Intelligence Unit Research Articles

An Exploration of Selected Anti-Money Laundering Role-Players in Zimbabwe

Although Zimbabwe has established several institutions to combat money laundering and related crimes, there is a perception that inadequate measures are taken to apprehend offenders responsible for financial crimes. Institutions such as the Financial Intelligence Unit (FIU), the Zimbabwe Anti-Corruption Commission (ZACC), the Zimbabwe Republic Police (ZRP), the National Prosecuting Authority (NPA) and the Reserve Bank of Zimbabwe (RBZ) have done little to prove that the government of Zimbabwe is resolute in combatting money laundering. On the contrary, it increasingly appears that these institutions are poorly equipped and lack the necessary capacity to enforce and uphold anti-money laundering (AML) measures in Zimbabwe. Further, there appears to be a selective application of the law, with one set of rules for individuals or institutions that are perceived as political adversaries of the incumbent establishment and a different set of rules for the political elite. Consequently, the selective application of the law projects Zimbabwe as a jurisdiction that is somehow tolerant to money laundering, corruption and related financial crimes, thereby lowering and tarnishing the standing of the country in the global economic community of nations. This paper provides a regulatory analysis of the AML role-players in Zimbabwe in order to assess their functions in combatting financial crimes. It also analyses whether these role-players are effective and substantively executing their responsibilities therein. The authors argue that while Zimbabwe is well able to effectively combat money laundering through the even application of the law to all persons regardless of their political or economic standing, it is imperative that its AML institutions operate without fear, favour or prejudice. This is crucial in combatting money laundering and instilling confidence in the general public's perception of AML institutions in Zimbabwe.

European brown hare syndrome virus and other lagoviruses of interest.

This focus article was prepared by Paul Duff of the APHA Wildlife Expert Group, with support from David Everest (APHA Pathology Department), Lucy Martindale (APHA Surveillance Intelligence Unit), Alex Barlow (Wildlife Network for Disease Surveillance), Mara Rocchi (Moredun Research Institute) and Antonio Lavazza (Istituto Zooprofilattico Sperimentale della Lombardia e dell'Emilia Romagna, Italy).

Graded Nanotexturing Architectural Wearable Triboelectric Sensor for Programmable Haptic Exploration.

Emulating biological perception mechanisms to construct intelligent sensing devices and systems represents a paradigm for promoting human-computer interaction in the Internet of Everything era. Nonetheless, developing highly sensitive, real-time sensing and rapidly integrated intelligent interaction units remains a challenging and time-consuming endeavor. This study employs a low-temperature glow discharge technique to rapidly fabricate graded nanotexturing architectural triboelectric nanopaper, upon which wearable triboelectric sensors for real-time tactile detection are designed. The structure enhances the contact area under an external force. Additionally, the Z-stacking structure design enables the sensor to achieve a remarkable sensitivity of 10.3 kPa-1 and a rapid response time of 52 ms. Furthermore, a tactile sensor array was designed to demonstrate the triboelectric sensor's ability to recognize characteristic pressures. With programmable machine learning techniques, the object recognition rate reached 97%. This study supports material structural design across disciplines, laying a solid foundation for the rapid fabrication and integration of transient wearable electronics.

Ensemble and Gossip Learning-Based Framework for Intrusion Detection System in Vehicle-to-Everything Communication Environment.

Autonomous vehicles are revolutionizing the future of intelligent transportation systems by integrating smart and intelligent onboard units (OBUs) that minimize human intervention. These vehicles can communicate with their environment and one another, sharing critical information such as emergency alerts or media content. However, this communication infrastructure is susceptible to cyber-attacks, necessitating robust mechanisms for detection and defense. Among these, the most critical threat is the denial-of-service (DoS) attack, which can target any entity within the system that communicates with autonomous vehicles, including roadside units (RSUs), or other autonomous vehicles. Such attacks can lead to devastating consequences, including the disruption or complete cessation of service provision by the infrastructure or the autonomous vehicle itself. In this paper, we propose a system capable of detecting DoS attacks in autonomous vehicles across two scenarios: an infrastructure-based scenario and an infrastructureless scenario, corresponding to vehicle-to-everything communication (V2X) Mode 3 and Mode 4, respectively. For Mode 3, we propose an ensemble learning (EL) approach, while for the Mode 4 environment, we introduce a gossip learning (GL)-based approach. The gossip and ensemble learning approaches demonstrate remarkable achievements in detecting DoS attacks on the UNSW-NB15 dataset, with efficiencies of 98.82% and 99.16%, respectively. Moreover, these methods exhibit superior performance compared to existing schemes.

