Computer Sciences Commons^™

The Process Of Adapting Innovations In Banking Services By Businesses In Kosovo, Burim Isa Berisha Dr.Sc, Burim Berisha B.B

International Journal of Business and Technology

This dissertation addresses the importance of a business model from businesses in Kosovo, which is able to adapt innovations from the banking sector such as digital services, and through which become part of a global market where such developments occur step by step. very fast At the beginning of this paper will be given definitions related to the main concepts that are addressed such as business model, innovations in banking services - digitalization of services and the role and importance of linking a business model with banking services of the time. After the theoretical part, from which the main concepts …

Agency Theory And Audit Quality, Burim Isa Berisha Bb

International Journal of Business and Technology

Auditing plays a vital role in reducing both: information asymmetry by empirically confi rming the validity of fi nancial statements and agency problems. The principal- agent confl ict illustrated in agency theory, where principal (owner) lack reasons to believe their agents (managers) because of information asymmetries and contradictory motives. Information asymmetry deals with the study of decisions in transactions where one party has more or superior information than other. Agents (either directors or auditors) may be trustworthy without further incentives to align interest or monitoring strategies such as audit or increased regulation. However, the simple agency model would recommend that …

Background To Auditing And Role Of Auditor, Burim I. Berisha B.B

International Journal of Business and Technology

Financial markets crisis since 2007 has unfolded many issues regarding the supervision of financial institutions, financial reporting and auditing as of core importance to many regulatory bodies in order to ensure proper-functioning framework in the internal market. An audit, along with both adequate supervision and corporate governance, can contribute towards the financial health of the companies by providing assurance in terms of bringing financial stability into their reports (European Commission [EC], 2010, p. 3). The assurance provided by the auditors reduces the risk of misstatements and ultimately the cost of failure to be suffered by the firm’s stakeholders’ also reduces. …

The Process Of Adapting Innovations In Banking Services By Businesses In Kosovo, Burim Isa Berisha Dr.Sc, Burim Berisha B.B

International Journal of Business and Technology

This dissertation addresses the importance of a business model from businesses in Kosovo, which is able to adapt innovations from the banking sector such as digital services, and through which become part of a global market where such developments occur step by step. very fast At the beginning of this paper will be given definitions related to the main concepts that are addressed such as business model, innovations in banking services - digitalization of services and the role and importance of linking a business model with banking services of the time. After the theoretical part, from which the main concepts …

Accountability Responsibility As An Instrument For Performance Measurement, Burhan Rexhepi B.R

International Journal of Business and Technology

This paper addresses the role and importance of accounting information, in particular liability accounting and the impact of liability centers on the success of the enterprise. The success of business decision making is closely linked to the quality and accuracy of accounting information. Every entity, regardless of ownership, size and form of legal organization, the capital structure exists and functions to achieve its objectives.

We live in a time of great changes in external environmental factors, which impose the need to know modern methods and models for running a business. However, the main basis of business success depends on the …

Types Of Financial And Economic Crisis, Burhan R. Rexhepi B.R

International Journal of Business and Technology

Financial crises have caused much debate among different economists. They have attempted to explore any possibility of detecting and preventing crises before they cause the damages that will require way more time and energy to repair the situation and bring the economies back on the right track of sustainable development. The purpose of this study is to analyze different types of financial crises that have affected the economies of the world in order to draw lessons from their experiences. Analysis of this study is divided into four types of financial crises: Banking crisis, speculative bubbles and the market failures, international …

An Outlook Of Factoring Industry In The World And In Kosovo, Burhan R. Rexhepi B.R

International Journal of Business and Technology

Factoring is the most appropriate one for both bank and SMEs as it is considering a method of raising short- term working capital for enterprise by exchanging its A/R, not collateral focused and not adding any liability into their balance sheet. Moreover, factoring is a comprehensive financial service that includes not only financing but also credit protection, accounts receivable bookkeeping and collection services. Factoring not only brings benefit to CBs as a new service for diversification and increasing turnover but also supports SMEs to access financing for roll-up their business and gaining profit from achieving advantages of competitiveness. Although it …

