Cost Benefit Analysis: Evaluation among the Millimetre Wavebands and SHF Bands of Small Cell 5G Networks

This article discusses the benefit cost analysis aspects of millimetre wavebands (mmWaves) and Super High Frequency (SHF). The devaluation along the distance of the carrier-to-noise-plus-interference ratio with the coverage distance is assessed by considering two different path loss models, the two-slope urban micro Line-of-Sight (UMiLoS) for the SHF band and the modified Friis propagation model, for frequencies above 24 GHz. The equivalent supported throughput is estimated at the 5.62, 28, 38, 60 and 73 GHz frequency bands and the influence of carrier-to-noise-plus-interference ratio in the radio and network optimization process is explored. Mostly owing to the lessening caused by the behaviour of the two-slope propagation model for SHF band, the supported throughput at this band is higher than at the millimetre wavebands only for the longest cell lengths. The benefit cost analysis of these pico-cellular networks was analysed for regular cellular topologies, by considering the unlicensed spectrum. For shortest distances, we can distinguish an optimal of the revenue in percentage terms for values of the cell length, R ≈ 10 m for the millimeter wavebands and for longest distances an optimal of the revenue can be observed at R ≈ 550 m for the 5.62 GHz. It is possible to observe that, for the 5.62 GHz band, the profit is slightly inferior than for millimetre wavebands, for the shortest Rs, and starts to increase for cell lengths approximately equal to the ratio between the break-point distance and the co-channel reuse factor, achieving a maximum for values of R approximately equal to 550 m.

Variable vs. Fixed Window Width Code Correlation Reference Waveform Receivers for Multipath Mitigation in Global Navigation Satellite Systems with Binary Offset Carrier and Multiplexed Binary Offset Carrier Signals

This paper compares the multipath mitigation performance of code correlation reference waveform receivers with variable and fixed window width, for binary offset carrier and multiplexed binary offset carrier signals typically used in global navigation satellite systems. In the variable window width method, such width is iteratively reduced until the distortion on the discriminator with multipath is eliminated. This distortion is measured as the Euclidean distance between the actual discriminator (obtained with the incoming signal), and the local discriminator (generated with a local copy of the signal). The variable window width have shown better performance compared to the fixed window width. In particular, the former yields zero error for all delays for the BOC and MBOC signals considered, while the latter gives rather large nonzero errors for small delays in all cases. Due to its computational simplicity, the variable window width method is perfectly suitable for implementation in low-cost receivers.

Ordinal Regression with Fenton-Wilkinson Order Statistics: A Case Study of an Orienteering Race

In sports, individuals and teams are typically interested in final rankings. Final results, such as times or distances, dictate these rankings, also known as places. Places can be further associated with ordered random variables, commonly referred to as order statistics. In this work, we introduce a simple, yet accurate order statistical ordinal regression function that predicts relay race places with changeover-times. We call this function the Fenton-Wilkinson Order Statistics model. This model is built on the following educated assumption: individual leg-times follow log-normal distributions. Moreover, our key idea is to utilize Fenton-Wilkinson approximations of changeover-times alongside an estimator for the total number of teams as in the notorious German tank problem. This original place regression function is sigmoidal and thus correctly predicts the existence of a small number of elite teams that significantly outperform the rest of the teams. Our model also describes how place increases linearly with changeover-time at the inflection point of the log-normal distribution function. With real-world data from Jukola 2019, a massive orienteering relay race, the model is shown to be highly accurate even when the size of the training set is only 5% of the whole data set. Numerical results also show that our model exhibits smaller place prediction root-mean-square-errors than linear regression, mord regression and Gaussian process regression.

