Search results for: p-hub median problem

Authors: Peyman Sindareh Esfahani, Jeffery Kurt Pieper

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In this paper, the problem of robust model predictive control (MPC) for discrete-time linear systems in linear fractional transformation form with structured uncertainty and norm-bounded disturbance is investigated. The problem of minimization of the cost function for MPC design is converted to minimization of the worst case of the cost function. Then, this problem is reduced to minimization of an upper bound of the cost function subject to a terminal inequality satisfying the l₂-norm of the closed loop system. The characteristic of the linear fractional transformation system is taken into account, and by using some mathematical tools, the robust predictive controller design problem is turned into a linear matrix inequality minimization problem. Afterwards, a formulation which includes an integrator to improve the performance of the proposed robust model predictive controller in steady state condition is studied. The validity of the approaches is illustrated through a robust control benchmark problem.

Keywords: linear fractional transformation, linear matrix inequality, robust model predictive control, state feedback control

Procedia PDF Downloads 373

Authors: Isabella Schwartz, Ori Safran, Naama Karniel, Michal Abel, Adina Berko, Martin Seyres, Tamir Tsoar, Sigal Portnoy

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Virtual Reality allows to manipulate the patient’s perception, thereby providing a motivational addition to real-time biofeedback exercises. We aimed to test the effect of manipulated virtual kinematic intervention on measures of active and passive Range of Motion (ROM), pain, and disability level in individuals with traumatic stiff shoulder. In a double-blinded study, patients with stiff shoulder following proximal humerus fracture and non-operative treatment were randomly divided into a non-manipulated feedback group (NM-group; N=6) and a manipulated feedback group (M-group; N=7). The shoulder ROM, pain, and the Disabilities of the Arm, Shoulder and Hand (DASH) scores were tested at baseline and after the 6 sessions, during which the subjects performed shoulder flexion and abduction in front of a graphic visualization of the shoulder angle. The biofeedback provided to the NM-group was the actual shoulder angle and the feedback provided to the M-group was manipulated so that 10° were constantly subtracted from the actual angle detected by the motion capture system. The M-group showed greater improvement in the active flexion ROM, with median and interquartile range of 197.1 (140.5-425.0) compared to 142.5 (139.1-151.3) for the NM-group (p=.046). Also, the M-group showed greater improvement in the DASH scores, with median and interquartile range of 67.7 (52.8-86.2) compared to 89.7 (83.8-98.3) for the NM-group (p=.022). Manipulated intervention is beneficial in individuals with traumatic stiff shoulder and should be further tested for other populations with orthopedic injuries.

Keywords: virtual reality, biofeedback, shoulder pain, range of motion

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Authors: Thomas Doutre, Emmanuel De Meric De Bellefon

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This paper describes the application of local-search metaheuristic quantum annealing to portfolio opti- mization. Heuristic technics are particularly handy when Markowitz’ classical Mean-Variance problem is enriched with additional realistic constraints. Once tailored to the problem, computational experiments on real collected data have shown the superiority of quantum annealing over simulated annealing for this constrained optimization problem, taking advantages of quantum effects such as tunnelling.

Keywords: optimization, portfolio risk management, quantum annealing, metaheuristic

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Authors: Yassir AbdelRazig

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Evolutionary optimization methods such as genetic algorithms have been used extensively for the construction site layout problem. More recently, ant colony optimization algorithms, which are evolutionary methods based on the foraging behavior of ants, have been successfully applied to benchmark combinatorial optimization problems. This paper proposes a formulation of the site layout problem in terms of a sequencing problem that is suitable for solution using an ant colony optimization algorithm. In the construction industry, site layout is a very important planning problem. The objective of site layout is to position temporary facilities both geographically and at the correct time such that the construction work can be performed satisfactorily with minimal costs and improved safety and working environment. During the last decade, evolutionary methods such as genetic algorithms have been used extensively for the construction site layout problem. This paper proposes an ant colony optimization model for construction site layout. A simple case study for a highway project is utilized to illustrate the application of the model.