Validity and timeliness of cancer diagnosis data collected during a prospective cohort study and reported by the English and Welsh cancer registries: a retrospective, comparative analysis

Cancer places a high burden on society and health-care systems. Cancer research requires high-quality data, which is resource-intensive to obtain. Using administrative datasets such as cancer registries could improve the efficiency of cancer studies if data were valid and timely. We aimed to compare the validity and timeliness of diagnostic cancer data on-site during the SYMPLIFY study to that obtained from the cancer registries of England and Wales. Cancer data were collected from 5461 participants across 44 hospital sites during a prospective observational study in England and Wales, SYMPLIFY (ISRCTN10226380). Linked cancer data were obtained from Digital Health and Care Wales (DHCW), the Welsh Cancer Intelligence and Surveillance Unit (WCISU), and the English National Cancer Registration Dataset (NCRD) and Rapid Cancer Registration Dataset (RCRD), regularly between April, 2022, and September, 2023. The primary objectives of the study were to evaluate the validity (via assessment of the proportion of completed data fields and concordance with SYMPLIFY sites), and timeliness of the data in all datasets, for all cancers diagnosed within 9 months of study enrolment. Data fields investigated were cancer site via International Classification of Disease, 10th Revision (ICD-10) code; cancer morphology via International Classification of Diseases for Oncology, 3rd Edition (ICD-O-3) morphology histology code and broad morphological grouping; overall stage; and TNM classification. For data collected between April, 2022, and September, 2023, completeness at the last data cut available for each dataset ranged from 84% to 100% for ICD-O-3 morphology, from 43% to 100% for overall stage, and from 74% to 83% for TNM stage. The concordance between SYMPLIFY data and NCRD was 96% (95% CI 92-98) for ICD-10, 60% (53-66) for ICD-O-3 morphology, 83% (78-88) for ICD-O-3 broad morphology groupings, 73% (67-78) for stage, and 51% (44-59) for TNM; and with WCISU was 89% (95% CI 81-94) for ICD-10, 63% (53-73) for ICD-O-3 morphology, 80% (70-87) for ICD-O-3 broad morphology groupings, 83% (74-90) for overall stage, and 49% (38-61) for TNM stage. Concordance between SYMPLIFY and RCRD was 95% (95% CI 92-98) for ICD-10, 67% (60-74) for ICD-O-3 morphology, 85% (79-90) for ICD-O-3 broad morphology groupings, and 73% (65-80) for overall stage; and between SYMPLIFY and DHCW was 96% (91-99) for ICD-10, 74% (64-83) for ICD-O-3 morphology, 84% (75-91) for ICD-O-3 broad morphology groupings, and 87% (74-95) for stage. The SYMPLIFY dataset reached completion at 12 months post-enrolment in November, 2022, compared with 13 months for NCRD in December, 2023. RCRD and DHCW reached completion at 13 months and 15 months post-enrolment, in December, 2022, and February, 2023, respectively. We report similar completeness of data fields, concordance, and timeliness between on-site and centrally collected cancer outcomes data. Our findings suggest that central registry data can help alleviate the resource burden in clinical trials and improve cancer research. Cancer registries might need additional resources to provide data for registry-based trials at scale. GRAIL Bio UK.

