Presence Of Limited Resources Research Articles

Retrospective analysis of a single unit experience in laparoscopic cholecystectomy in Northern Sri Lanka during the Covid-19 pandemic

Introduction: Laparoscopic cholecystectomy is a surgical procedure that removes a diseased gallbladder for various indications. It is preferred over open cholecystectomy due to fewer complications and early recovery. However, it carries different operative and postoperative complications. In addition, the availability of resources and skillful surgeons limits its use worldwide. Analysing the experience of laparoscopic cholecystectomy will enhance the training and skills and improve the surgical outcome.
 Methods: All the laparoscopic cholecystectomies done from July 2020 to July 2022 were analysed retrospectively. 
 Results: This study included eighty-seven surgeries with patients ages 8 to 84 years (mean 51.76 ±17.15). Male patients were 32.2% and females 67.8%. The indication for laparoscopic cholecystectomy was symptomatic gallstone disease in 72.4% acute/chronic cholecystitis in 14.9%, distal CBD stones in 5.7%, Gall bladder polyp in 3.4%, biliary colic in 18.4%, cholangitis in 1.2%, obstructive jaundice in 1.2% and pyocele in 1.2%. ERCP was performed by the surgeons of the same unit to manage 6.8% of the cases preoperatively and 2.2% post-operatively. Intra-operative difficulty or problems was seen in 24.13% of the cases, which included adhesions with adjacent organs in 14.9%, difficult identification of Calot's triangle in 3.4%, bile spillage 6.8% and abnormally distended gall bladder, adhered deep into the liver, and double gallbladder in 1.2% each. 1.2% of the cases needed conversion to open. Postoperative complications were noted in 20.68% of cases. 3.4% had Clavian Dindo grade I complications.
 Conclusion: Professorial unit Teaching hospital Jaffna is performing laparoscopic cholecystectomies even in the presence of limited resources. The outcomes were comparable with the international standards published up to date.

Role of recovery profile dependency in time‐dependent resilience

AbstractResilience assessment of civil structures and infrastructure systems plays a vital role in quantitatively measuring the object's ability to withstand and recover from disruptive events (e.g., natural hazards). The performance of the object (structure or system) may degrade with time, and the external loads often display nonstationary characteristics with time‐varying occurrence rate and/or magnitude. In this context, the resilience would be dependent on the duration of the reference period of interest, known as time‐dependent resilience. This article investigates the effect of recovery profile dependency on the time‐dependent resilience of structures and systems. The term “recovery profile dependency” refers to the association of the post‐hazard recovery processes in the aftermath of different load events within the object's service life, and is reflected through the following three aspects: (1) the temporal correlation between the remaining functionalities associated with different load events; (2) the load–recovery interaction (i.e., the scenario that a load event occurs before the full recovery of the degraded functionality due to the previous load event), and (3) the resource allocation strategy in the presence of limited resources, which affects the expeditiousness of each recovery process. In particular, for (2), the concept of average ratio of interaction is proposed to measure the frequency of load‐recovery interaction. The evaluation of time‐dependent resilience is demonstrated through two examples. It is shown that, the time‐dependent resilience is sensitive to the impact of load–recovery interaction and the selection of resource allocation strategy, but is insensitive to the temporal correlation of the remaining functionalities.

Synchronizing network systems in the presence of limited resources via edge snapping.

In this work, we propose a multilayer control protocol for the synchronization of network dynamical systems under limited resources. In addition to the layer where the interactions of the system take place, i.e., the backbone network, we propose a second, adaptive layer, where the edges are added or removed according to the edge snapping mechanism. Different from classic edge snapping, the inputs to the edge dynamics are modified to cap the number of edges that can be activated. After studying the local stability of the overall network dynamics, we illustrate the effectiveness of the approach on a network of Rössler oscillators and then show its robustness in a more general setting, exemplified with a model of the Italian high-voltage power grid.