Keywords: ant colony, construction site layout, optimization, genetic algorithms

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Authors: Malika Yaici, Assia Arab, Betitra Yakouben, Samia Zermani

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Ubiquitous computing is nowadays a reality through the networking of a growing number of computing devices. It allows providing users with context aware information and services in a heterogeneous environment, anywhere and anytime. Selection of the best context-aware service, between many available services and providers, is a tedious problem. In this paper, a service selection method based on Constraint Satisfaction Problem (CSP) formalism is proposed. The services are considered as variables and domains; and the user context, preferences and providers characteristics are considered as constraints. The Backtrack algorithm is used to solve the problem to find the best service and provider which matches the user requirements. Even though this algorithm has an exponential complexity, but its use guarantees that the service, that best matches the user requirements, will be found. A comparison of the proposed method with the existing solutions finishes the paper.

Keywords: ubiquitous computing, services selection, constraint satisfaction problem, backtrack algorithm

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Authors: D. K. Rao, M. G. M. Khan, K. G. Reddy

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The focus of this paper is to develop a technique of solving a combined problem of determining Optimum Strata Boundaries (OSB) and Optimum Sample Size (OSS) of each stratum, when the population understudy is skewed and the study variable has a Pareto frequency distribution. The problem of determining the OSB is formulated as a Mathematical Programming Problem (MPP) which is then solved by dynamic programming technique. A numerical example is presented to illustrate the computational details of the proposed method. The proposed technique is useful to obtain OSB and OSS for a Pareto type skewed population, which minimizes the variance of the estimate of population mean.

Keywords: stratified sampling, optimum strata boundaries, optimum sample size, pareto distribution, mathematical programming problem, dynamic programming technique

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Authors: I. A. Farhat

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The dynamic economic dispatch (DED) problem is one of the complex, constrained optimization problems that have nonlinear, con-convex and non-smooth objective functions. The purpose of the DED is to determine the optimal economic operation of the committed units while meeting the load demand. Associated to this constrained problem there exist highly nonlinear and non-convex practical constraints to be satisfied. Therefore, classical and derivative-based methods are likely not to converge to an optimal or near optimal solution to such a dynamic and large-scale problem. In this paper, an Artificial Immune System technique (AIS) is implemented and applied to solve the DED problem considering the transmission power losses and the valve-point effects in addition to the other operational constraints. To demonstrate the effectiveness of the proposed technique, two case studies are considered. The results obtained using the AIS are compared to those obtained by other methods reported in the literature and found better.

Keywords: artificial immune system, dynamic economic dispatch, optimal economic operation, large-scale problem

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez

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We consider the problem of attacks on networks. We define the concept of system survivability in networks in the presence of intelligent threats. Our setting of the problem assumes a flow to be sent from one source node to a destination node. The attacker attempts to disable the network by preventing the flow to reach its destination while the defender attempts to identify the best path-set to use to maximize the chance of arrival of the flow to the destination node. Our concept is shown to be different from the classical concept of network reliability. We distinguish two types of network survivability related to the defender and to the attacker of the network, respectively. We prove that the defender-based-network survivability plays the role of a lower bound while the attacker-based-network survivability plays the role of an upper bound of network reliability. We also prove that both concepts almost never agree nor coincide with network reliability. Moreover, we use the shortest-path problem to determine the defender-based-network survivability and the min-cut problem to determine the attacker-based-network survivability. We extend the problem to a variety of models including the minimum-spanning-tree problem and the multiple source-/destination-network problems.

Keywords: defense/attack strategies, information, networks, reliability, survivability

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Authors: Man Fung Ho, Lap So, Jiaqi Zhang, Yuheng Zhao, Huiyang Lu, Tat Shing Choi, K. Y. Michael Wong