An Overview Of Elements And Relations: Aspects Of A Scientific Metaphysics, Martin Zwick

Complex Systems Faculty Publications and Presentations

A talk on my book, Elements and Relations: Aspects of a Scientific Metaphysics. Book description:

This book develops the core proposition that systems theory is an attempt to construct an “exact and scientific metaphysics,” a system of general ideas central to science that can be expressed mathematically. Collectively, these ideas would constitute a non-reductionist “theory of everything” unlike what is being sought in physics. Inherently transdisciplinary, systems theory offers ideas and methods that are relevant to all of the sciences and also to professional fields such as systems engineering, public policy, business, and social work. To demonstrate the generality …

Large Language Model Use Cases For Instruction, Plus A Primer On Prompt Engineering, Roy Haggerty, Justin Cochran

LSU Health New Orleans Symposium Series on Artificial Intelligence

AMA Credit Designation Statement: The Louisiana State University School of Medicine, New Orleans designates this live activity for a maximum of 1.0 AMA PRA Category 1 Credit™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

NCPD Credit Designation Statement: Nursing participants may earn 1.0 NCPD contact hours. Each nursing participant must be present for the entire session for which NCPD contact hours are requested and must complete an evaluation of the session to receive credit.

Machine Learning For Electronic Design Automation: Specification Mining And High-Level Synthesis, Md Rubel Ahmed

USF Tampa Graduate Theses and Dissertations

The rapid growth of complex system-on-chip (SoC) designs has presented unprecedented opportunities and challenges in electronic design automation (EDA). This dissertation explores two facets of electronic design automation: message flow specification mining using data mining and natural language processing (NLP) and high-level synthesis (HLS) acceleration using different machine learning (ML) methods. It also discusses an ML model co-optimization method for energy-efficient hardware implementation.

Effective SoC design validation relies heavily on message flow specifications. This dissertation presents an efficient technique for synthesizing finite state automaton (FSA) models from SoC execution traces. The synthesized models can provide valuable insights into the on-chip …

Foundation Of The Superhypersoft Set And The Fuzzy Extension Superhypersoft Set: A New Vision, Florentin Smarandache

Neutrosophic Systems with Applications

We introduce for the first time the SuperHyperSoft Set and the Fuzzy and Fuzzy Extension SuperHyperSoft Set. Through a theorem, we prove that the SuperHyperSoft Set is composed from many HyperSoft Sets.

Foundation Of The Superhypersoft Set And The Fuzzy Extension Superhypersoft Set: A New Vision, Florentin Smarandache

Neutrosophic Systems with Applications

We introduce for the first time the SuperHyperSoft Set and the Fuzzy and Fuzzy Extension SuperHyperSoft Set. Through a theorem, we prove that the SuperHyperSoft Set is composed from many HyperSoft Sets.

Bridging Domain Gaps For Cross-Spectrum And Long-Range Face Recognition Using Domain Adaptive Machine Learning, Cedric Armel Nimpa Fondje

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Face recognition technology has witnessed significant advancements in recent decades, enabling its widespread adoption in various applications such as security, surveillance, and biometrics applications. However, one of the primary challenges faced by existing face recognition systems is their limited performance when presented with images from different modalities or domains( such as infrared to visible, long range to close range, nighttime to daytime, profile to f rontal, etc.) Additionally, advancements in camera sensors, analytics beyond the visible spectrum, and the increasing size of cross-modal datasets have led to a particular interest in cross-modal learning for face recognition in the biometrics and …

S-Net: A Multiple Cross Aggregation Convolutional Architecture For Automatic Segmentation Of Small/Thin Structures For Cardiovascular Applications, Nan Mu, Zonghan Lyu, Mostafa Rezaeitaleshmahalleh, Cassie Bonifas, Jordan Gosnell, Marcus Haw, Joseph Vettukattil, Jingfeng Jiang