Present Scenario of Post-poll Alliance in India

India is one of the greatest democracies in the World, however, the 2021 Economic Intelligence Unit ranked India at 46th position on Democracy Index with a score of 6.91. Such low ranking of in Democracy Index shows the mirror to changing opportunistic political culture prevailing in India. Free and fair election is the basis of any democracy where the government is formed as per the mandate of the voters. However, recent years in Indian polity has seen the increase in the trend of post poll alliance which provides the opportunity to form government by bypassing the public mandate. This left voters in a state of confusion where they are left uncertain of their role in democracy. The increasing trend of post poll alliances is a severe challenge to democracy which cannot be dealt with existing election laws. The present scenario of Indian politics demands the formulation of new laws to put a stop to this unethical practice of opportunistic politics

Trends in the incidence and mortality of cervical, ovarian, and corpus uteri cancers in Wales, UK: A joinpoint regression analysis from 2002 to 2021

ObjectivesThe primary objective of this study was to examine the secular trends of cervical, ovarian, and corpus uteri neoplasm in Wales, UK, over the period from 2002 to 2021. We aimed to identify changes in the incidence and mortality rates of these cancers to inform future healthcare policies and cancer prevention programs. MethodsWe sourced incidence data from 2002 to 2019 and mortality data from 2002 to 2021 from the Welsh Cancer Intelligence and Surveillance Unit. The data were analysed using Joinpoint regression to compute the average annual percentage change (AAPC) in age-standardized incidence rates (ASIR) and mortality rates (ASMR) per 100,000 population for each type of cancer. ResultsThe results showed that the ASIR for cervical cancer remained stable between 2002 and 2019 (AAPC = −0.5; 95 %CI = −1.4–0.4). However, the ASMR significantly declined from 4.88 in 2002–3.03 in 2021 (AAPC = −2.3; 95 %CI = −3.4 to −1.1). The ASIR for ovarian cancer significantly decreased from 27.39 in 2002–17.87 in 2019 (AAPC = −2.6; 95 %CI = −3.0 to −2.1), and the ASMR showed a statistically significant decreasing trend from 15.92 in 2002–11.2 in 2021 (AAPC = −1.7; 95 %CI = −2.5 to −0.9). In contrast, the ASIR for corpus uteri neoplasm significantly increased from 22.24 in 2002–30.41 in 2019 (AAPC = 2.2; 95 %CI = 1.2–3.4), and ASMR also showed a statistically significant increasing trend from 3.27 in 2002–6.42 in 2021 (AAPC = 3.8; 95 %CI = 2.3–5.3). ConclusionsThe study concludes that while the incidence and mortality rates for cervical and ovarian cancers in Wales have significantly decreased, corpus uteri neoplasm rates have increased during the study period. These findings underscore the need for continued efforts to improve early detection and treatment strategies, including national screening programs and public health initiatives, to mitigate the burden of these cancers.

RD-SLAM: Real-Time Dense SLAM Using Gaussian Splatting

Simultaneous localization and mapping (SLAM) is fundamental for intelligent mobile units to perform diverse tasks. Recent work has shown that integrating neural rendering and SLAM showed promising results in photorealistic environment reconstruction. However, existing methods estimate pose by minimizing the error between rendered and input images, which is time-consuming and cannot be run in real-time, deviating from the original intention of SLAM. In this paper, we propose a dense RGB-D SLAM based on 3D Gaussian splatting (3DGS) while employing generalized iterative closest point (G-ICP) for pose estimation. We actively utilize 3D point cloud information to improve the tracking accuracy and operating speed of the system. At the same time, we propose a dual keyframe selection strategy and its corresponding densification method, which can effectively reconstruct new observation scenes and improve the quality of previously constructed maps. In addition, we introduce regularization loss to address the scale explosion of the 3D Gaussians and over-elongate in the camera viewing direction. Experiments on the Replica, TUM-RGBD, and ScanNet datasets show that our method achieves state-of-the-art tracking accuracy and runtime while being competitive in rendering quality.