Intercultural Competence among Jewish and Arab Students Studying Together in an Academic Institution in Israel

Since the establishment of the state of Israel, and as a result of various events that led to it, Jewish citizens and Arab citizens of the state have been in constant conflict, which finds its expression in most levels of life. Therefore, the attitude of one group member to the other group members is mostly tense, loaded, and saturated with mutual suspicion. Within this reality, in many higher education institutions in Israel, Jews and Arabs meet with each other intensively and for several years. For some students, this is their first opportunity for a meaningful cross-cultural encounter. These intercultural encounters, which allow positive interactions between members of different cultural groups, may contribute to the formation of "intercultural competence" which means long-term change in knowledge, attitudes, and behavior towards 'the other culture'. The current study examined the concept of the ‘other’ among Jewish and Arab students studying together and their "intercultural competence". The study also examined whether there is a difference in the perception of the ‘other’ between students studying in different academic programs, and between students taking academic courses on multiculturalism. This quantitative study was conducted among 274 Arab and Jewish students studying together, for bachelors or master's degree, in various academic programs at the Israel Academic College of Ramat-Gan. The background data of the participants are varied, in terms of religion, origin, religiosity, employment status, living area, and marital status. The main hypothesis is that academic, social, and intercultural encounters between Jewish and Arab students, who attend college together, will be a significant factor in building "intercultural competence". Additionally, the existence of "intercultural competence" has been linked to demographic characteristics of the students, as well as the nature of intercultural encounters between Jews and Arabs in a higher education institution. The dependent variables were measured by a self-report questionnaire, using the components of '"intercultural competence"' among students, which are: 1. Cognitive knowledge of the ‘others’, 2. Feelings towards the ‘others’, 3. Change in attitudes towards the 'others', and 4. Change in behavior towards the ‘others’. The findings indicate a higher "intercultural competence" among Arab students than Jews; it was also found higher level of "intercultural competence" among Educational Counseling students than the other respondents. The importance of this research lies in finding the means to develop "intercultural competence" among Jewish and Arab students, which may reduce prejudice and stereotypes towards the other culture and may even prevent occurrences of alienation and violence in cross-cultural encounters in Israel.

Influence of Security on Fan Attendance during Nigeria Professional Football League Matches

The stadium transcends a field of play to cultural heritage of a club especially when there is security of life and property and a conducive environment with exciting media facilities, CCTV and adequate field of play. Football fans love watching their clubs’ matches especially when nothing discourages their presence in the stadium. This study investigated the influence of security on fans’ attendance during Nigeria Professional Football League matches. Descriptive survey research design was used and the population consists of all Nigeria Professional Football League fans. Simple random sampling technique was used to pick a state from the six geo-political zones. 600 respondents comprising male and female fans were sampled from the ten selected vendors’ stands in each selected state. A structured questionnaire on Security and Fan attendance scale (SFAS) was used. The instrument consists of two sections. Section A seeks information on demographic data of the respondents, while section B was used to elicit information on security and fans’ attendance. The modified instrument which consists of 20 items has a reliability coefficient of 0.73. The hypothesis was tested at 0.05 significance level. The completed questionnaire was collated, coded and analyzed using descriptive statistics of frequency counts and percentage and inferential statistics of chi-square (X2). Findings of this study revealed that adequate security significantly influences fan attendance during Nigeria Professional Football League matches. There is no sport that can develop if the facilities in use are inadequate. Improving the condition of the stadium in Nigeria is paramount to the development of the Nigeria Professional Football League. All stakeholders in the organization of the League must put into consideration the need to improve the standard of the stadium as it will help to increase the attendance of fans during matches. Only the standard ones should be used during matches.

Investigation of Boll Properties on Cotton Picker Machine Performance

Cotton, as a strategic crop, plays an important role in providing human food and clothing need, because of its oil, protein, and fiber. Iran has been one of the largest cotton producers in the world in the past, but unfortunately, for economic reasons, its production is reduced now. One of the ways to reduce the cost of cotton production is to expand the mechanization of cotton harvesting. Iranian farmers do not accept the function of cotton harvesters. One reason for this lack of acceptance of cotton harvesting machines is the number of field losses on these machines. So, the majority of cotton fields are harvested by hand. Although the correct setting of the harvesting machine is very important in the cotton losses, the morphological properties of the cotton plant also affect the performance of cotton harvesters. In this study, the effect of some cotton morphological properties such as the height of the cotton plant, number, and length of sympodial and monopodial branches, boll dimensions, boll weight, number of carpels and bracts angle were evaluated on the performance of cotton picker. In this research, the efficiency of John Deere 9920 spindle Cotton picker is investigated on five different Iranian cotton cultivars. The results indicate that there was a significant difference between the five cultivars in terms of machine harvest efficiency. Golestan cultivar showed the best cotton harvester performance with an average of 87.6% of total harvestable seed cotton and Khorshid cultivar had the least cotton harvester performance. The principal component analysis showed that, at 50.76% probability, the cotton picker efficiency is affected by the bracts angle positively and by boll dimensions, the number of carpels and the height of cotton plants negatively. The seed cotton remains (in the plant and on the ground) after harvester in PCA scatter plot were in the same zone with boll dimensions and several carpels.