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Nowadays, a tremendous amount of data is available in the transportation system, enabling the development of various machine learning approaches to make short-term latency predictions. A natural question is then the choice of relevant information to enable accurate predictions. Using traffic data collected from the Taiwan Freeway System, we consider the prediction of short-term latency of a freeway segment with a length of 17 km covering 5 measurement points, each collecting vehicle-by-vehicle data through the electronic toll collection system. The processed data include the past latencies of the freeway segment with different time lags, the traffic conditions of the individual segments (the accumulations, the traffic fluxes, the entrance and exit rates), the total accumulations, and the weekday latency profiles obtained by Gaussian process regression of past data. We arrive at several important conclusions about how data should be refined to obtain accurate predictions, which have implications for future system-wide latency predictions. (1) We find that the prediction of median latency is much more accurate and meaningful than the prediction of average latency, as the latter is plagued by outliers. This is verified by machine-learning prediction using XGBoost that yields a 35% improvement in the mean square error of the 5-minute averaged latencies. (2) We find that the median latency of the segment 15 minutes ago is a very good baseline for performance comparison, and we have evidence that further improvement is achieved by machine learning approaches such as XGBoost and Long Short-Term Memory (LSTM). (3) By analyzing the feature importance score in XGBoost and calculating the mutual information between the inputs and the latencies to be predicted, we identify a sequence of inputs ranked in importance. It confirms that the past latencies are most informative of the predicted latencies, followed by the total accumulation, whereas inputs such as the entrance and exit rates are uninformative. It also confirms that the inputs are much less informative of the average latencies than the median latencies. (4) For predicting the latencies of segments composed of two or three sub-segments, summing up the predicted latencies of each sub-segment is more accurate than the one-step prediction of the whole segment, especially with the latency prediction of the downstream sub-segments trained to anticipate latencies several minutes ahead. The duration of the anticipation time is an increasing function of the traveling time of the upstream segment. The above findings have important implications to predicting the full set of latencies among the various locations in the freeway system.

Keywords: data refinement, machine learning, mutual information, short-term latency prediction

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Authors: Jemini Vyas, Oluwatobi Adeyoe, Jenny Branagan, Chandran Tanabalan, Aakash Pai

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Introduction: Radical prostatectomy and radiotherapy are both viable options for the treatment of localised prostate cancer. Over the years medicine has evolved towards a patient-centred approach. Patient decision-making is not motivated by clinical outcomes alone. Geographical location and ease of access to treating clinician are contributory factors. With the development of robotic surgery, prostatectomy has been centralised into tertiary centres. This has impacted on the distances that patients and their families are expected to travel. Methods: A single centre retrospective study was undertaken over a five-year period. All patients with localised prostate cancer, undergoing radical radiotherapy or prostatectomy were collected pre-centralisation. This was compared to the total number undergoing these treatments post centralisation. Results: Pre-centralisation, both radiotherapy and prostatectomy groups had to travel a median of less than five miles for treatment. Post-centralisation of pelvic surgery, prostatectomy patients had to travel a median of more than 40 miles, whilst travel distance for the radiotherapy group was unchanged. In the post centralisation cohort, there was a 63% decline in the number of patients undergoing radical prostatectomy per month from a mean of 5.1 to 1.9. The radical radiotherapy group had a concurrent 41% increase in patient numbers with a mean increase from 13.3 to 18.8 patients per month. Conclusion: Choice of radical treatment in localised prostate cancer is based on multiple factors. This study infers that local availability can influence choice of radical treatment. It is imperative that efforts are made to maintain accessibility to all viable options for prostate cancer patients, so that patient choice is not compromised.

Keywords: prostate, prostatectomy, radiotherapy, centralisation

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Authors: Abbas Mirakhorli

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A hub covering problem is a type of hub location problem that tries to maximize the coverage area with the least amount of installed hubs. There have not been many studies in the literature about multi-objective hubs covering location problems. Thus, in this paper, a bi-objective model for the hub covering problem is presented. The two objectives that are considered in this paper are the minimization of total transportation costs and the maximization of coverage of origin-destination nodes. A genetic algorithm is presented to solve the model when the number of nodes is increased. The genetic algorithm is capable of solving the model when the number of nodes increases by more than 20. Moreover, the genetic algorithm solves the model in less amount of time.