Soberanía nacional y antisemitismo. La memoria de la derecha nacionalista argentina frente al caso Eichmann

After World War II, Adolf Eichmann found refuge in Argentina. In May 1960, he was captured by an Israeli intelligence unit and taken to Israel for trial. After being found guilty, he was sentenced to death and executed two years later. These events had a strong impact on the country from which he was abducted. Argentinian right-wing nationalist groups carried out numerous demonstrations to demand his restitution while leading strong waves of anti-Semitism in the country. The actions of youth groups such as the Movimiento Nacionalista Tacuara and the Guardia Restauradora Nacionalista against the Argentine Jewish community were strongly repudiated by society. Through the analysis of nationalist bulletins, press, national newspapers, and former militants' memories, and upon verifying the claims for the violation of national sovereignty we found that these were the main cloak that concealed the racial aspect of these anti-Semitic movements, both in the 1960s and in recent years. Furthermore, the role of anti-Zionism as a facade is particularly relevant in this context. Lastly, contemporary memoirs reveal attempts to downplay, omit, or silence the perpetration of anti-Semitic violence.

Использование финансовой информации в сотрудничестве государств по выявлению и пресечению преступлений

The use of financial information in investigations plays the key role in crime combating. Efficient application of data on financial transactions facilitates identification and prevention of activities of transnational and organized criminal networks. However, limited opportunities of law enforcement authorities and the absence of access to centralized bank account registers can hinder such investigations. Enhancement of international cooperation and information exchange between law enforcement authorities and financial intelligence units (FIUs) can substantially increase the efficiency of investigations. Such cooperation includes training and professional development of employees (it is critically important to teach them contemporary financial data analysis methods and how to use cutting-edge technologies), development of new technologies. Innovative instruments of analysis of financial information are required for timely and accurate identification of criminal acts. Creation of flexible mechanisms of access to information requires development of international data exchange systems, which will enable law enforcement authorities to receive information on bank accounts without delay.

Advanced smart HVAC system utilizing borehole thermal energy storage: Detailed analysis of a Uppsala case study focused on the deep green cooling innovation

This article presents and thoroughly examines an innovative, practical, cost-effective, and energy-efficient smart heating, ventilation, and air conditioning (HVAC) system. The fundamental component of this concept is a state-of-the-art method called Deep Green Cooling technology, which uses deep drilling to utilize the ground's heating and cooling potential directly without the need for machinery or heat pumps. This method satisfies demands with the least energy use, environmental impact, and operational costs. In order to effectively oversee and regulate energy production, storage, and utilization, the system consists of an intelligent control unit with many smart controllers and valves. Renewable energy deployment is made easier, and the intelligent automation unit is more compatible with the help of a high-temperature cooling resource with a high supply temperature of 16 °C. The technical, environmental, and financial aspects of the suggested smart office building system in the southern region of Uppsala, Sweden, are evaluated using TRNSYS software. According to the results, boreholes provide more than 28.5 % of the building's energy requirements by utilizing the ground's ability to generate affordable, dependable seasonal thermal energy. The district heating network satisfies the remaining demand, amounting to 787.2 MWh, highlighting the benefits of combining conventional and renewable energy sources for increased supply security and dependability. The borehole thermal energy storage system meets the building's entire cooling need, underscoring the importance of high-temperature cooling systems. The most expensive part of the system is the borehole thermal energy storage, which accounts for over half of the total investment. The system has an appropriate payback period of ten years, proving its long-term profitability and cost-effectiveness, thanks to removing the machinery and heat pump. With 3138 MWh of ground-source heating and cooling, the system saves 17,962 USD by reducing CO2 emissions by about 143.7 t, sufficient to grow 16.3 ha of trees throughout the payback period.

Physical readiness of scouts - as the main component of their professional activity

The existence of threats to national security, especially the territorial integrity of the country, requires the existence of such Armed Forces in Ukraine that could to ensure the complete security of our state in all situations. Analyzing the activities of reconnaissance specialists, the conditions of the present and the fighting on the territory of the state, we can say that recently a weak possession of personal small arms, hand-to-hand combat techniques, insufficient skills of servicemen to overcome existing engineering barriers, rubble, especially against the background of fatigue, have been revealed. At the same time, there is a lack of scientific, theoretical, theoretical and methodological justification of practical ways to achieve the physical readiness of military personnel, the presence of weak links in the system of their preparation for action in extreme conditions of combat activity. One of the reasons, in our opinion, is the imperfect and long-term solution of organizational issues regarding the introduction of a scientific approach to the physical training of servicemen of intelligence units in the conditions of warfare. Thus, the urgent issue remains the search for ways to increase the effectiveness of physical training of the reconnaissance units of the Armed Forces of the Armed Forces of Ukraine and their implementation in the guidance documents on physical training.