Analysis of Career Support Programs for Olympic Athletes in Japan with Fifteen Conceptual Categories

The Japan Sports Agency has made efforts to unify several career support programs for Olympic athletes prior to the 2020 Tokyo Olympics. One of the programs, the Japan Olympic Committee Career Academy (JCA) was established in 2008 for Olympic athletes at their retirement. Research focusing on the service content of sport career support programs can help athletes experience a more positive transition. This study was designed to investigate the service content of the JCA program in relation to athletes’ career transition needs, including any differences of the reasons for retirement between Summer/Winter and Male/Female Olympic athletes, and to suggest the directions of how to unify the career support programs in Japan after hosting the Olympic Games using sport career transition models. Semi-structured interviews were conducted and analyzed the JCA director who started and managed the program since its inception, and a total of 15 conceptual categories were generated by the analysis. Four conceptual categories were in the result of “JCA situation”, 4 conceptual categories were in the result of “Athletes using JCA”, and 7 conceptual categories were in the result of “JCA current difficulties”. Through the analysis it was revealed that: the JCA had occupational supports for both current and retired Olympic athletes; other supports such as psychological support were unclear due to the lack of psychological professionals in JCA and the difficulties collaborating with other sports organizations; and there are differences in tendencies of visiting JCA, financial situations, and career choices depending on Summer/Winter and Male/Female athletes.

Evaluation of Deformable Boundary Condition Using Finite Element Method and Impact Test for Steel Tubes

Stainless steel pipelines are crucial components to transportation and storage in the oil and gas industry. However, the rise of random attacks and vandalism on these pipes for their valuable transport has led to more security and protection for incoming surface impacts. These surface impacts can lead to large global deformations of the pipe and place the pipe under strain, causing the eventual failure of the pipeline. Therefore, understanding how these surface impact loads affect the pipes is vital to improving the pipes’ security and protection. In this study, experimental test and finite element analysis (FEA) have been carried out on EN3B stainless steel specimens to study the impact behaviour. Low velocity impact tests at 9 m/s with 16 kg dome impactor was used to simulate for high momentum impact for localised failure. FEA models of clamped and deformable boundaries were modelled to study the effect of the boundaries on the pipes impact behaviour on its impact resistance, using experimental and FEA approach. Comparison of experimental and FE simulation shows good correlation to the deformable boundaries in order to validate the robustness of the FE model to be implemented in pipe models with complex anisotropic structure.

Modeling Engagement with Multimodal Multisensor Data: The Continuous Performance Test as an Objective Tool to Track Flow

Engagement is one of the most important factors in determining successful outcomes and deep learning in students. Existing approaches to detect student engagement involve periodic human observations that are subject to inter-rater reliability. Our solution uses real-time multimodal multisensor data labeled by objective performance outcomes to infer the engagement of students. The study involves four students with a combined diagnosis of cerebral palsy and a learning disability who took part in a 3-month trial over 59 sessions. Multimodal multisensor data were collected while they participated in a continuous performance test. Eye gaze, electroencephalogram, body pose, and interaction data were used to create a model of student engagement through objective labeling from the continuous performance test outcomes. In order to achieve this, a type of continuous performance test is introduced, the Seek-X type. Nine features were extracted including high-level handpicked compound features. Using leave-one-out cross-validation, a series of different machine learning approaches were evaluated. Overall, the random forest classification approach achieved the best classification results. Using random forest, 93.3% classification for engagement and 42.9% accuracy for disengagement were achieved. We compared these results to outcomes from different models: AdaBoost, decision tree, k-Nearest Neighbor, naïve Bayes, neural network, and support vector machine. We showed that using a multisensor approach achieved higher accuracy than using features from any reduced set of sensors. We found that using high-level handpicked features can improve the classification accuracy in every sensor mode. Our approach is robust to both sensor fallout and occlusions. The single most important sensor feature to the classification of engagement and distraction was shown to be eye gaze. It has been shown that we can accurately predict the level of engagement of students with learning disabilities in a real-time approach that is not subject to inter-rater reliability, human observation or reliant on a single mode of sensor input. This will help teachers design interventions for a heterogeneous group of students, where teachers cannot possibly attend to each of their individual needs. Our approach can be used to identify those with the greatest learning challenges so that all students are supported to reach their full potential.

