Search results for: hand gesture classification

Authors: Mahmut Yildirim

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This paper proposed the bidirectional long short-term memory (Bi-LSTM) network-aided deep learning (DL)-based signal detection for Orthogonal frequency division multiplexing with all index modulation (OFDM-AIM), namely Bi-DeepAIM. OFDM-AIM is developed to increase the spectral efficiency of OFDM with index modulation (OFDM-IM), a promising multi-carrier technique for communication systems beyond 5G. In this paper, due to its strong classification ability, Bi-LSTM is considered an alternative to the maximum likelihood (ML) algorithm, which is used for signal detection in the classical OFDM-AIM scheme. The performance of the Bi-DeepAIM is compared with LSTM network-aided DL-based OFDM-AIM (DeepAIM) and classic OFDM-AIM that uses (ML)-based signal detection via BER performance and computational time criteria. Simulation results show that Bi-DeepAIM obtains better bit error rate (BER) performance than DeepAIM and lower computation time in signal detection than ML-AIM.

Keywords: bidirectional long short-term memory, deep learning, maximum likelihood, OFDM with all index modulation, signal detection

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Authors: Orsolya Kegyes-Brassai, Zsolt Szilvágyi, Ákos Wolf, Richard P. Ray

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Local ground conditions have a substantial influence on the seismic response of structures. Their inclusion in seismic hazard assessment and structural design can be realized at different levels of sophistication. However, response results based on more advanced calculation methods e.g. nonlinear or equivalent linear site analysis tend to show significant discrepancies when compared to simpler approaches. This project's main objective was to compare results from several 1-D response programs to Eurocode 8 design spectra. Data from in-situ site investigations were used for assessing local ground conditions at several locations in Hungary. After discussion of the in-situ measurements and calculation methods used, a comprehensive evaluation of all major contributing factors for site response is given. While the Eurocode spectra should account for local ground conditions based on soil classification, there is a wide variation in peak ground acceleration determined from 1-D analyses versus Eurocode. Results show that current Eurocode 8 design spectra may not be conservative enough to account for local ground conditions typical for Hungary.

Keywords: 1-D site response analysis, multichannel analysis of surface waves (MASW), seismic CPT, seismic hazard assessment

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Authors: Moumita Chanda, Md. Fazlul Karim Patwary

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Smoking is one of the most popular recreational drug use behaviors, and it contributes to birth defects, COPD, heart attacks, and erectile dysfunction. To completely eradicate this disease, it is imperative that it be identified and treated. Numerous smoking cessation programs have been created, and they demonstrate how beneficial it may be to help someone stop smoking at the ideal time. A tomography meter is an effective smoking detector. Other wearables, such as RF-based proximity sensors worn on the collar and wrist to detect when the hand is close to the mouth, have been proposed in the past, but they are not impervious to deceptive variables. In this study, we create a machine that can discriminate between smokers and non-smokers in real-time with high sensitivity and specificity by watching and collecting the human lung and analyzing the X-ray data using machine learning. If it has the highest accuracy, this machine could be utilized in a hospital, in the selection of candidates for the army or police, or in university entrance.

Keywords: CNN, smoker detection, non-smoker detection, OpenCV, artificial Intelligence, X-ray Image detection

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Authors: Xiaoxing Ye

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To investigate complex rumen microbial communities, 16S ribosomal RNA (rRNA) sequencing is widely used. Here, we evaluated the impact of bioinformatics pipelines on the observation of OTUs and taxonomic classification of 750 cattle rumen microbial samples by comparing three commonly used pipelines (LotuS, UPARSE, and QIIME) with Usearch. In LotuS-based analyses, 189 archaeal and 3894 bacterial OTUs were observed. The observed OTUs for the Usearch analysis were significantly larger than the LotuS results. We discovered 1495 OTUs for archaea and 92665 OTUs for bacteria using Usearch analysis. In addition, taxonomic assignments were made for the rumen microbial samples. All pipelines had consistent taxonomic annotations from the phylum to the genus level. A difference in relative abundance was calculated for all microbial levels, including Bacteroidetes (QIIME: 72.2%, Usearch: 74.09%), Firmicutes (QIIME: 18.3%, Usearch: 20.20%) for the bacterial phylum, Methanobacteriales (QIIME: 64.2%, Usearch: 45.7%) for the archaeal class, Methanobacteriaceae (QIIME: 35%, Usearch: 45.7%) and Methanomassiliicoccaceae (QIIME: 35%, Usearch: 31.13%) for archaeal family. However, the most prevalent archaeal class varied between these two annotation pipelines. The Thermoplasmata was the top class according to the QIIME annotation, whereas Methanobacteria was the top class according to Usearch.