The Accountability and Transparency of Police Record Certificate (SKCK) Issuance Services at the Bali Regional Police

The role of the Bali regional police in providing accountable and transparent police record certificate services is very large, measured by the best service quality indicators into 5 dimensions, including Tangible (tangible), Reliability (reliability), Responsiveness (responsiveness), Assurance (guarantee), and Empathy (empathy). The obstacles for the Bali Regional Police in issuing police record certificates for the Bali Regional Police are lack of facilities and infrastructure, lack of human resources or staff, and lack of public awareness. Efforts to overcome problems in improving the quality of services for making police record certificates in the Bali regional police intelligence and security unit are maximizing facilities and infrastructure, increasing human resources, providing socialization and evaluation.

Declining Incidence of Major Lower-Extremity Amputations in the Northern Danish Region Between 2016 and 2021: The Impact of Diabetes and Preventive Vascular Procedures

BackgroundPreventing lower-extremity amputations (LEAs) is pivotal. In the present study we aimed to examine the recent trends in non-traumatic LEAs seen in the Northern Danish Region. MethodsUsing data from the regional Business Intelligence unit we identified all non-traumatic LEAs (n=689) performed in people above 50 years of age in the Northern Danish Region between January 2016 and December 2021 (approximately 600.000 inhabitants). Persons with diabetes (n=26,025) were identified based on ICD-10 codes and data from The National Health Insurance Service Registry, while preventive vascular procedures (n=1,097) were identified using surgical codes. Major LEA was defined as any amputation above the ankle. Incidence rates were expressed as events per 1.000 person-years. Trends were described as differences between the periods 2016-2018 and 2019-2021. ResultsA total of 249 (36%) major LEAs were performed in people with diabetes. People with diabetes were younger (71 vs 77 years, p<0.001) and more frequently male (70% versus 54%, p<0.001). Between 2016-2018 and 2019-2021 the incidence of major LEA declined from 1.76 (95% CI: 1.75-1.76) to 1.39 (1.39-1.39) in people with diabetes, and from 0.47 (0.47-0.47) to 0.20 (0.20-0.20) in people without diabetes (all p<0.001). Simultaneously, the incidence of preventive vascular surgery increased from 2.26 (2.26-2.26) to 3.48 (3.48-3.48) in people with diabetes and declined slightly in people without 0.49 (0.49-0.49) to 0.47 (0.47-0.47) (all p<0.001). ConclusionDespite significant declines in major LEA in both people with and without diabetes, most of the decline was driven by a large reduction in major LEAs in people without diabetes. Diabetic foot, lower extremity amputation, major amputation, minor amputation, preventive vascular procedures, revascularization, vascular surgery.

Application of International Law in Tackling Money Laundering

Money laundering has become a complex and challenging global issue, this complexity is compounded by its cross-border nature, which demands effective international cooperation in its handling and the application of international law to be key to comprehensively combating trafficking and preventing the proliferation of proceeds of crime. International law related to trafficking has evolved rapidly in recent decades. Beginning with the 1988 Vienna Convention on Psychotropic Drugs and Psychotropic Substances, various international legal instruments have been formulated to define trafficking, criminalize its perpetrators, and strengthen cooperation between states. For example the United Nations Convention Against Transnational Organized Crime (Palermo Convention) of 2000 and Recommendation 40 of the FATF, In 2022, the Center for Financial Transaction Reporting and Analysis (PPATK) fully disclosed the amount of Money Laundering (TPPU) which reached IDR 183.88 trillion. Indonesia has ratified various international legal instruments related to TPPU and implemented them in national regulations. Law Number 23 of 2003 concerning Money Laundering and Terrorism Financing is the main legal basis in Indonesia. PPATK, as a UIF (Financial Intelligence Unit), plays an important role in collecting, analyzing, and disseminating information related to TPPU to relevant authorities.