Normal and Peaberry Coffee Beans Classification from Green Coffee Bean Images Using Convolutional Neural Networks and Support Vector Machine

The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Non-Linear Control Based on State Estimation for the Convoy of Autonomous Vehicles

In this paper, a longitudinal and lateral control approach based on a nonlinear observer is proposed for a convoy of autonomous vehicles to follow a desired trajectory. To authors best knowledge, this topic has not yet been sufficiently addressed in the literature for the control of multi vehicles. The modeling of the convoy of the vehicles is revisited using a robotic method for simulation purposes and control design. With these models, a sliding mode observer is proposed to estimate the states of each vehicle in the convoy from the available sensors, then a sliding mode control based on this observer is used to control the longitudinal and lateral movement. The validation and performance evaluation are done using the well-known driving simulator Scanner-Studio. The results are presented for different maneuvers of 5 vehicles.

The Alliance for Grassland Renewal: A Model for Teaching Endophyte Technology

To the author’s best knowledge, there are no published reports of effective methods for teaching fescue toxicosis and grass endophyte technology in the USA. To address this need, a group of university scientists, industry representatives, government agents, and livestock producers formed an organization called the Alliance for Grassland Renewal. One goal of the Alliance was to develop a teaching method that could be employed across all regions in the USA and all sectors of the agricultural community. The first step in developing this method was identification of experts who were familiar with the science and management of fescue toxicosis. The second step was curriculum development. Experts wrote a curriculum that addressed all aspects of toxicosis and management, including toxicology, animal nutrition, pasture management, economics, and mycology. The curriculum was created for presentation in lectures, laboratories, and in the field. The curriculum was in that it could be delivered across state lines, regardless of peculiar, in-state recommendations. The curriculum was also unique as it was unanimously supported by private companies otherwise in competition with each other. The final step in developing this teaching method was formulating a delivery plan. All experts, including university, industry, government, and production, volunteered to travel from any state in the USA, converge in one location, teach a 1-day workshop, then travel to the next location. The results of this teaching method indicate widespread success. Since 2012, experts across the entire USA have converged to teach Alliance workshops in Kansas, Oklahoma, Missouri, Kentucky, Georgia, South Carolina, North Carolina, and Virginia, with ongoing workshops in Arkansas and Tennessee. Data from post-workshop surveys indicate that instruction has been effective, as at least 50% of the participants stated their intention to adopt the endophyte technology presented in these workshops. The teaching method developed by the Alliance for Grassland Renewal has proved to be effective, and the Alliance continues to expand across the USA.

Implementation of the Quality Management System and Development of Organizational Learning: Case of Three Small and Medium-Sized Enterprises in Morocco

The profusion of studies relating to the concept of organizational learning shows the importance that has been given to this concept in the management sciences. A few years ago, companies leaned towards ISO 9001 certification; this requires the implementation of the quality management system (QMS). In order for this objective to be achieved, companies must have a set of skills, which pushes them to develop learning through continuous training. The results of empirical research have shown that implementation of the QMS in the company promotes the development of learning. It should also be noted that several types of learning are developed in this sense. Given the nature of skills development is normative in the context of the quality demarche, companies are obliged to qualify and improve the skills of their human resources. Continuous training is the keystone to develop the necessary learning. To carry out continuous training, companies need to be able to identify their real needs by developing training plans based on well-defined engineering. The training process goes obviously through several stages. Initially, training has a general aspect, that is to say, it focuses on topics and actions of a general nature. Subsequently, this is done in a more targeted and more precise way to accompany the evolution of the QMS and also to make the changes decided each time (change of working method, change of practices, change of objectives, change of mentality, etc.). To answer our problematic we opted for the method of qualitative research. It should be noted that the case study method crosses several data collection techniques to explain and understand a phenomenon. Three cases of companies were studied as part of this research work using different data collection techniques related to this method.