Keywords: facility location, hub covering, multi-objective optimization, genetic algorithm

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Authors: Anjelika Kremer, Irina Nachimov, Dan Justo

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Background: C-reactive protein (CRP) serum levels are commonly measured in hospitalized patients. Elevated admission CRP serum levels and in-hospital mortality has been seldom studied in the general population of elderly patients admitted to the acute Geriatrics department. Methods: A retrospective cross-sectional study was conducted at a tertiary medical center. Included were all elderly patients (age 65 years or more) admitted to a single acute Geriatrics department from the emergency room between April 2014 and January 2015. CRP serum levels were measured routinely in all patients upon the first 24 hours of admission. A logistic regression analysis was used to study if admission CRP serum levels were associated with in-hospital mortality independent of age, gender, functional status, and co-morbidities. Results: Overall, 498 elderly patients were included in the analysis: 306 (61.4%) female patients and 192 (38.6%) male patients. The mean age was 84.8±7.0 years (median: 85 years; IQR: 80-90 years). The mean admission CRP serum levels was 43.2±67.1 mg/l (median: 13.1 mg/l; IQR: 2.8-51.7 mg/l). Overall, 33 (6.6%) elderly patients died during the hospitalization. A logistic regression analysis showed that in-hospital mortality was independently associated with history of stroke (p < 0.0001), heart failure (p < 0.0001), and admission CRP serum levels (p < 0.0001) – and to a lesser extent with age (p = 0.042), collagen vascular disease (p=0.011), and recent venous thromboembolism (p=0.037). Receiver operating characteristic (ROC) curve showed that admission CRP serum levels predict in-hospital mortality fairly with an area under the curve (AUC) of 0.694 (p < 0.0001). Cut-off value with maximal sensitivity and specificity was 19.7 mg/L. Conclusions: Admission CRP serum levels may be used to predict in-hospital mortality in the general population of elderly patients admitted to the acute Geriatrics department.

Keywords: c-reactive protein, elderly, mortality, prediction

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Authors: A. Giannakopoulos, S. B. Buckley

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Problem solving in any field is recognised as a prerequisite for any advancement in knowledge. For example in South Africa it is one of the seven critical outcomes of education together with critical thinking. As a systematic way to problem solving was initiated in mathematics by the great mathematician George Polya (the father of problem solving), more detailed and comprehensive ways in problem solving have been developed. This paper is based on the findings by the author and subsequent recommendations for further research in problem solving and critical thinking. Although the study was done in mathematics, there is no doubt by now in almost anyone’s mind that mathematics is involved to a greater or a lesser extent in all fields, from symbols, to variables, to equations, to logic, to critical thinking. Therefore it stands to reason that mathematical principles and learning cannot be divorced from any field. In management of knowledge situations, the types of problems are similar to mathematics problems varying from simple to analogical to complex; from well-structured to ill-structured problems. While simple problems could be solved by employees by adhering to prescribed sequential steps (the process), analogical and complex problems cannot be proceduralised and that diminishes the capacity of the organisation of knowledge creation and innovation. The low efficiency in some organisations and the low pass rates in mathematics prompted the author to view problem solving as a product. The authors argue that using mathematical approaches to knowledge management problem solving and treating problem solving as a product will empower the employee through further training to tackle analogical and complex problems. The question the authors asked was: If it is true that problem solving and critical thinking are indeed basic skills necessary for advancement of knowledge why is there so little literature of knowledge management (KM) about them and how they are connected and advance KM?This paper concludes with a conceptual model which is based on general accepted principles of knowledge acquisition (developing a learning organisation), knowledge creation, sharing, disseminating and storing thereof, the five pillars of knowledge management (KM). This model, also expands on Gray’s framework on KM practices and problem solving and opens the doors to a new approach to training employees in general and domain specific areas problems which can be adapted in any type of organisation.