Implementation of E-Learning in Public and Private Schools: Impact of COVID-19 Pandemic

The present study aimed to explore the impact of virtual learning on student’s educational progress related to E-learning practices during pandemic, modification of teaching methodology, skills and competencies as well as teaching effectiveness. The study was descriptive survey; in order to investigate the findings the questionnaire was circulated among 500 participants i.e the academic and administrative staff of public and private schools using simple random sampling technique. Data were analyzed by using SPSS. The empirical outcomes of this research work signify that the adoption of virtual-Learning schools drastically improved students' skills towards learning new ideas. There was no significant difference among teachers on gender basis, regarding the student’s competencies, administrative roles, and government initiatives. Moreover, in this research work high level of internal consistency has been pragmatic for scale. These findings advocate that using E-Learning in schools could be an effectual to enhance students learning and teacher’s skill. Government and administration have plenty of digital resources at school level to initiate the digitalization and should start emphasizing on practices of the virtual learning even in the presence of limited resources, not only in the duration of any pandemic but also in future perspectives.

Advances in orphan drug development: Time to change the status and stereotype.

Rare diseases remain a challenge for many of the countries in the world. The millions of people collectively suffering from rare diseases, in the context of raging COVID-19 pandemics globally, require an innovative and recent solution from different stakeholders. Regulatory bodies such as the Food and Drug Administration and the European Medicines Agency have come up with many different approaches including financial assistance to prompt drug development and approval. Novel approaches pertinent to clinical trials of such drugs such as patient centricity, early interaction with regulatory bodies, and establishing clinical outcome of interest have been experimented. Various international organizations including cross-country collaborators have initiated various projects or consortiums to bridge the gap between knowledge and practice. The challenges remain more pivotal in developing countries such as India, which has adopted few noteworthy initiatives by involving relevant stakeholders in the presence of limited resources, infrastructures, and a nascent regulatory framework. Therefore, it is imperative to revisit the key aspects of orphan drug development to fulfill the unmet needs of such patients suffering from various rare diseases.

A Deep-Learning-Based Bug Priority Prediction Using RNN-LSTM Neural

Context: Predicting the priority of bug reports is an important activity in software maintenance. Bug priority refers to the order in which a bug or defect should be resolved. A huge number of bug reports are submitted every day. Manual filtering of bug reports and assigning priority to each report is a heavy process, which requires time, resources, and expertise. In many cases mistakes happen when priority is assigned manually, which prevents the developers from finishing their tasks, fixing bugs, and improve the quality. Objective: Bugs are widespread and there is a noticeable increase in the number of bug reports that are submitted by the users and teams’ members with the presence of limited resources, which raises the fact that there is a need for a model that focuses on detecting the priority of bug reports, and allows developers to find the highest priority bug reports. This paper presents a model that focuses on predicting and assigning a priority level (high or low) for each bug report. Method: This model considers a set of factors (indicators) such as component name, summary, assignee, and reporter that possibly affect the priority level of a bug report. The factors are extracted as features from a dataset built using bug reports that are taken from closed-source projects stored in the JIRA bug tracking system, which are used then to train and test the framework. Also, this work presents a tool that helps developers to assign a priority level for the bug report automatically and based on the LSTM’s model prediction. Results: Our experiments consisted of applying a 5-layer deep learning RNN-LSTM neural network and comparing the results with Support Vector Machine (SVM) and K-nearest neighbors (KNN) to predict the priority of bug reports. The performance of the proposed RNN-LSTM model has been analyzed over the JIRA dataset with more than 2000 bug reports. The proposed model has been found 90% accurate in comparison with KNN (74%) and SVM (87%). On average, RNN-LSTM improves the F-measure by 3% compared to SVM and 15.2% compared to KNN. Conclusion: It concluded that LSTM predicts and assigns the priority of the bug more accurately and effectively than the other ML algorithms (KNN and SVM). LSTM significantly improves the average F-measure in comparison to the other classifiers. The study showed that LSTM reported the best performance results based on all performance measures (Accuracy = 0.908, AUC = 0.95, F-measure = 0.892).

Tourism and Inclusive Growth: Evaluating a Diagnostic Framework

ABSTRACT This paper aims to further advance the theoretical and practical understanding of tourism and inclusive growth by evaluating the Tourism-Driven Inclusive Growth Diagnostic (T-DIGD) framework in practice. This was done by defining a mixed-method methodology including identifying 96 indicators and applying the framework to the tourism sector of North Macedonia. Testing the diagnostic and evaluating its strengths and weaknesses showed that this is a promising approach as it can identify the possible binding constraints to tourism-driven inclusive growth out of a large selection of possible factors. It can thereby contribute to a way of systematically and transparently prioritizing policies to formulate a context-specific development strategy in the presence of limited resources. This paper is timely and relevant for tourism policy makers as there is an increased demand for tools that can be used for evidence-based policy making for tourism development.