Keywords: cattle rumen, rumen microbial, 16S rRNA gene sequencing, bioinformatics pipeline

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Authors: S. Jagadeesh Kumar

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This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

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Authors: A. Samer Ezeldin, Jwanda M. El Sarag

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Variation orders are of great importance in any construction project. Variation orders are defined as any change in the scope of works of a project that can be an addition omission, or even modification. This paper investigates the variation orders that occur during construction projects in Egypt. The literature review represents a comparison of causes of variation orders among Egypt, Tanzania, Nigeria, Malaysia and the United Kingdom. A classification of occurrence of variation orders due to owner related factors, consultant related factors and other factors are signified in the literature review. These classified events that lead to variation orders were introduced in a survey with 19 events to observe their frequency of occurrence, and their time and cost impacts. The survey data was obtained from 87 participants that included clients, consultants, and contractors and a database of 42 scenarios was created. A model is then developed to help assist project managers in predicting the frequency of variations and account for a budget for any additional costs and minimize any delays that can take place. Two experts with more than 25 years of experience were given the model to verify that the model was working effectively. The model was then validated on a residential compound that was completed in July 2016 to prove that the model actually produces acceptable results.

Keywords: construction, cost impact, Egypt, time impact, variation orders

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Authors: Fayyaz Rasool, Shakeela Parveen

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The studies on genetic diversity of Labeo rohita by using molecular markers were carried out to investigate the genetic structure by RAPAD marker and the levels of polymorphism and similarity amongst the different groups of five populations of wild and farmed types. The samples were collected from different five locations as representatives of wild and hatchery raised populations. RAPAD data for Jaccard’s coefficient by following the un-weighted Pair Group Method with Arithmetic Mean (UPGMA) for Hierarchical Clustering of the similar groups on the basis of similarity amongst the genotypes and the dendrogram generated divided the randomly selected individuals of the five populations into three classes/clusters. The variance decomposition for the optimal classification values remained as 52.11% for within class variation, while 47.89% for the between class differences. The Principal Component Analysis (PCA) for grouping of the different genotypes from the different environmental conditions was done by Spearman Varimax rotation method for bi-plot generation of the co-occurrence of the same genotypes with similar genetic properties and specificity of different primers indicated clearly that the increase in the number of factors or components was correlated with the decrease in eigenvalues. The Kaiser Criterion based upon the eigenvalues greater than one, first two main factors accounted for 58.177% of cumulative variability.

Keywords: variation, clustering, PCA, wild, hatchery, RAPAD, Labeo rohita

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Authors: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour

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In this work we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.

Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift

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Authors: Belkacem Selma, Boumediene Selma, Tourkia Guerzou, Abbes Labdelli

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Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. The Earthquakes prediction to prevent the loss of human lives and even property damage is an important factor; that is why it is crucial to develop techniques for predicting this natural disaster. This present study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 10^4J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines has been analyzed. The results obtained show that the ANN with high accuracy was able to predict earthquake parameters; the classification accuracy through neural networks is more than 94%, and that the models developed are efficient and robust and depend only weakly on the initial database.

Keywords: earthquake prediction, ANN, seismic bumps

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Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan

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In the food industry high quality production is required within a limited time to meet up with the demand in the society. In this research work, we have developed a model which can be used to replace the human operator due to their low output in production and slow in making decisions as a result of an individual differences in deciding the defective and healthy banana. This model can perform the vision attributes of human operators in deciding if the banana is defective or healthy for food production based. This research work is divided into two phase, the first phase is the image processing where several image processing techniques such as colour conversion, edge detection, thresholding and morphological operation were employed to extract features for training and testing the network in the second phase. These features extracted in the first phase were used in the second phase; the classification system phase where the multilayer perceptron using backpropagation neural network was employed to train the network. After the network has learned and converges, the network was tested with feedforward neural network to determine the performance of the network. From this experiment, a recognition rate of 97% was obtained and the time taken for this experiment was limited which makes the system accurate for use in the food industry.