Michigan Tech Publications

With the success of U-Net or its variants in automatic medical image segmentation, building a fully convolutional network (FCN) based on an encoder-decoder structure has become an effective end-to-end learning approach. However, the intrinsic property of FCNs is that as the encoder deepens, higher-level features are learned, and the receptive field size of the network increases, which results in unsatisfactory performance for detecting low-level small/thin structures such as atrial walls and small arteries. To address this issue, we propose to keep the different encoding layer features at their original sizes to constrain the receptive field from increasing as the network …

Motif-Cluster: A Spatial Clustering Package For Repetitive Motif Binding Patterns, Mengyuan Zhou

School of Computing: Dissertations, Theses, and Student Research

Previous efforts in using genome-wide analysis of transcription factor binding sites (TFBSs) have overlooked the importance of ranking potential significant regulatory regions, especially those with repetitive binding within a local region. Identifying these homogenous binding sites is critical because they have the potential to amplify the binding affinity and regulation activity of transcription factors, impacting gene expression and cellular functions. To address this issue, we developed an open-source tool Motif-Cluster that prioritizes and visualizes transcription factor regulatory regions by incorporating the idea of local motif clusters. Motif-Cluster can rank the significant transcription factor regulatory regions without the need for experimental …

Cyberattacks And Security Of Cloud Computing: A Complete Guideline, Muhammad Dawood, Shanshan Tu, Chuangbai Xiao, Hisham Alasmary, Muhammad Waqas, Sadaqat Ur Rehman

Research outputs 2022 to 2026

Cloud computing is an innovative technique that offers shared resources for stock cache and server management. Cloud computing saves time and monitoring costs for any organization and turns technological solutions for large-scale systems into server-to-service frameworks. However, just like any other technology, cloud computing opens up many forms of security threats and problems. In this work, we focus on discussing different cloud models and cloud services, respectively. Next, we discuss the security trends in the cloud models. Taking these security trends into account, we move to security problems, including data breaches, data confidentiality, data access controllability, authentication, inadequate diligence, phishing, …

Smartphone Based Object Detection For Shark Spotting, Darrick W. Oliver

Master's Theses

Given concern over shark attacks in coastal regions, the recent use of unmanned aerial vehicles (UAVs), or drones, has increased to ensure the safety of beachgoers. However, much of city officials' process remains manual, with drone operation and review of footage still playing a significant role. In pursuit of a more automated solution, researchers have turned to the usage of neural networks to perform detection of sharks and other marine life. For on-device solutions, this has historically required assembling individual hardware components to form an embedded system to utilize the machine learning model. This means that the camera, neural processing …

Examining The Externalities Of Highway Capacity Expansions In California: An Analysis Of Land Use And Land Cover (Lulc) Using Remote Sensing Technology, Serena E. Alexander, Bo Yang, Owen Hussey, Derek Hicks

Mineta Transportation Institute

There are over 590,000 bridges dispersed across the roadway network that stretches across the United States alone. Each bridge with a length of 20 feet or greater must be inspected at least once every 24 months, according to the Federal Highway Act (FHWA) of 1968. This research developed an artificial intelligence (AI)-based framework for bridge and road inspection using drones with multiple sensors collecting capabilities. It is not sufficient to conduct inspections of bridges and roads using cameras alone, so the research team utilized an infrared (IR) camera along with a high-resolution optical camera. In many instances, the IR camera …

Demo Abstract: Vgglass - Demonstrating Visual Grounding And Localization Synergy With A Lidar-Enabled Smart-Glass, Darshana Rathnayake, Dulanga Weerakoon, Meeralakshmi Radhakrishnan, Vigneshwaran Subbaraju, Inseok Hwang, Archan Misra

Research Collection School Of Computing and Information Systems

This work demonstrates the VGGlass system, which simultaneously interprets human instructions for a target acquisition task and determines the precise 3D positions of both user and the target object. This is achieved by utilizing LiDARs mounted in the infrastructure and a smart glass device worn by the user. Key to our system is the union of LiDAR-based localization termed LiLOC and a multi-modal visual grounding approach termed RealG(2)In-Lite. To demonstrate the system, we use Intel RealSense L515 cameras and a Microsoft HoloLens 2, as the user devices. VGGlass is able to: a) track the user in real-time in a global …