Credibility of Risk scores in predicting coronary artery disease severity in non-ST segment elevation acute coronary syndrome patients

Abstract Objectives We aimed to assess the value of Global Registry of Acute Coronary Events (GRACE) and Thrombolysis in Myocardial Infarction (TIMI) risk scores (RSs) for predicting coronary artery disease (CAD) severity and prognosis in patients with non-ST segment elevation acute coronary syndrome (NSTE-ACS). Background Patients with NSTE-ACS are at varying risks of death and recurrent cardiac events, early risk stratification plays a central role, different scores are now available based on initial clinical history, ECG, and laboratory tests that enable early risk stratification on admission. Methods A prospective study was conducted including 100 patients (age, 45–68 years) with NSTE-ACS who were admitted at our hospital from January 2018 to January 2019. The two RSs (TIMI& GRACE) were calculated from the initial clinical history, electrocardiogram, and laboratory values collected and recorded on admission. All patients were subjected to conventional coronary angiography during admission, Patients were divided into two groups: 1) patients with syntax score ≤32 (test group, 80 patients) and 2) patients with syntax score >32 (comparative group, 20 patients). Median follow-up duration was 6 (4–9) days. Results Regarding correlation between coronary angiographic severity based on syntax score and the clinical profile based on the two RSs (TIMI&GRACE) in NSTE-ACS patients, statistically significant correlation were found between GRACE score and syntax score (r=0.789; P=0.001) with GRACE score accuracy: 94% and negative predictive value (NPV): 98.7%, whereas no statistically significant correlation were found between TIMI score and syntax score (r=0.087; P=0.388) with TIMI score accuracy: 32% and NPV: 73.1%. Conclusions In conclusion the GRACE score provides a quick and reliable prediction of CAD severity in NSTE-ACS patients, It allows accurate risk estimation, categorizes patients and consequently can help in making accurate therapeutic decisions either with the use of invasive strategies in high risk selected patients or the use of conservative strategies in low risk patients in presence of limited resources. Funding Acknowledgement Type of funding source: None

The Level of Integrated Reporting Alignment with the IIRC Framework: Evidence from South Africa

In recent years, corporate disclosure policies have undergone important changes due mainly to greater requests from stakeholders and the presence of limited resources. Companies are forced to rethink their disclosure strategies and the way they communicate to the outside, in order to increase transparency and meet the needs of their stakeholders. In this context, Integrated Reporting (IR), developed by the International Integrated Reporting Council (IIRC), represents a new way to provide, in a single document, interconnected information on strategies, risks, performance, governance and future prospects. In the development process of this reporting tool, South Africa played an important role. Therefore, this study aims to analyse the level of alignment of integrated reports with the IIRC framework in the South African contest. The results show first of all that South African companies provide integrated reports with high levels of alignment with the IIRC framework. Secondly, the analysis of the determinants shows how firm size, firm profitability and financial leverage positively affect the level of compliance of the integrated reports with the IIRC requirements.

Food Industry Forensics: Safety and Quality Issues

Taking into consideration its importance to life in general, food will stay the most fundamental of our necessities, as it represents the source of all the energy needed to carry out daily activities, including those which delineate the very specifics of life. Authorities have reinforced strict regulations for certain information to be outlined in the labels and labeling, which should comply to the rules and regulations set by describing properly the geographical provenance and authenticity of all that is claimed in terms of quality and composition on the packaging labels. The rules, guidelines and regulations that have been set utter extensively about the legality of the whole issue on food provenance and fingerprinting, with laws being enacted to prosecute the culprits, offenders and transgressors. This sort of fraud is termed as “crude fraud” and in many cases it involves expensive, highly moveable items such as alcoholic beverages. Another type of fraud that takes place within the food industry is known as “sophisticated fraud”, in which some food components are manipulated by either replacing a quality ingredient with inferior ones or the entire food product is subjected to dilution (e.g. addition of water to milk, brine to frozen meat, glycerol to wine, etc.). Urbanization and globalization encourage a specific trend of food supply chain to sustain the large population concentrated in urban areas. To control such a complex food supply chain in the current global economy in the presence of limited resources, creates room for transgressors to perform unethical business deals with food products. As time goes by, they come up with new ways of committing fraud, which leads to more challenges in dealing with this issue.