Keywords: banana, food processing, identification system, neural network

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Authors: Qasim Idrees, Gao Liangtian, Liu Bo, Miao Yiran

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In order to improve the efficiency and accuracy of the pressure hull structure, optimization of underwater vehicle based on response surface methodology, a method for optimizing the design of pressure hull structure was studied. To determine the pressure shell of five dimensions as a design variable, the application of thin shell theory and the Chinese Classification Society (CCS) specification was carried on the preliminary design. In order to optimize variables of the feasible region, different methods were studied and implemented such as Opt LHD method (to determine the design test sample points in the feasible domain space), parametric ABAQUS solution for each sample point response, and the two-order polynomial response for the surface model of the limit load of structures. Based on the ultimate load of the structure and the quality of the shell, the two-generation genetic algorithm was used to solve the response surface, and the Pareto optimal solution set was obtained. The final optimization result was 41.68% higher than that of the initial design, and the shell quality was reduced by about 27.26%. The parametric method can ensure the accuracy of the test and improve the efficiency of optimization.

Keywords: parameterization, response surface, structure optimization, pressure hull

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Authors: Fatma Keskin Arabul, Ibrahim Senol, Ahmet Yigit Arabul, Ali Rifat Boynuegri

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On account of the concern of the fossil fuel is depleting and its negative effects on the environment, interest in alternative energy sources is increasing day by day. However, considering the importance of transportation in human life, instead of oil and its derivatives fueled vehicles with internal combustion engines, electric vehicles which are sensitive to the environment and working with electrical energy has begun to develop. In this study, simulation was carried out for providing energy management and recovering regenerative braking in fuel cell-battery hybrid electric vehicle. The main power supply of the vehicle is fuel cell on the other hand not only instantaneous power is supplied by the battery but also the energy generated due to regenerative breaking is stored in the battery. Obtained results of the simulation is analyzed and discussed.

Keywords: electric vehicles, fuel cell, battery, regenerative braking, energy management

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Authors: Fatma El-Zahraa El-Taher, Ayman Taha, Jane Courtney, Susan Mckeever

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Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions, is critical to decisions such as crossing roads or selecting the safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer the state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset is examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of the detection of intersections in satellite images is evaluated.

Keywords: satellite images, remote sensing images, data acquisition, autonomous vehicles

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Authors: Qing Lyu, Hang Zhu

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Various flows in the network require to go through different types of middlebox. The improper placement of network middlebox and path assignment for flows could greatly increase the network latency and also decrease the performance of network. Minimizing the total end to end latency of all the ows requires to assign path for the incoming flows. In this paper, the flow path assignment problem in regard to the placement of various kinds of middlebox is studied. The flow path assignment problem is formulated to a linear programming problem, which is very time consuming. On the other hand, a naive greedy algorithm is studied. Which is very fast but causes much more latency than the linear programming algorithm. At last, the paper presents a heuristic algorithm named FPA, which takes bottleneck link information and estimated bandwidth occupancy into consideration, and achieves near optimal latency in much less time. Evaluation results validate the effectiveness of the proposed algorithm.

Keywords: flow path, latency, middlebox, network

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Authors: Iftikhar A. Tayubi, Aabdulrahman Alsubhi, Abdullah Althrwi

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The deoxyribonucleic acid text provides a single source of high-quality Cryptography about Deoxyribonucleic acid sequence for structural biologists. We will provide an intuitive, well-organized and user-friendly web interface that allows users to encrypt and decrypt Deoxy Ribonucleic Acid sequence text. It includes complex, securing by using Algorithm to encrypt and decrypt Deoxy Ribonucleic Acid sequence. The utility of this Deoxy Ribonucleic Acid Sequence Text is that, it can provide a user-friendly interface for users to Encrypt and Decrypt store the information about Deoxy Ribonucleic Acid sequence. These interfaces created in this project will satisfy the demands of the scientific community by providing fully encrypt of Deoxy Ribonucleic Acid sequence during this website. We have adopted a methodology by using C# and Active Server Page.NET for programming which is smart and secure. Deoxy Ribonucleic Acid sequence text is a wonderful piece of equipment for encrypting large quantities of data, efficiently. The users can thus navigate from one encoding and store orange text, depending on the field for user’s interest. Algorithm classification allows a user to Protect the deoxy ribonucleic acid sequence from change, whether an alteration or error occurred during the Deoxy Ribonucleic Acid sequence data transfer. It will check the integrity of the Deoxy Ribonucleic Acid sequence data during the access.