Effect of Damping on Performance of Magnetostrictive Vibration Energy Harvester

This article presents an analytical model to estimate the harvested power from a Magnetostrictive cantilevered beam with tip excitation. Furthermore, the effects of internal and external damping on harvested power are investigated. The magnetostrictive material in this harvester is Galfenol. In comparison to other popular smart materials like Terfenol-D, Galfenol has higher strength and machinability. In this article, first, a mechanical model of the Euler-Bernoulli beam is employed to calculate the deflection of the harvester. Then, the magneto-mechanical equation of Galfenol is combined with Faraday's law to calculate the generated voltage of the Magnetostrictive cantilevered beam harvester. Finally, the beam model is incorporated in the aforementioned combination. The results show that a 30×8.5×1 mm Galfenol cantilever beam harvester with 80 turn pickup coil can generate up to 3.7 mV and 9 mW. Furthermore, sensitivity analysis made by Response Surface Method (RSM) shows that the harvested power is only sensitive to the internal damping coefficient.

Study of Proton-9,11Li Elastic Scattering at 60~75 MeV/Nucleon

The radial form of nuclear matter distribution, charge and the shape of nuclei are essential properties of nuclei, and hence, are of great attention for several areas of research in nuclear physics. More than last three decades have witnessed a range of experimental means employing leptonic probes (such as muons, electrons etc.) for exploring nuclear charge distributions, whereas the hadronic probes (for example alpha particles, protons, etc.) have been used to investigate the nuclear matter distributions. In this paper, p-9,11Li elastic scattering differential cross sections in the energy range  to  MeV have been studied by means of Coulomb modified Glauber scattering formalism. By applying the semi-phenomenological Bhagwat-Gambhir-Patil [BGP] nuclear density for loosely bound neutron rich 11Li nucleus, the estimated matter radius is found to be 3.446 fm which is quite large as compared to so known experimental value 3.12 fm. The results of microscopic optical model based calculation by applying Bethe-Brueckner–Hartree–Fock formalism (BHF) have also been compared. It should be noted that in most of phenomenological density model used to reproduce the p-11Li differential elastic scattering cross sections data, the calculated matter radius lies between 2.964 and 3.55 fm. The calculated results with phenomenological BGP model density and with nucleon density calculated in the relativistic mean-field (RMF) reproduces p-9Li and p-11Li experimental data quite nicely as compared to Gaussian- Gaussian or Gaussian-Oscillator densities at all energies under consideration. In the approach described here, no free/adjustable parameter has been employed to reproduce the elastic scattering data as against the well-known optical model based studies that involve at least four to six adjustable parameters to match the experimental data. Calculated reaction cross sections σR for p-11Li at these energies are quite large as compared to estimated values reported by earlier works though so far no experimental studies have been performed to measure it.

Analytical Authentication of Butter Using Fourier Transform Infrared Spectroscopy Coupled with Chemometrics

Fourier Transform Infrared (FT-IR) spectroscopy coupled with chemometrics was used to distinguish between butter samples and non-butter samples. Further, quantification of the content of margarine in adulterated butter samples was investigated. Fingerprinting region (1400-800 cm–1) was used to develop unsupervised pattern recognition (Principal Component Analysis, PCA), supervised modeling (Soft Independent Modelling by Class Analogy, SIMCA), classification (Partial Least Squares Discriminant Analysis, PLS-DA) and regression (Partial Least Squares Regression, PLS-R) models. PCA of the fingerprinting region shows a clustering of the two sample types. All samples were classified in their rightful class by SIMCA approach; however, nine adulterated samples (between 1% and 30% w/w of margarine) were classified as belonging both at the butter class and at the non-butter one. In the two-class PLS-DA model’s (R2 = 0.73, RMSEP, Root Mean Square Error of Prediction = 0.26% w/w) sensitivity was 71.4% and Positive Predictive Value (PPV) 100%. Its threshold was calculated at 7% w/w of margarine in adulterated butter samples. Finally, PLS-R model (R2 = 0.84, RMSEP = 16.54%) was developed. PLS-DA was a suitable classification tool and PLS-R a proper quantification approach. Results demonstrate that FT-IR spectroscopy combined with PLS-R can be used as a rapid, simple and safe method to identify pure butter samples from adulterated ones and to determine the grade of adulteration of margarine in butter samples.