Step-up Establishment of Neurosurgical Laboratory Starting with Limited Resources—Tips and Tricks

Neurosurgical diseases have a devastating impact on society. It is estimated that approximately 14 million essential neurosurgical cases develop worldwide annually, of which more than 80% arise in low- and middle-income countries. Neurosurgical cadaveric dissection remains largely unexploited as a learning tool for the training of surgeons in developing countries, often because of the assumed high costs. The minimum requirements to establish a neurosurgical cadaver laboratory are the availability of minimally equipped environment to perform dissection, respecting safety requirements, fitting surgical instruments, anatomic samples, and materials to be used for preservation and preparation of anatomical specimens. Moving from these basic foundations, we established our Neurosurgical Dissection Laboratory at Fondazione Policlinico Universitario A. Gemelli IRCCS in Rome, Italy. The laboratory is located at the Institute of Public Health Section of Legal Medicine of University. After reviewing relevant literature and discussing our experience, we provide advice for setting up a neurosurgical dissection cadaver laboratory with specific focus on suitable location identification, surgical equipment procurement, fresh cadaver and frozen specimen acquisition, and preparation and description of a step-up strategy to progressively enrich the laboratory. Our study demonstrates the feasibility of establishing a neurosurgical cadaver dissection laboratory for training and research purposes even in presence of limited resources. The introduction of cost-effective guidelines and targeted funding could represent an added value to target the unmet neurosurgical disease need by promoting development of local neurosurgical expertise with the aim of providing health coverage for the treatment of common neurosurgical pathologies in developing countries.

Determinants of cancer screening awareness and participation among Indonesian women

BackgroundCancer screening awareness and participation may be lower in low- and middle-income countries that lack established national screening programmes compared with those that do. We evaluated potential determinants of awareness about and participation in breast and cervical cancer screening, and breast self-examination (BSE) in women using survey data from Indonesia.MethodsFrom the fifth Indonesian Family Life Survey (2014–2015), a total of 5397 women aged 40 and older without any history of cancer who responded to questionnaires concerning Pap smears, mammography, and BSE were included. Multilevel modelling was used to assess potential determinants in relation to awareness about Pap smears and mammography, and participation in Pap smears and BSE practice. Multivariable analyses were performed to identify independent predictors of cancer screening.ResultsOf the 5397 respondents, 1058 (20%) women were aware of Pap smears, of which 297 had never had the procedure. Only 251 (5%) participants were aware of mammography. A total of 605 (12%) of women reported they performed BSE. Higher education and household expenditure were consistently associated with higher odds of awareness about Pap smears and mammography (e.g. odds ratio [OR] of being aware of Pap smear and mammography: 7.82 (95% CI: 6.30–9.70) and 7.70 (6.19–9.58), respectively, for high school graduates compared to women with less educational attainment in the multivariable models), and participation in Pap smears and BSE. We also identified enabling factors linked with greater cancer screening awareness and participation, including health insurance, shorter distance to health services, and social participation.ConclusionThere are socioeconomic disparities in cancer screening awareness and participation among Indonesian women. Our findings may help inform targeted health promotion and screening for cancer in the presence of limited resources.

Supermodular Batch State Estimation in Optimal Sensor Scheduling

This letter addresses the problem of activating, at each time-step in a finite time horizon problem, a subset of available sensors to generate a “high quality” estimate of the state of a discrete-time linear system operating under limited resources. We propose a sensor schedule that minimizes the mean square estimation error of the batch state vector of the system—the batch state estimation (BSE) problem. Due to the presence of limited resources, we address the cardinality-constrained BSE problem, which is inherently combinatorial and computationally intractable when working with large-scale systems. This NP-hard complexity is overcome by employing a greedy algorithm, which returns a near-optimal sensor schedule with performance guarantees when minimizing a supermodular objective over matroids . To this end, we prove (despite the existence of counter-examples in literature) that our objective function is supermodular when the batch prior information matrix is a strictly diagonally dominant ${M}$ -matrix (with a constraint on its inverse and conditions on the measurement model). Hence, we obtain a near-optimal solution to the BSE problem via a greedy algorithm. Additionally, we provide its time complexity.