Keywords: algorithm, ASP.NET, DNA, encrypt, decrypt

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Authors: S. S. Abdullahi, H. Musa, A. A. Salisu, A. Ismaila, A. H. Birniwa

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In this study the treated and untreated kenaf fiber reinforced unsaturated polyester conventional composites were prepared. Hand lay-up technique was used with dump-bell shaped mold. The kenaf bast fiber was retted enzymatically, washed, dried and combed with a nylon brush. A portion of the kenaf fiber was mercerized and treated with benzoylchloride prior to composite fabrication. Untreated kenaf fiber was also used to prepare the composites to serve as control. The cured composites were subjected to various mechanical testes, such as hardness test, impact test and tensile strength test. The results obtained indicated an increase in all the parameters tested with the fiber treatment. This is because the lignin, hemi-celluloses, pectin and other impurities were removed during alkaline treatment (i.e mercerization). This shows that, the durability of the natural cellulosic fibers to different composite applications can be achieved via fiber treatments.

Keywords: composite, kenaf fibre, reinforce, retted

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Authors: Alexander Harrison Greer, Edward King, Elijah Lee, Safa Obuz, Ruhao Sun, Aditya Sardesai, Toby Ma, Daniel Chow, Bryce Broadus, Calvin Costner, Troy Barnes, Biagio DeSimone, Yeshwin Sankuratri, Yiheng Chen, Holly Golecki

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Although a relatively new field, soft robotics is experiencing a rise in applicability in the secondary school setting through The Soft Robotics Toolkit, shared fabrication resources and a design competition. Exposing students outside of university research groups to this rapidly growing field allows for development of the soft robotics industry in new and imaginative ways. Soft robotic actuators have remained difficult to implement in classrooms because of their relative cost or difficulty of fabrication. Traditionally, a two-part molding system is used; however, this configuration often results in delamination. In an effort to make soft robotics more accessible to young students, we aim to develop a simple, single-mold method of fabricating soft robotic actuators from common household materials. These actuators are made by embedding a soluble polymer insert into silicone. These inserts can be made from hand-cut polystyrene, 3D-printed polyvinyl alcohol (PVA) or acrylonitrile butadiene styrene (ABS), or molded sugar. The insert is then dissolved using an appropriate solvent such as water or acetone, leaving behind a negative form which can be pneumatically actuated. The resulting actuators are seamless, eliminating the instability of adhering multiple layers together. The benefit of this approach is twofold: it simplifies the process of creating a soft robotic actuator, and in turn, increases its effectiveness and durability. To quantify the increased durability of the single-mold actuator, it was tested against the traditional two-part mold. The single-mold actuator could withstand actuation at 20psi for 20 times the duration when compared to the traditional method. The ease of fabrication of these actuators makes them more accessible to hobbyists and students in classrooms. After developing these actuators, they were applied, in collaboration with a ceramics teacher at our school, to a glove used to transfer nuanced hand motions used to throw pottery from an expert artist to a novice. We quantified the improvement in the users’ pottery-making skill when wearing the glove using image analysis software. The seamless actuators proved to be robust in this dynamic environment. Seamless soft robotic actuators created by high school students show the applicability of the Soft Robotics Toolkit for secondary STEM education and outreach. Making students aware of what is possible through projects like this will inspire the next generation of innovators in materials science and robotics.

Keywords: pneumatic actuator fabrication, soft robotic glove, soluble polymers, STEM outreach

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Authors: Akbar Esmaeili, Fateme Dadashi

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Bismuth can increase radiation and reduce the dose of radiotherapy. On the other hand, hyaluronic acid plays a role in healing damaged cells, and melittin has been used to destroy cancer cells. This research aims to destroy eye cancer cells and accelerate the recovery of damaged healthy cells during treatment. In this research, we used this nanoparticle, the sol-gel method. According to the optimization process that was carried out, we obtained the optimal value of the desired variables for the manufacture of nanoparticles. The advantage of doing this is reducing the amount of medicine used, as a result of reducing the number of side effects during the treatment and using melittin as an anti-eye cancer drug and the presence of hyaluronic acid to accelerate the recovery of cells, as well as coating the bismuth nanoparticle with chitosan to increase the half-life of the nanoparticle and prevent its adhesion.

