes in nanotechnology and devices.

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Abstract-IEEE802.16 technology due to its outstanding larger coverage area, high data rates, inexpensive equipments, ease of deployment and guaranteed QoS make it a suitable candidate for future broadband wireless access networks. The Mobile WiMAX has been designed to provide Broadband Internet service to mobile users. The VoIP is flexible and provides low cost telephony to customers over the existing IP infrastructure. However, there are still many challenges that need to be addressed to provide a steady and good quality voice connection over the best-effort Internet. In this paper we evaluate the performance of different VoIP codecs over the best effort WiMAX network. The network performance metrics such as jitter, one way delay, and packet loss and user perception metric that is Mean Opinion Score have been used to evaluate the performance of VoIP codecs. The simulation is performed in QualNet simulator with varying values of Packet size, number of calls and jitter buffer sizes. Our results indicate that varying the jitter buffer size and packetization time affects the quality of voice over the best effort network.

In this research article, the authors have discussed the simulation, analysis, and characterization of calcium-doped zinc oxide (Ca-doped-ZnO) nanostructures for advanced generation solar cells. A comparative study has been performed to envisage the effect of Ca-doped ZnO nanoparticles (NP), seeded Ca-doped ZnO nanorods (NR), and unseeded Ca-doped ZnO NR as photoanodes in dye-sensitized solar cells. Simulations were performed in MATLAB fuzzy logic controller to study the effect of various structures on the overall solar cell efficiency. The simulation results show an error of less than 1% in between the simulated and calculated values. This work shows that the diameter of the seeded Ca-doped ZnO NR is greater than that of the unseeded Ca-doped ZnO NR. The incorporation of Ca in the ZnO nanostructure is confirmed using XRD graphs and an EDX spectrum. The optical band gap of the seeded substrate is 3.18 eV, which is higher compared to those of unseeded Ca-doped ZnO NR and Ca-doped ZnO NP, which are 3.16 eV and 3.13 ev, respectively. The increase in optical band gap results in the improvement of the overall solar cell efficiency of the seeded Ca-doped ZnO NR to 1.55%. The incorporation of a seed layer with Ca-doped ZnO NR increases the fill factor and the overall efficiency of dye-sensitized solar cells (DSSC).