Online Healthcare Community Interaction Dynamics

With the increasing dilemma of the rapid global demand for healthcare services (often in the presence of limited resources), how to creatively allocate and use healthcare resources across a widespread population has become a salient issue. Online healthcare communities (OHCs) are regarded as a potential ICT-based partial solution. In contrast to traditional healthcare, online doctor-patient interaction is unlimited in terms of time and space limitations while an OHC is exposed to the whole community. These characteristics are key to achieving synergistic doctor-patient interaction and community development in the longer term. In order to explore the nature of doctor-patient interaction dynamics in an OHC, we systematically investigate doctor-patient interaction dynamics from the dual perspectives of doctor and patient. Our doctor-patient interaction dual-cycle model has been built based on six doctor-patient interaction processes (i.e., searching, choosing, knowledge sharing, providing, receiving and balancing). According to our dual-cycle model, four key managerial issues in OHC (information asymmetry, incentive mechanisms, service delivery processes and interaction mechanisms) have been identified as examples. Discussion and directions for future research, with challenges as well as opportunities, have been elaborated. A broad view with fruitful research potential is ensured and new theories and methods ultimately provide implications for effectively and efficiently allocating scarce healthcare resources to a broader population.

External control strategies for self-propelled particles: Optimizing navigational efficiency in the presence of limited resources.

We experimentally and numerically study the dependence of different navigation strategies regarding the effectivity of an active particle to reach a predefined target area. As the only control parameter, we vary the particle's propulsion velocity depending on its position and orientation relative to the target site. By introducing different figures of merit, e.g., the time to target or the total consumed propulsion energy, we are able to quantify and compare the efficiency of different strategies. Our results suggest that each strategy to navigate towards a target has its strengths and weaknesses, and none of them outperforms the other in all regards. Accordingly, the choice of an ideal navigation strategy will strongly depend on the specific conditions and the figure of merit which should be optimized.

Uterine transplantation is not a good use of limited resources: FOR: Uterine transplantation is not a good use of limited resources-a case of distributive justice and burden of disease.

The debate surrounding uterine transplantation (UTx) is complex and multifaceted. Although its scientific merit has recently been put in the spotlight, the social, economic and ethical considerations implicated have been largely left out of the mainstream conversation. In its current state, a principlistic analysis of UTx reveals arguments in favour of the principles of autonomy and beneficence, but it remains largely equivocal with regards to the principle of justice (Lefkowitz et al. Transpl Int 2012; 25:439–47). Successful public healthcare systems aim to abide by the principle of distributive justice, where providers seek to allocate the scarce resources at their command (operating rooms, time of physicians and nurses, medical supplies) in a just way so as to most efficiently address the needs, health and welfare of individuals and groups within the population. The aim of such an approach is to ensure maximisation of quality-adjusted life-years (Skedgel et al. Med Decis Making 2015;35:94–105). In such considerations, ‘micro-allocation at the lower level’ (Breyer, F. Health care rationing and distributive justice. Rationality, Markets and Morals 2009;27:406), particularly among individuals with rare conditions, is not prioritised unless unjust burden exists, or the population-risk of not treating such individuals is disproportionate (e.g. epidemics and quarantines). Indeed, in the setting of limited resources, the needs of the people should guide the distribution of opportunities for wellbeing, including access to care and partitioning of goods and services. Relative to a number of life-threatening conditions for which there may not be treatment alternatives, the burden of disease of uterine factor infertility, the main indication for UTx, remains comparatively low. In addition, the cost of the procedure is disproportionate in comparison to the cost of its alternatives, namely surrogacy and adoption. Said cost includes four surgeries, anti-rejection regimens, at least one cycle of in vitro fertilisation, and close monitoring for at least a year after the transplant and throughout the pregnancies. Furthermore, as it stands today, the number-needed-to-treat to reach a live birth in UTx is unknown; however, in theory it is likely to be rather high because it must take into account the success of both the transplant itself and the ensuing in vitro fertilisation cycle. Hence, a cost-effectiveness analysis is necessary before allocating limited resources to this procedure. As it has been performed at an experimental stage, where it still remains, UTx programmes are better funded by grants from private research foundations and philanthropists [Brännström et al. Lancet 2015;385(9968):607–16]. Other ethical concerns that arise in the case of UTx, notably the principles of equity, inclusion and social solidarity, reveal tensions with the use of limited resources for like-procedures. A challenge exists in finding the right balance between the social responsibility of the state and the individual rights and responsibilities of citizens. Although each person should benefit from the same care, health equity is not the same as equality in health status. Inequalities in health status between individuals are inevitable consequences of genetic differences, gaps between social and economic circumstances or personal choice of lifestyle. Such individual decisions should not drive the unequal distribution of resources for expensive interventions like UTx. Although healthcare systems may no longer be exclusively concerned with the preservation of life but rather with remedying the malfunctions of the body and enhancing quality of life (Warnock. A question of life: The Warnock report on human fertilisation and embryology. Oxford: Blackwell, 1985), the use of limited resources should be morally prioritised into the research and treatment of life-threatening diseases. Indeed, in the presence of limited resources, the management of life-enhancing conditions, such as uterine factor infertility, need not be prioritised. None declared. Completed disclosure of interests form available to view online as supporting information.■ Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