Natural Frequency Analysis of a Porous Functionally Graded Shaft System

The vibration characteristics of a functionally graded (FG) rotor model having porosities and micro-voids is investigated using three-dimensional finite element analysis. The FG shaft is mounted with a steel disc located at the midspan. The shaft ends are supported on isotropic bearings. The FG material is composed of a metallic (stainless-steel) and ceramic phase (zirconium oxide) as its constituent phases. The layer wise material property variation is governed by power law. Material property equations are developed for the porosity modelling. Python code is developed to assign the material properties to each layer including the effect of porosities. ANSYS commercial software is used to extract the natural frequencies and whirl frequencies for the FG shaft system. The obtained results show the influence of porosity volume fraction and power-law index, on the vibration characteristics of the ceramic-based FG shaft system.

The Greek Root Word ‘Kos’ and the Trade of Ancient Greek with Tamil Nadu, India

The ancient Greeks were forerunners in many fields than other societies. So, the Greeks were well connected with all the countries which were well developed during that time through trade route. In this connection, trading of goods from the ancient Greece to Tamil Nadu which is presently in India, though they are geographically far away, played an important role. In that way, the word and the goods related with kos and kare got exchanged between these two societies. So, it is necessary to compare the phonology and the morphological occurrences of these words that are found common both in the ancient Greek and Tamil literatures of the contemporary period. The results show that there were many words derived from the root kos with the basic meaning of ‘arrange’ in the ancient Greek language, but this is not the case in the usage of the word kare. In the ancient Tamil literature, the word ‘kos’ does not have any root and also had rare occurrences. But it was just the opposite in the case of the word ‘kare’. One of all the meanings of the word, which was derived from the root ‘kos’ in ancient Greek literature, is related with costly ornaments. This meaning seems to have close resemblance with the usage of word ‘kos’ in ancient Tamil literature. Also, the meaning of the word ‘kare’ in ancient Tamil literature is related with spices whereas, in the ancient Greek literature, its meaning is related to that of the cooking of meat using spices. Hence, the similarity seen in the meanings of these words ‘kos’ and ‘kare’ in both these languages provides lead for further study. More than that, the ancient literary resources which are available in both these languages ensure the export and import of gold and spices from the ancient Greek land to Tamil land.

Improving the Frequency Response of a Circular Dual-Mode Resonator with a Reconfigurable Bandwidth

In this paper, a method for reconfiguring bandwidth in a circular dual-mode resonator is presented. The method concerns the optimized geometry of a structure that may be used to host the tuning elements, which are typically RF (Radio Frequency) switches. The tuning elements themselves, and their performance during tuning, are not the focus of this paper. The designed resonator is able to reconfigure its fractional bandwidth by adjusting the inter-coupling level between the degenerate modes, while at the same time improving its response by adjusting the external-coupling level and keeping the center frequency fixed. The inter-coupling level has been adjusted by changing the dimensions of the perturbation element, while the external-coupling level has been adjusted by changing one of the feeder dimensions. The design was arrived at via optimization. Agreeing simulation and measurement results of the designed and implemented filters showed good improvements in return loss values and the stability of the center frequency.

Understanding How Money Laundering and Financing of Terrorism Are Conducted through the Real Estate Sector in the Middle East and North Africa Region

This research seeks to identify how money laundering activities are executed through the real estate sector. This article provides academics with literature on the topic and provides scholars, and practitioners with a better understanding of the risks and challenges involved. Data are gathered through survey in the Middle East and North Africa region and review of the available research. The results of the analysis will help identifying the factors attracting criminals to the real estate sector and develop an understanding of the methods used to launder illicit funds through this sector and the indicators of suspicion for reporting entities. Further analysis reveals the risks posed by money laundering and terrorist financing on the real estate sector and challenges facing states in this regard.