Keywords: critical thinking, knowledge management, mathematics, problem solving

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Authors: B. Grygalewicz, R. Woroniecka, J. Rygier, K. Borkowska, A. Labak, B. Nowakowska, B. Pienkowska-Grela

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Introduction: Chronic lymphocytic leukemia (CLL) is the most common form of adult leukemia in the Western world. Hemizygous and or homozygous loss at 13q14 occur in more than half of cases and constitute the most frequent chromosomal abnormality in CLL. It is believed that deletions 13q14 play a role in CLL pathogenesis. Two microRNA genes miR-15a and miR- 16-1 are targets of 13q14 deletions and plays a tumor suppressor role by targeting antiapoptotic BCL2 gene. Deletion size, as a single change detected in FISH analysis, has haprognostic significance. Patients with small deletions, without RB1 gene involvement, have the best prognosis and the longest overall survival time (OS 133 months). In patients with bigger deletion region, containing RB1 gene, prognosis drops to intermediate, like in patients with normal karyotype and without changes in FISH with overall survival 111 months. Aim: Precise delineation of 13q14 deletions regions in two groups of CLL patients, with mono- and biallelic deletions and qualifications of their prognostic significance. Methods: Detection of 13q14 deletions was performed by FISH analysis with CLL probe panel (D13S319, LAMP1, TP53, ATM, CEP-12). Accurate deletion size detection was performed by CGH Haematological Cancer and SNP array (8x60K). Results: Our investigated group of CLL patients with the 13q14 deletion, detected by FISH analysis, comprised two groups: 18 patients with monoallelic deletions and 18 patients with biallelic deletions. In FISH analysis, in the monoallelic group the range of cells with deletion, was 43% to 97%, while in biallelic group deletion was detected in 11% to 94% of cells. Microarray analysis revealed precise deletion regions. In the monoallelic group, the range of size was 348,12 Kb to 34,82 Mb, with median deletion size 7,93 Mb. In biallelic group discrepancy of total deletions, size was 135,27 Kb to 33,33 Mb, with median deletion size 2,52 Mb. The median size of smaller deletion regions on one copy chromosome 13 was 1,08 Mb while the average region of bigger deletion on the second chromosome 13 was 4,04 Mb. In the monoallelic group, in 8/18 deletion region covered RB1 gene. In the biallelic group, in 4/18 cases, revealed deletion on one copy of biallelic deletion and in 2/18 showed deletion of RB1 gene on both deleted 13q14 regions. All minimal deleted regions included miR-15a and miR-16-1 genes. Genetic results will be correlated with clinical data. Conclusions: Application of CGH microarrays technique in CLL allows accurately delineate the size of 13q14 deletion regions, what have a prognostic value. All deleted regions included miR15a and miR-16-1, what confirms the essential role of these genes in CLL pathogenesis. In our investigated groups of CLL patients with mono- and biallelic 13q14 deletions, patients with biallelic deletion presented smaller deletion sizes (2,52 Mb vs 7,93 Mb), what is connected with better prognosis.

Keywords: CLL, deletion 13q14, CGH microarrays, SNP array

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Authors: Guncel Ozturk

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Background: Rhinoplasty is the most commonly performed cosmetic operations in plastic surgery. Maneuvers used in rhinoplasty lead to a firm and stiff nasal tip in the early postoperative months. This unnatural stability of the nose may easily cause distortion in the reshaped nose after severe trauma. Moreover, a firm nasal tip may cause difficulties in performing activities such as touching, hugging, or kissing. Decreasing the stability and increasing the mobility of the nasal tip would help rhinoplasty patients to avoid these small but relatively important problems. Methods: We use delivery approach with closed rhinoplasty and changed positions of intranasal incisions to reach a dynamic and mobile nose. A total of 203 patients who had undergone primary closed rhinoplasty in private practice were inspected retrospectively. Posterior strut flap that was connected with connective tissues in the caudal of septum and the medial crurals were formed. Cartilage of the posterior strut graft was left 2 mm thick in the distal part of septum, it was cut vertically, and the connective tissue in the distal part was preserved. Results: The median patient age was 24 (range 17-42) years. The median follow-up period was15.2 (range12-26) months. Patient satisfaction was assessed with the 'Rhinoplasty Outcome Evaluation' (ROE) questionnaire. Twelve months after surgeries, 87.5% of patients reported excellent outcomes, according to ROE. Conclusion: The soft tissue connections between that segment and surrounding structures should be preserved to save the support of the tip while having a mobile tip at the same time with this method. These modifications would access to a mobile, non-stiff, and dynamic nasal tip in the early postoperative months. Further and prospective studies should be performed for supporting this method.