A Novel Sampling Technique for Probabilistic Static Coverage Problems

Resource allocation in the presence of constraints is an important activity in many systems engineering problems such as surveillance, infrastructure planning, environmental monitoring, and cooperative task performance. The resources in many important problems are agents such as a person, machine, unmanned aerial vehicles (UAVs), infrastructures, and software. Effective execution of a given task is highly correlated with effective allocation of resources to execute the task. An important class of resource allocation problem in the presence of limited resources is static coverage problem. In static coverage problems, it is necessary to allocate resources (stationary configuration of agents) to cover an area of interest so that an event or spatial property of the area can be detected or monitored with high probability. In this paper, we outline a novel sampling algorithm for the static coverage problem in presence of probabilistic resource intensity allocation maps (RIAMs). The key intuition behind our sampling approach is to use the finite number of samples to generate an accurate representation of RIAM. The outlined sampling technique is based on an optimization framework that approximates the RIAM with piecewise linear surfaces on the Delaunay triangles and optimizes the sample placement locations to decrease the difference between the probability distribution and Delaunay triangle surface. Numerical results demonstrate that the algorithm is robust to the initial sample point locations and has superior performance in a wide range of theoretical problems and real-life applications. In a real-life application setting, we demonstrate the efficacy of the proposed algorithm to predict the position of wind stations for monitoring wind speeds across the U.S. The algorithm is also used to give recommendations on the placement of police cars in San Francisco and weather buoys in Pacific Ocean.

The fine art of user-centered software development

In this article, we report on the user-centered development of a mobile medical app under limited resources. We discuss (non-functional) quality attributes that we used to choose the platform for development of the medical app. As the major contribution, we show how to integrate user-centered design in an early stage of mobile app development under the presence of limited resources. Moreover, we present empirical results gained from our two-stage testing procedure including recommendations to provide both a useful and useable business app.

Message Passing for Distributed QoS-Security Tradeoffs

Abstract : Information Assurance (IA) is of growing concern to the field of distributed systems. However, IA cannot be considered in isolation, as it interacts with Quality of Service (QoS); in the presence of limited resources, the security mechanisms employed for IA (e.g., firewalls, antivirus, encryption) usually adversely affect QoS levels delivered by a system. The system therefore needs to make a tradeoff between IA and QoS. This tradeoff is complicated by the fact that users' relative preferences over QoS/IA aspects change based on the situation, the interests of different users conflict, and tradeoff decisions made at one node in the distributed system typically affect other nodes as well.

SURVEY ON MOBILE AD HOC NETWORK ATTACKS AND MITIGATION USING ROUTING PROTOCOLS

Mobile Ad hoc Networks (MANET) due to its unpredictable topology and bandwidth limitations are vulnera ble to attacks. Establishing security measures and find ing secure routes are the major challenges faced by MANET. Security issues faced by ad hoc networks are node a uthentication, insider attack and intrusion detecti on. Implementing security measures is challenging due to the presence of limited resources in the hardware device and the network. Routing protocols attempt to mitig ate the attacks by isolating the malicious nodes. In this study, a survey of various kinds of attacks against MANET is studied. It is also proposed to study modificati on of AODV and DSR routing protocol implementation with regard to mitigating attacks and intrusion detection . This study studied various approaches to predict and mit igate attacks in MANET.