Internet of Things-Based Robust Green Smart Grid

Renewable energy sources play a critical role in all governments’ and organizations’ energy management and sustainability plans. The solar cell represents one such renewable energy resource, generating power in a population-free circumference. Integrating these renewable sources with the smart grids leads to the generation of green smart grids. Smart grids are critical for modernizing electricity distribution by using new communication technologies that improve power system efficiency, reliability, and sustainability. Smart grids assist in balancing supply and demand by allowing for real-time monitoring and administration, as well as accommodating renewable energy sources and reducing outages. However, their execution presents considerable problems. High upfront expenditures and the need for substantial and reliable infrastructure changes present challenges. Despite these challenges, shifting to green smart grids is critical for a resilient and adaptable energy future that can fulfill changing consumer demands and environmental aims. To this end, this work considers developing a reliable Internet of Things (IoT)-based green smart grid. The proposed green grid integrates traditional grids with solar energy and provides a control unit between the generation and consumption parts of the grid. The work deploys intelligent IoT units to control energy demands and manage energy consumption effectively. The proposed framework deploys the paradigm of distributed edge computing in four levels to provide efficient data offloading and power management. The developed green grid outperformed traditional grids in terms of its reliability and energy efficiency. The proposed green grid reduces energy consumption over the distribution area by an average of 24.3% compared to traditional grids.

Impact of Climate Policy Uncertainty (CPU) and global Energy Uncertainty (EU) news on U.S. sectors: The moderating role of CPU on the EU and U.S. sectoral stock nexus

This article accounts for the impact of positive and negative shocks of the news-related Climate Policy Uncertainty (CPU) and the novel Economist Intelligence Unit's report-based global Energy Uncertainty (EU) on the U.S. sectoral stock returns by using the ARDL and NARDL approaches with dynamic multiplier simulations. We also utilize both the DCC-GARCH and ADCC-GARCH approaches to extract the symmetric and asymmetric dynamic conditional correlations between the EU and the U.S. sectoral stock returns and then regress these conditional correlation series on the CPU through series of quantile regressions. Overall, the findings suggest that only the positive CPU shocks negatively impact the U.S. sectoral stock returns of Consumer Services, Financials, Industries, Telecommunication and Utilities in the long-term, whereas the negative CPU shocks insignificantly predict the U.S. sectoral returns. The findings also report that only the negative EU shocks increase the U.S. sectoral stock returns of Consumer Services, Financials, Health Care, Industries, Moreover, the positive (negative) EU shocks cause the U.S. sectoral returns of Materials and Technology to decrease (increase) in the long-term. Portfolio managers may consider diversifying their portfolios to include sectors least susceptible to negative impacts from the CPU and EU shocks such as Health Care and Oil & Gas. Our findings also show that CPU shocks moderate the dynamic conditional correlations between the EU and the U.S. sectoral returns of Consumer Services, Materials, Health Care, Telecommunication, Oil and Gas and Utility. Fund managers should contemplate augmenting the allocations to the Financials, Industrials, and Technology sectors owing to their diminished interconnectivity with the EU during periods of heightened CPU.

The tale of the Baltics: Experiences, challenges, and lessons from reforming their national Financial Intelligence Units (FIUs)