Keywords: closed rhinoplasty, dynamic, mobile, tip

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Authors: Boularas El Alia, H. Rezk-Allah, S. Chaoui, A. Chama, B. Rezk-Allah

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Aims: To assess the current exposure to the PHA among various workers in the sector of asphalt and road paving. Methods: The assessment of the exposure to PHA has been performed on workers (n=14) belonging to two companies, allocated into several activities such as road paving, manufacturing of coated bituminous warm, manufacturing of asphalt cut-back, manufacturing of emulsion of asphalt. A group of control subjects (n=18) was associated. The internal exposure to PHA was investigated by measurement of the urinary excretion of 2-naphtol, urine metabolite of naphtalene, one of the biomarkers of total PHA exposure. Urine samples were collected from the exposed workers, at the beginning of the week, at the beginning of the work shift (BWBS) and at the end of the work shift, at the end of the week (ESEW). In the control subjects, single samples of urine were collected after the end of the work shift.Every subject was invited to answer a questionnaire for the collection of technical and medical data as well as smoking habits and food intake. The concentration of 2-naphtol in the hydrolysate of urine was determined spectrophotometrically, after its reaction with the Fast Blue BB salt (diazotized 4-benzoylamino-2,5-diethoxyaniline). Results: For all the workers included in the study, the 2-urinary naphtol concentrations were higher than those in the control subjects (Median=9,55 µg/g creatinine) whether it is at (BWBS) (Md=16,2 µg/g creatinine) or at (ESEW) (n=18,Median=32,22 µg/g creatinine). Considerable differences are observed according to the category of job. The concentrations are also higher among smokers. Conclusion:The results show a significant exposure, mainly during manual laying, reveals an important risk particularly for the respiratory system.Considering the current criteria, carcinogenic risk due to the PHA seems not insignificant.

Keywords: PHA, asphalt, assessment, occupational, exposure

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Authors: Nidhal Azawi

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Colonoscopy procedure is widely used in the world to detect an abnormality. Early diagnosis can help to heal many patients. Because of the unavoidable artifacts that exist in colon images, doctors cannot detect a colon surface precisely. The purpose of this work is to improve the visual quality of colonoscopy videos to provide better information for physicians by removing some artifacts. This work complements a series of work consisting of three previously published papers. In this paper, Optic flow is used for motion compensation, and then consecutive images are aligned/registered to integrate some information to create a new image that has or reveals more information than the original one. Colon images have been classified into informative and noninformative images by using a deep neural network. Then, two different strategies were used to treat informative and noninformative images. Informative images were treated by using Lucas Kanade (LK) with an adaptive temporal mean/median filter, whereas noninformative images are treated by using Lucas Kanade with a derivative of Gaussian (LKDOG) with adaptive temporal median images. A comparison result showed that this work achieved better results than that results in the state- of- the- art strategies for the same degraded colon images data set, which consists of 1000 images. The new proposed algorithm reduced the error alignment by about a factor of 0.3 with a 100% successfully image alignment ratio. In conclusion, this algorithm achieved better results than the state-of-the-art approaches in case of enhancing the informative images as shown in the results section; also, it succeeded to convert the non-informative images that have very few details/no details because of the blurriness/out of focus or because of the specular highlight dominate significant amount of an image to informative images.

Keywords: optic flow, colonoscopy, artifacts, spatial temporal filter

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Authors: Shazia Ali, Yves Mard, Éric Severin