Keywords: synthesis, nanoparticles, coated, cancer

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Authors: Tom D. Gedeon, Ujala Rampaul

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The evaluation of electronic consumer goods are most often done from the perspective of analysing the latest models, comparing their advantages and disadvantages with respect to price. This style of evaluation is often performed by one or a few product experts on a wide range of features that may not be applicable to each user. We instead used a scenario-based approach to evaluate a number of e-readers. The setting is similar to a user who is interested in a new product or technology and has allocated a limited budget. We evaluate the quality and usability of e-readers available within that budget range. This is based on the assumption of a rational market which prices older second hand devices the same as functionally equivalent new devices. We describe our evaluation and comparison of four branded eReaders, as the initial stage of a larger project. The scenario has a range of tasks approximating a busy person who does not bother to read the manual. We found that navigation within books to be the most significant differentiator between the eReaders in our scenario based evaluation process.

Keywords: eReader, scenario based, price comparison, Kindle, Kobo, Nook, Sony, technology adoption

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Authors: Ahmed A. D. Sarhan, S. R. Besharaty, Javad Akbaria, M. Hamdi

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The capability of CNC gantry milling machines in manufacturing long components has caused the expanded use of such machines. On the other hand, the machines’ gantry rigidity can reduce under severe loads or vibration during operation. Indeed, the quality of machining is dependent on the machine’s dynamic behavior throughout the operating process. For this reason, this type of machines has always been used prudently and are non efficient. Therefore, they can usually be employed for rough machining and may not produce adequate surface finishing. In this paper, a CNC gantry milling machine with the potential to produce good surface finish has been designed and analyzed. The lowest natural frequency of this machine is 202 Hz at all motion amplitudes with a full range of suitable frequency responses. Meanwhile, the maximum deformation under dead loads for the gantry machine is 0.565µm, indicating that this machine tool is capable of producing higher product quality.

Keywords: frequency response, finite element, gantry machine, gantry design, static and dynamic analysis

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Authors: Sai Charan Kamana, Harsha Vardhan Nakkina, B.R. Chandavarkar

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In a highly secure and robust key generation process, a key role is played by randomness and random numbers when current real-world cryptosystems are observed. Most of the present-day cryptographic protocols depend upon the Random Number Generators (RNG), Pseudo-Random Number Generator (PRNG). These protocols often use noisy channels such as Disk seek time, CPU temperature, Mouse pointer movement, Fan noise to obtain true random values. Despite being cost-effective, these noisy channels may need additional hardware devices to continuously communicate with them. On the other hand, Hash functions are Pseudo-Random (because of their requirements). So, they are a good replacement for these noisy channels and have low hardware requirements. This paper discusses, some of the key generation methodologies, and their drawbacks. This paper explains how hash functions can be used in key generation, how to combine Key Derivation Functions with hash functions.

Keywords: key derivation, hash based key derivation, password based key derivation, symmetric key derivation

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Authors: Shunichiro Morishita

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This study examines the factors for attracting foreign guests in the Japanese lodging industry and discusses some measures taken for accepting foreign guests. It reviews three different accommodation providers acclaimed highly by foreign guests, Yamashiroya, Sawanoya and Fuji-Hakone Guest House, and identifies their characteristics. The common points for attracting foreign guests were: 1) making the best use of the old facilities, 2) multilingual signs, guidance and websites, 3) necessary and sufficient communication in English, 4) events and opportunities to experience Japanese culture, 5) omotenashi, warm and homely Japanese hospitality. These findings indicate that foreign guests’ dissatisfaction level can be decreased through internationalization utilizing ICT and by offering multilingual support. On the other hand, their satisfaction level can be increased by encouraging interaction with other guests and local Japanese people, providing events and opportunities to experience Japanese culture and omotenashi, home-style Japanese hospitality.

Keywords: hospitality management, foreign guests, Japanese lodging industry, Omotenashi

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Authors: Emon Chairote, Panatda Jannoey, Griangsak Chairote

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A strain of Monascus purpureus CMU001 was used to prepared red yeast rice from Thai glutinous rice Korkor 6 (RD 6). Adding of different amounts of histidine (156, 312, 625, and 1250 mg in 100 g of rice grains)) under aerobic and air limitation (air-lock) condition were used in solid fermentation. Determination of the yield as well as monacolin K content was done. Citrinin content was also determined in order to confirm the safety use of prepared red yeast rice. It was found that under air-lock condition with 1250 mg of histidine addition gave the highest yield of 37.40 g of dried red yeast rice prepared from 100 g of rice. Highest 5.72 mg content of monacolin K was obtained under air-lock condition with 312 mg histidine addition. In the other hand, citrinin content was found to be less than 24462 ng/g of all dried red yeast rice samples under the experimental methods used in this work.