Joint Location And Cost Planning In Maximum Capture Facility Location Under Random Utilities, Ngan H. Duong, Tien Thanh Dam, Thuy Anh Ta, Tien Mai

Research Collection School Of Computing and Information Systems

We study a joint facility location and cost planning problem in a competitive market under random utility maximization (RUM) models. The objective is to locate new facilities and make decisions on the costs (or budgets) to spend on the new facilities, aiming to maximize an expected captured customer demand, assuming that customers choose a facility among all available facilities according to a RUM model. We examine two RUM frameworks in the discrete choice literature, namely, the additive and multiplicative RUM. While the former has been widely used in facility location problems, we are the first to explore the latter in …

Robust Maximum Capture Facility Location Under Random Utility Maximization Models, Tien Thanh Dam, Thuy Anh Ta, Tien Mai

Research Collection School Of Computing and Information Systems

We study a robust version of the maximum capture facility location problem in a competitive market, assuming that each customer chooses among all available facilities according to a random utility maximization (RUM) model. We employ the generalized extreme value (GEV) family of models and assume that the parameters of the RUM model are not given exactly but lie in convex uncertainty sets. The problem is to locate new facilities to maximize the worst-case captured user demand. We show that, interestingly, our robust model preserves the monotonicity and submodularity from its deterministic counterpart, implying that a simple greedy heuristic can guarantee …

Deep Learning-Based Automatic Stereology For High- And Low-Magnification Images, Hunter Morera

USF Tampa Graduate Theses and Dissertations

Quantification of the true number of stained cells in specific brain regions is an important metric in many fields of biomedical research involving cell degeneration, cytotoxicology, cellular inflammation, and drug development for a wide range of neurological disorders and mental illnesses. Unbiased stereology is the current state-of-the-art method for collecting the cell count data from tissue sections. These studies require trained experts to manually focus through a z-stack of microscopy images and count (click) on a hundred or more cells per case, making this approach time consuming (~1 hour per case) and prone to human error (i.e., inter-rater variability). Thus, …

Demo-Abstract: A Dtn System For Tracking Miners Using Gae-Lstm And Contact Graph Routing In An Underground Mine, Abhay Goyal, Sanjay Kumar Madria, Samuel Frimpong

Computer Science Faculty Research & Creative Works

Localization and prediction of movement of miners in underground mines have been a constant problem more so during a mine disaster. Due to the unavailability of GPS signals, the pillars are used as a method to locate these miners, and thus, location prediction is also carried out with reference to these pillars. In this work, we demon- strate a Delay-tolerant Network (DTN) system called Miner-Finder that leverages Machine Learning (ML) framework (GAE-LSTM) that works on edge devices (e.g., mobile phones, tablets) to predict the location of miners in an underground mine. The information such as speed, angle, time, nearest pillar …

Electromagnetic Transient Equivalent Modeling Method For Wind Power Clusters Adapted To Expected Faults, Dongsheng Li, Ye Liu, Yankan Song, Chen Shen

Journal of System Simulation

Abstract: Based on an existing equivalent modeling method for individual wind farm, an iterative simulation-based equivalent modeling method for wind power clusters is proposed and a software development for equivalent modeling of wind power clusters is completed by using CloudPSS-XStudio suite. The system integrates expected fault selection, equivalent parameter calculation and result analysis, which provides support for dynamic security assessment of power systems with large-scale wind power clusters. The equivalent method takes the average wind speed of each wind farm and the expected faults as input, and obtains the cluster index of each wind turbine based on the iterative simulation …

Key Technology And Application Of Digital Twin Modeling For Mri, Shanshan Chen, Hongzhi Wang, Tian Xia