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To the best of our knowledge, this is the first study to have analyzed the impact of a) firm-specific product-market power and b) industry competition on earnings management behavior of European firms in distress versus healthy years while controlling for firm-level characteristics. We predicted a significant relationship between firms’ product market power and earnings management tools and their trade-off under the moderation effect of financial distress. We found that the firm-level market power hereinafter referred to as MP (proxied by the industry-adjusted Lerner Index) is positively associated with both real and accrual earnings management. However, MP is associated with a higher level of real earnings management compared to accrual earnings management in distress years compared to healthy years. On the other hand, industry product market power (representing low competition and proxied by the inverse of the total number of firms in an industry hereinafter referred to as NUMB) and firms product market power (proxied by firm market share hereinafter referred to as MS) are associated with lower inflationary accruals and higher deflationary accruals respectively. On the other hand, they are found to be linked with higher real earnings management in distress versus healthy years. When we divided the sample into small and big firms based on their respective industry-year median total assets, we found that all three measures of industry competition (Industry Median Lerner Index (hereinafter referred to as IMLI), NUMB, and Herfindahl–Hirschman Index (hereinafter referred to as HHI) indicate that small firms in low-competitive industries in financial distress are more likely to inflate their earnings through discretionary accruals. While big firms in this situation are more likely to lower the use of both inflationary and deflationary discretionary accruals as indicated by IMLI and HHI and trade-off accruals earnings management for real earnings management as indicated by NUMB. Moreover, IMLI and HHI did not show any interesting results when we divided the sample based on the firm Lerner Index/Market Power. However, the distressed firms with high market power (MP>industry median) are found to engage in income-decreasing discretionary accruals in low-competitive industries (high NUMB). Whereas firms with low market power in the same industry use downward discretionary accruals but inflate income using real activities (abnCFO). Our findings are robust across alternate measures of discretionary accruals and financial distress, such as the Altman Z-Score. The finding of the study is valuable for accounting standard setters, competition authorities, policymakers, and investors alike to help in informed decision-making.

Keywords: financial distress, earnings management, market competition

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Authors: Md. Zahidul Islam, Mohamed Shujau Abdul Hakeem

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Illegal immigrants’ problem is a big problem all over the world including Maldives. Nowadays, it is turned into a major problem for Maldives. Many illegal immigrants are staying in Maldives from different countries such as Bangladesh, India, Pakistan, Nepal, Philippines and Sri Lanka. The aim of this article is to highlight the present situation of illegal immigrant in Maldives. At the same time, this article also tries to explain the legal protection of illegal immigrant. The research will adopt qualitative methods of research. The qualitative method involves doctrinal. As a doctrinal research, author used secondary sources. As secondary sources, the author used journal articles, newspapers and other useful materials to help the purpose of this research. Government agencies have to more concern to solve this problem.

Keywords: critical appraisal, illegal immigrants, Maldives, overview

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Authors: Bezhan Ghvaberidze

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A fuzzy multi-objective facility location-selection problem (FLSP) under uncertain and extreme environments based on possibility theory is developed. The model’s uncertain parameters in the q-rung orthopair fuzzy values are presented and transformed in the Dempster-Shaper’s belief structure environment. An objective function – distribution centers’ selection ranking index as an extension of Dempster’s extremal expectations under discrimination q-rung orthopair fuzzy information is constructed. Experts evaluate each humanitarian aid from distribution centers (HADC) against each of the uncertain factors. HADCs location problem is reduced to the bicriteria problem of partitioning the set of customers by the set of centers: (1) – Minimization of transportation costs; (2) – Maximization of centers’ selection ranking indexes. Partitioning type constraints are also constructed. For an illustration of the obtained results, a numerical example is created from the facility location-selection problem.

Keywords: FLSP, multi-objective combinatorial optimization problem, evidence theory, HADC, q-rung orthopair fuzzy set, possibility theory

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Authors: Zhenjie Liu

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This paper investigates the existence and uniqueness of solutions for singular higher order boundary value problems on time scales by using mixed monotone method. The theorems obtained are very general. For the different time scale, the problem may be the corresponding continuous or discrete boundary value problem.