Keywords: red yeast rice, Thai glutinous rice, monacolin K., citrinin

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Authors: Kaltume Kabir Sharrif

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Teacher education is the bedrock of educational growth and development of any nation. With development in education all human problems can be overcome. Educational Psychology, on the other hand, is in a strategic position for any programme in teacher education to be successful hence other aspects of societal issues. In other words, no teacher education can be of any help in ensuring transformation and security without adequate study in Educational Psychology. Without adequate knowledge and skills in Educational Psychology the teacher may not function effectively in the course of discharging his duty. It is in view of this, that the paper discusses some aspects of Educational Psychology that are of paramount importance in teacher education for sustainable transformation and security of Nigeria. Some recommendations were offered on the role educational psychology play in resolving security challenges facing the country. These include enriching educational psychology with topics from forensic psychology that will provide the teacher the skills of fighting crime in the school, Behavioural Science Unit should be established in each school to monitor the behavior of students, among others.

Keywords: transformation, security challenges, teacher education, educational psychology

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Authors: Rashid Mahmood, Muhammad Sufyan, Nasir Ahmed

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The MANETs have lessened transportation and decentralized network. There are numerous basis of routing protocols. We derived the MANETs protocol into three major categories like Reactive, Proactive and hybrid. In these protocols, we discussed only some protocols like Distance Sequenced Distance Vector (DSDV), Ad hoc on Demand Distance Vector (AODV) and Dynamic Source Routing (DSR). The AODV and DSR are both reactive type of protocols. On the other hand, DSDV is proactive type protocol here. We compare these routing protocols for network security estimated by network simulator (NS-2). In this dissertation some parameters discussed such as simulation time, packet size, number of node, packet delivery fraction, push time and speed etc. We will construct all these parameters on routing protocols under suitable conditions for network security measures.

Keywords: DSDV, AODV, DSR NS-2, PDF, push time

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Authors: Luna Shamieh

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Various players are part of the game in an asymmetric war, all making efforts to provide human security to their own adherents. Although a fragile state is not able to provide sufficient and comprehensive services, it still provides special services and security to the elite; the insurgents as well provide services and security to their associates. The humanitarian organisations, on the other hand, provide some fundamental elements of human security, but only in the regions, they are able to access when possible (if possible). The counterinsurgents (security forces of the state and intervention forces) operate within a narrow band defined by the vision of the responsibility to protect and the perspective of the resolution of the conflict through combat; hence, the possibility to provide human security is shaken at this end. This article examines how each player provides human security from the perspective of freedom from want in order to secure basic and strategic needs, freedom from fear through providing protection against all kinds of violence, and the freedom to live in dignity. It identifies a vicious cycle caused by the intervention of the different players causing a centrifugal force that may lead to disintegration of the nation under war.

Keywords: asymmetric war, counterinsurgency, fragile state, human security, insurgency

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Authors: Md. Fazlul Karim, Ahmad Izani Md. Ismail, Mohammed Ashaque Meah

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This paper focuses on the development of a 2-D Boundary Fitted and Nested Grid (BFNG) model to compute the tsunami propagation of Indonesian tsunami 2004 along the coastal region of Penang in Peninsular Malaysia. In the presence of a curvilinear coastline, boundary fitted grids are suitable to represent the model boundaries accurately. On the other hand, when large gradient of velocity within a confined area is expected, the use of a nested grid system is appropriate to improve the numerical accuracy with the least grid numbers. This paper constructs a shallow water nested and orthogonal boundary fitted grid model and presents computational results of the tsunami impact on the Penang coast due to the Indonesian tsunami of 2004. The results of the numerical simulations are compared with available data.

