iosr-JCE   Volume-23 ~ Issue-4 ~ Jul. - Aug. 2021

Abstract: Over the past decade, the use of the internet has grown to an astonishing extent. It has dominated almost every field of life and it acts as a channel of communication between various walks of life. However, with an amplified penetration of the internet, cybercrimes have also gained significant impetus. In order to implement their illegal activities and achieve illegal objectives, cybercriminals employ online networking. They use online networking devices to connect with any device of another online user and gain illegal profits in terms of finance, publicity or any other personal motive. The main reason behind such blatant violation of law by these cybercriminals is due to the loopholes and vulnerabilities present in the online system. They conveniently exploit these weak links and breach the privacy of online users. Despite......

[1]. Alami, S., & Elbeqqali, O. (2015). Cybercrime profiling: Text mining techniques to detect and predict criminal activities in microblog posts. Paper presented at the 2015 10th International Conference on Intelligent Systems: Theories and Applications (SITA).
[2]. Bahnsen, A. C., Aouada, D., Stojanovic, A., & Ottersten, B. (2016). Feature engineering strategies for credit card fraud detection. Expert Systems with Applications, 51, 134-142.
[3]. Ch, R., Gadekallu, T. R., Abidi, M. H., & Al-Ahmari, A. (2020). Computational system to classify cyber crime offenses using machine learning. Sustainability, 12(10), 4087.
[4]. Chandrakala, T., Rajini, S. N. S., Dharmarajan, K., & Selvam, K. (2020). Development of crime and fraud prediction using data mining approaches. Technology, 11(12), 1450-1470.
[5]. Chitra, K., & Subashini, B. (2013). Data mining techniques and its applications in banking sector. International Journal of Emerging Technology and Advanced Engineering, 3(8), 219-226.

Abstract: Compaction related issues very often lead to construction dispute on site when the test results do not meet the specified requirements. The author was closely involved in extensive research into the material properties that influence the compactability of untreated roadbuilding materials. Untreated materials obtained from all the provinces in South Africa were used in the research. From the 21 sets of density research results obtained, the DENSITY software was developed to try and pinpoint the cause of a compaction problem with untreated material, as well as treated materials such as asphalt and Ordinary Portland Cement (OPC) mixes. The paper briefly explains the extensive research programme that was followed. This is followed by a brief discussion of ten compaction problems that were solved by means of the DENSITY software program.

[1]. Semmelink C.J. 1991. The effect of material properties on the compactability of some untreated roadbuilding materials PhD Thesis.
[2]. Semmelink C.J. and Visser A.T. 1994. Effect of material properties on compactability and bearing capacity. Journal of Transportation Engineering, ASCE, Vol.120, No.4, Jul/Aug 1994. 20p.

Abstract: The paper discusses the conceptual model of the development of Georgian lexicographic system, which is presented in the context of information system projection (design). It describes the elements of the system's framework and their functional purpose. The paper suggests the conceptual framework of the lexicographic information system in the form of diagram and its extended view in relation to databases.

Key Word: Lexicography; dictionary; information systems.

[1]. Tarp S., "Lexicography in the information age," vol. 17, pp. 170-179, 2007.
[2]. Robins K., Webster F., "Technology and education: progress or control," Critical Social Policy, vol. 5, no. 15, pp. 36-61, 1985.
[3]. Tarp S., "Dictionaries in the Internet Era: Innovation or Business as Usual? (Enrique Alcaraz Memorial Lecture 2014)," licante Journal of English Studies, vol. 27, pp. 233-261, 2014.
[4]. Avison D., Guy F., Information Systems Development: Methodologies, Techniques and Tools, 4. ed, Ed., McGraw-Hill, 2006.
[5]. Hewitt B., Georgian: A Structural Reference Grammar., Amsterdam: John Benjamins., 1995.

Abstract: Purpose: Breast cancer is the most common type of cancer in women worldwide, accounting for 25.4% of the total number of new cases diagnosed in 2018. This study investigates the problem of classifying Breast Cancer his- tology images dataset, which is considered a challenging task. The challenge lies in detecting the predominant cancer type in the whole-slide images (WSI). We propose training an ensemble architecture that consists of three convolu- tional neural networks: Inception-v3, Densenet-121 and ResneXt-101 optimized using triplet loss. The three networks showed great performance on medical image processing and analysis. Due to the limited number of images in the training dataset, we used transfer-learning to initialize the weights of our networks. We opted for using the triplet loss during.........

Keywords: Bach challenge, Breast cancer, Deep learning, Histology.

[1]. L. A. Torre, F. Bray, R. L. Siegel, et al., "Global cancer statistics, 2012," CA: A Cancer Journal for Clinicians 65(2), 87–108 (2015).
[2]. C. Desantis, J. Ma, A. Goding Sauer, et al., "Breast cancer statistics, 2017, racial disparity in mortality by state," CA: A Cancer Journal for Clinicians 67 (2017).
[3]. S. Bhattacharjee, J. Mukherjee, S. Nag, et al., "Review on histopathological slide analysis using digital microscopy," International journal of advanced science and technology 62, 65– 96 (2014).
[4]. C. Demir and B. Yener, "Automated cancer diagnosis based on histopathological images : a systematic survey," (2005).
[5]. C. Bergmeir, M. Garcia-Silvente, and J. Ben´ıtez, "Segmentation of cervical cell nuclei in high-resolution microscopic images: A new algorithm and a web-based software framework," Computer methods and programs in biomedicine 107, 497–512 (2012).