Journal of System Simulation

Abstract: With the accelerating digitalization in education, the construction of digital resources and application platforms has caught increasing attention. The framework of MRI equipment digital twin fivedimensional model is constructed to solve the problems in teaching and training for magnetic resonance imaging (MRI). A modeling and simulation method based on the mechanism model is proposed. The multi-dimensional physical data are obtained to perform digital human modeling, and the virtual acquisition and image reconstruction method is proposed to generate images. The digital twin data are adopted for iterative optimization to implement the whole process of the three-dimensional visual operation including preparation …

A Hybrid Empirical Method For Fast Modeling Of Ship Manoeuvring Motion, Peng Wu, Zongmo Yang, Qianfeng Jing, Yulin Li

Journal of System Simulation

Abstract: Simulation testing is an important means to verify the functions of intelligent ships. Ship maneuvering motion modeling and simulation is the key theoretical basis for the intelligent collision avoidance of multiple vessels in complex sea areas. To address the problem that the calculation of the hydrodynamic coefficients required for ship maneuvering modeling is complex and difficult to obtain, a hybrid empirical method is proposed, a combination method of the existing regression methods is established, the comprehensive performance indicators are constructed, the optimal hydrodynamic coefficients groups are selected by simulated maneuvering experiments, and a rapid modeling program code is developed …

Reliability Evaluation Method Of Radar Simulation Model Based On Air Combat Mechanism, Chenguang Wang, Jinpeng Bai, Tingting Li, Lifeng Miao, Kaifeng Wang

Journal of System Simulation

Abstract: In modern air combat simulation, the reliability of radar simulation model is very important. Based on simulation model VV&A theory, a cropped and suitable for engineering applications simulation model reliability evaluation method is proposed. Based on the analysis of radar use mechanism in medium and long range air combat and short range air combat is analyzed,, the requirement of radar model in air combat simulation system, the evaluation index system is established, and the reliability quantification method based on JS dispersion is proposed, which further enriches the base of basic method. The test case is designed, the simulation test …

Learning And Analysis Of Dynamic Models For Grid Discrete Events Based On Log Information, Danlong Zhu, Yunqi Yan, Ying Chen, Jiaqi Zhang, Longxing Jin, Wei Fu

Journal of System Simulation

Abstract: With the increasing scale of power grid, the massive amount of log information generated bydevices in the power grid poses a challenge to the manual analysis of abnormal grid conditions. The log information generated during the operation of the power grid has the typical discrete sequential characteristics. By analyzing the log information of grid alarm messages, a station event transition probability model and an event sequence risk calculation method are proposed to effectively model and analyze the abnormal operation level of primary and secondary systems in substations. The proposed method not only successfully identifies the event sequences corresponding to …

Research On Multi-Aircraft Air Combat Behavior Modeling Based On Hierarchical Intelligent Modeling Methods, Yukun Wang, Ze Wang, Liwei Dong, Ni Li

Journal of System Simulation

Abstract: In response to the problem of the difficulty of decision-making in the game of force under the constraints of high-dimensional state-space in multi-machine air combat confrontation scenarios, a force intelligent agent decision-making generation strategy based on deep reinforcement learning is adopted. The developing situational cognition and reward feedback generation algorithms for force intelligentgame are proposed, a behavior modeling hierarchical framework based on hybrid intelligence modeling method is constructed, which solve the technical difficulty of sparse reward in the reinforcement learning process. It provides an feasible reinforcement learning training method that can solve the large-scale, multi-model, and multi-element air combat …

Dynamic 3d Scene Perception Based On Battlefield Metaverse, Haoyu Wang, Guanghong Gong, Jihong Cai, Bipeng Ye, Zhaofang Zhou, Zheng Mei, Ni Li

Journal of System Simulation

Abstract: Informatization combat needs higher requirements for battlefield situational awareness, and the use of unmanned intelligences to conduct battlefield reconnaissance and perceive target information is particularly important. Facing the needs of complex dynamic environment localization and target recognition, a dynamic 3D scene perception system is proposed and constructed based on battlefield meta-universe target data and operational environment, which uses vision and IMU fusion sensor simulation data as inputs, extracts battlefield target information through instance segmentation and dense optical flow estimation network and uses it as a scene prior, and synchronizes the position estimation of unmanned intelligences in the battlefield with …