Keywords: boundary fitted nested model, tsunami, Penang Island, 2004 Indonesian Tsunami

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Authors: Luis Fonseca, Filipe Cabral Pinto, Susana Sargento

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The increase of the world population, especially in large urban centers, has resulted in new challenges particularly with the control and optimization of public safety. Thus, in the present work, a solution is proposed for the prediction of criminal occurrences in a city based on historical data of incidents and demographic information. The entire research and implementation will be presented start with the data collection from its original source, the treatment and transformations applied to them, choice and the evaluation and implementation of the Machine Learning model up to the application layer. Classification models will be implemented to predict criminal risk for a given time interval and location. Machine Learning algorithms such as Random Forest, Neural Networks, K-Nearest Neighbors and Logistic Regression will be used to predict occurrences, and their performance will be compared according to the data processing and transformation used. The results show that the use of Machine Learning techniques helps to anticipate criminal occurrences, which contributed to the reinforcement of public security. Finally, the models were implemented on a platform that will provide an API to enable other entities to make requests for predictions in real-time. An application will also be presented where it is possible to show criminal predictions visually.

Keywords: crime prediction, machine learning, public safety, smart city

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Authors: Khaled Nagaty, Heba Nagaty, Gerard McKee

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A signature is a behavioral biometric that is used for authenticating users in most financial and legal transactions. Signatures can be easily forged by skilled forgers. Therefore, it is essential to verify whether a signature is genuine or forged. The aim of any signature verification algorithm is to accommodate the differences between signatures of the same person and increase the ability to discriminate between signatures of different persons. This work presented in this paper proposes an automatic signature verification system to indicate whether a signature is genuine or not. The system comprises four phases: (1) The pre-processing phase in which image scaling, binarization, image rotation, dilation, thinning, and connecting ridge breaks are applied. (2) The feature extraction phase in which global and local features are extracted. The local features are minutiae points, curvature orientation, and curve plateau. The global features are signature area, signature aspect ratio, and Hu moments. (3) The post-processing phase, in which false minutiae are removed. (4) The classification phase in which features are enhanced before feeding it into the classifier. k-nearest neighbors and support vector machines are used. The classifier was trained on a benchmark dataset to compare the performance of the proposed offline signature verification system against the state-of-the-art. The accuracy of the proposed system is 92.3%.

Keywords: signature, ridge breaks, minutiae, orientation

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Authors: Armine Vahanyan

Abstract:

Humanity has been still coping with the new COVID-19 pandemic. Healthcare providers, economists, psychologists, and other specialists speak about the impact of the virus on different spheres of our life. In the list of similar discussions, the impact of pandemics on global education is of utmost importance. Ideally, providing quality education services should be crucial, and the ways education programs are being adapted will determine the success or failure of the service providers. The paper aims to summarize the research touching upon the current situation of higher education in Armenia. The research includes data from official reports, surveys among education leads, faculty, and students, as well as personal observations and consideration. Through descriptive analysis, the findings of the research are being presented from various aspects. Interim results of the research unveiled two major issues in the sector of higher education in Armenia. On the one hand, the entire compulsory digitization of instruction, assessment, and grading has evoked serious gaps related to the lack of technical competencies. There is an urgent need for professional development programs that will address most of the concerns due to the shift to the online instruction mode. On the other hand, online teaching and learning require revision and adaptation of the existing curricula. Given that the content of certain programs may not be compromised, the teaching methods, the assignments, and evaluation require profound transformation, which will still be in line with course learning outcomes and student learning outcomes. The given paper focuses on the ways the mentioned issues are being addressed in Armenia. The extent of commitment for changes and adaptability to the new situation varies from the government-funded and private universities. In particular, the paper compares and contrasts activities and measures taken at the Armenian State Pedagogical University and the American University of Armenia. Thus, the Pedagogical University focused on the use of Google Classroom as the only means for teaching and learning as well as adopted the compulsory synchronous instruction mode. The American University, on the contrary, kept practicing the academic freedom, enabling both synchronous and asynchronous instruction modes, ensuring alignment of the course learning outcomes and student learning outcomes. The State University utilized the assignments and assessment, which would work for the on-campus instruction mode, while the American university employed a variety of assignments applicable for online teaching mode. The latter has suggested the utilization of multiple apps, internet sources, and online library access for a better online instant. Discussions with faculty through online forums and/or professional development workshops also facilitate restructuring and adaptation of the courses. Finally, the paper will synthesize the results of the undertaken research and will outline the e-learning perspectives and opportunities boosted by the known devastating healthcare issue.

Keywords: assessment, compulsory digitization of education services, online teaching, instruction mode, program restructuring

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