Abstract: This work is devoted to the issues of solving the multicriteriaretail marketing problem on the rational choice of the location of retail outlets using the Z-number. Along with other methods that were developed by the authors, the early use of this approach allows a more adequate consideration of the uncertainties inherent in the very problem of choosing the location of a retail outlet, is more practical and requires minimal costs to solve such problems. The paper gives a general algorithm and a numerical example of solving the considered problem.

Keywords: Commercial establishments, retail marketing, multi-criteria decision-making, fuzzy set theory, Znumber

[1]. Methods for selecting the location of a retail outlet [Методывыбораместоположенияторговойточки].https://dis.ru/library/520/25648/ , last accessed on 15.07.2020.
[2]. Hiduke G., RyanJ. D.: Small Business: An Entrepreneur's Business Plan 9th Edition. South-Western College Pub. ( 2013)
[3]. BrizhashevaO.V.: Trade Marketing [Маркетингторговли], UlGTU, Ulyanovsk (2007).
[4]. Alekperov R.B., Salahli V.M: Estimation of Potential Locations of Trade Objects on the Basis of Fuzzy Set Theory. In: Kahraman C., CevikOnar S., Oztaysi B., Sari I., Cebi S., Tolga A. (eds) Intelligent and Fuzzy Techniques: Smart and Innovative Solutions. INFUS 2020. Advances in Intelligent Systems and Computing, vol 1197. Springer, Cham. (2021) https://doi.org/10.1007/978-3-030-51156-2_28

Abstract: A corona virus is a combination of viruses which points at an infecting the respiratory system. Due to COVID-19 pandemic, we are facing a tough time since it causes body illness such as common cold and cough. It is the most contagious disease that can be easily infected from one to hundreds of people within no time. This virus was initially identified and originated in China. The first COVID case was informed by WHO (World Health Organization) and was treated as an Emergency Public Health Issue (EPMC). Nowadays, work culture has already been changing to meet the current time requirements. Wearing a mask is a major aspect in public place, as wearing a mask provides a highest effect in case of viral spread. Body temperature has also become a major consideration in differentiating, an individual is healthy or not. Based on this scenario, temperature verification and checking of.......

Key Word: COVID-19, WHO, EMPC, Corona.

[1] Howard, Andrew G., et al. "Mobilenets: Efficient convolutional neural networks for mobile vision applications." arXiv preprint arXiv:1704.04861 (2017). [2] Sandler, Mark, et al. "Mobilenetv2: Inverted residuals and linear bottlenecks." Proceedings of the IEEE conference on computer vision and pattern recognition. 2018. [3] Ge, Shiming, et al. "Detecting masked faces in the wild with lle-cnns." Proceedings of the IEEE conference on computer vision and pattern recognition. 2017. [4] Gunawan, Teddy Surya, et al. "Prototype design of smart home system using internet of things." Indonesian Journal of Electrical Engineering and Computer Science 7.1 (2017): 107-115. [5] Turk, Matthew A., and Alex P. Pentland. "Face recognition using eigenfaces." Proceedings. 1991 IEEE computer society conference on computer vision and pattern recognition. IEEE Computer Society, 1991.

Abstract: The various biometric traits are used to accurately identify a person. Personal identification is more popular because it is more reliable. Many traits like fingerprint, face, palm print, vein, DNA and many others used personal authentication. Now- a-days finger knuckle surface is used for personal authentication and identification. The texture pattern produced by finger knuckle bending is highly unique and make surface as biometric identifier. The image processing used for recognition of collected data, increasing matching accuracy. The motivation of this topic is to develop system for biometric purpose with high accuracy and with less consuming time. This review papers represents survey on various methods are used for database collection and technique used for recognition.....

[1]. Ajay Kumar, "Personal Authentication Using Finger Knuckle Surface" IEEE Transactions On Information Forensics And Security, Volume(4), No. 1, March 2009.
[2]. Miguel A. Ferrer, Carlos M. Travieso"Using Hand Knuckle texture for biometric identification" IEEE A&E Systems Magazine. June 2006.
[3]. Prof. V. U. Kale, Prof. R. A.Wakode, Rinky L. Batra," Finger Knuckle System for Human Identification: A Literature Survey" ,IJETAE, volume(5),issue 1,january 2015.
[4]. Lin Zhang, "Online finger-knuckle-print verification for personal authentication", Pattern Recognition 43 (2010) 2560–2571.
[5]. Shubhangi Neware, "Finger Knuckle Surface Biometrics", IJETAE, Volume 2, Issue 12, December 2012