The banking sector of three Baltic countries, i.e., Lithuania, Latvia and Estonia, was abused by money laundering scandals between 2018 and 2020. The Danske Bank scandal was the largest one and, combined with the other scandals, inevitably triggered a heavy critique of national anti-money laundering (AML) frameworks that govern the supervision of banking sectors. At the European Union (EU) level, weak mechanisms to ensure the EU-wide supervisory consistency, were also identified. As a result of detected flaws, a new body called The Anti-Money Laundering Authority (AMLA) will be established in the EU as of 2027.This context provides an opportunity to scrutinize the rationale behind AMLA’s establishment, by examining the role that the Baltic countries’ Financial Intelligence Units (FIUs) fulfill in financial surveillance, and the scope of AML reforms that took place in the aftermath of those banking scandals. Could those scandals have been prevented by national FIUs and their supervisory bodies? Whether one Baltic model of FIU exists or rather three different national models are visible? Can AMLA fulfill its mandate without relying on the work carried out by national FIUs and supervisory bodies?Based on extensive interviews with the representatives of the three Baltic FIUs, their supervisory authorities, and content analysis of publicly available sources, this paper offers a unique insight into idiosyncratic characteristics of the Lithuanian, Latvian and Estonian FIUs modus operandi. The findings are that each Baltic FIU was confronted with its own set of problems affecting the fulfillment of these agencies’ statutory duties. However, significant “grass-root” reforms of the AML national frameworks in each Baltic country have already been undertaken.11AML Anti-Money LaunderingBL Bank of LithuaniaCFT Combating Financing of TerrorismEU European UnionAMLA Anti-Mooney Laundering AuthorityECB European Central BankLEA Law-Enforcement AuthorityFIU Financial intelligence unitGDP Gross Domestic ProductFL Finance LatviaPPP Public-Private PartnershipSTR Suspicious Activity ReportUTR Unusual Transaction Report

The role and importance of financial intelligence in identifying and tracing criminal assets

The paper examines the basic principles of improving efficiency and providing law enforcement officers, as well as authorized bodies, in whose management the seized property is transferred, with instructions on the legal grounds, procedural and tactical features of detection, search and seizure of property. It was determined that financial intelligence is a complex system aimed at detecting operations related to the legalization of proceeds obtained through crime. This system can act as a component of the pre-trial investigation in criminal proceedings related to the research. Asset search activities should include elements of economic and monetary intelligence. It has been established that in Ukraine, the State Financial Monitoring Service, subordinate to the Ministry of Finance of Ukraine, is entrusted with the functions of financial intelligence, which implements the state policy in the field of prevention and countermeasures against the legalization (laundering) of proceeds obtained through crime, the financing of terrorism, and the proliferation of weapons of mass destruction. It is argued that financial intelligence is not a function of the National Agency of Ukraine for detection, search and management of assets obtained from corruption and other crimes. In turn, the DSFM collects, processes and analyzes information on financial transactions subject to mandatory financial monitoring and other transactions related to money laundering. It was investigated that the bodies of foreign countries are similar: Financial Crimes Enforcement Network (FinCEN) - the US financial intelligence agency; Financial Transactions and Reports Analysis Center (FINTRAC), Canada's financial intelligence agency; Zentralstelle für Verdachtsanzeigen – German financial intelligence agency; TRACFIN – financial intelligence unit of the French Republic; The Inland Revenue Service NCIS/ECU is the UK's financial intelligence agency. Having analyzed the relevant legislation of ARMA and the State Financial Monitoring Service, we come to the conclusion that the terms "asset discovery" and "asset search" are explicitly defined at the legislative level only for ARMA. The profile legislation of the State Financial Monitoring Service does not reflect or explain the essence of these terms, however, in the course of implementing measures to prevent and counter the legalization (laundering) of proceeds obtained through crime, the State Financial Monitoring Service conducts financial investigations with the aim of finding information about the assets of questionable origin.

ANALYSIS OF MACHINE LEARNING METHODS FOR SOLVING ANTENNA TECHNOLOGY PROBLEMS

The scheme of modern machine learning methods classification is considered and presented. The content of each methods in the classification is briefly disclosed. A structural diagram of an adaptive antenna system with an artificial intelligence unit is presented, and the principle of this scheme operation is explained. The role and function of the artificial intelligence unit within the adaptive antenna system are elucidated. The existing classes of machine learning methods are analyzed to determine their potential applicability to adaptive antenna systems for the purpose of intelligent control of the radiation pattern. It was determined that the primary machine learning method that could potentially be utilized by adaptive antenna system with artificial intelligence unit to achieve intelligent control of its directional characteristics is reinforcement learning. It is demonstrated that the reinforcement learning method can be integrated with other machine learning techniques, such as neural network methods, to enhance the precision of directing the directivity characteristics of adaptive antenna system with artificial intelligence unit.