Keywords: mixed monotone operator, boundary value problem, time scale, green's function, positive solution, singularity

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Authors: Mohammad Jalali Varnamkhasti

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The genetic algorithms have been very successful in handling difficult optimization problems. The fundamental problem in genetic algorithms is premature convergence. This paper, present a new fuzzy genetic algorithm based on chaotic values instead of the random values in genetic algorithm processes. In this algorithm, for initial population is used chaotic sequences and then a new sexual selection proposed for selection mechanism. In this technique, the population is divided such that the male and female would be selected in an alternate way. The layout of the male and female chromosomes in each generation is different. A female chromosome is selected by tournament selection size from the female group. Then, the male chromosome is selected, in order of preference based on the maximum Hamming distance between the male chromosome and the female chromosome or The highest fitness value of male chromosome (if more than one male chromosome is having the maximum Hamming distance existed), or Random selection. The selections of crossover and mutation operators are achieved by running the fuzzy logic controllers, the crossover and mutation probabilities are varied on the basis of the phenotype and genotype characteristics of the chromosome population. Computational experiments are conducted on the proposed techniques and the results are compared with some other operators, heuristic and local search algorithms commonly used for solving p-median problems published in the literature.

Keywords: genetic algorithm, fuzzy system, chaos, sexual selection

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Authors: Ashish Shrivastava, C. Pandu Rangan

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In this paper, we consider The Hospitals Residents problem with Social Stability (HRSS), where hospitals and residents can communicate only through the underlying social network. Those residents and hospitals which don not have any social connection between them can not communicate and hence they cannot be a social blocking pair with respect to a socially stable matching in an instance of hospitals residents problem with social stability. In large scale matching like NRMP or Scottish medical matching scheme etc. where set of agents, as well as length of preference lists, are very large, social stability is a useful notion in which members of a blocking pair could block a matching if and only if they know the existence of each other. Thus the notion of social stability in hospitals residents problem allows us to increase the cardinality of the matching without taking care of those blocking pairs which are not socially connected to each other. We know that finding a maximum cardinality socially stable matching, in an instance, of HRSS is NP-hard. This motivates us to solve this problem with bounded length preference lists on one side. In this paper, we have presented a polynomial time algorithm to compute maximum cardinality socially stable matching in a HRSS instance where residents can give at most two length and hospitals can give unbounded length preference list. Preference lists of residents and hospitals will be strict in nature.

Keywords: matching under preference, socially stable matching, the hospital residents problem, the stable marriage problem

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Authors: Adel Bouchakhchoukha, Hakim Akeb

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In this work, we propose a hybrid heuristic in order to solve the Team Orienteering Problem (TOP). Given a set of points (or customers), each with associated score (profit or benefit), and a team that has a fixed number of members, the problem to solve is to visit a subset of points in order to maximize the total collected score. Each member performs a tour starting at the start point, visiting distinct customers and the tour terminates at the arrival point. In addition, each point is visited at most once, and the total time in each tour cannot be greater than a given value. The proposed heuristic combines beam search and a local optimization strategy. The algorithm was tested on several sets of instances and encouraging results were obtained.

Keywords: team orienteering problem, vehicle routing, beam search, local search

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Authors: Claudia Ehrentraut, Osama Ibrahim, Hercules Dalianis

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Policy making situations are real-world problems that exhibit complexity in that they are composed of many interrelated problems and issues. To be effective, policies must holistically address the complexity of the situation rather than propose solutions to single problems. Formulating and understanding the situation and its complex dynamics, therefore, is a key to finding holistic solutions. Analysis of text based information on the policy problem, using Natural Language Processing (NLP) and Text analysis techniques, can support modelling of public policy problem situations in a more objective way based on domain experts knowledge and scientific evidence. The objective behind this study is to support modelling of public policy problem situations, using text analysis of verbal descriptions of the problem. We propose a formal methodology for analysis of qualitative data from multiple information sources on a policy problem to construct a causal diagram of the problem. The analysis process aims at identifying key variables, linking them by cause-effect relationships and mapping that structure into a graphical representation that is adequate for designing action alternatives, i.e., policy options. This study describes the outline of an algorithm used to automate the initial step of a larger methodological approach, which is so far done manually. In this initial step, inferences about key variables and their interrelationships are extracted from textual data to support a better problem structuring. A small prototype for this step is also presented.

Keywords: public policy, problem structuring, qualitative analysis, natural language processing, algorithm, inference extraction

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Authors: Chong-Yang Qiao, Teeravarunyou Sakol

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Current production-oriented factories need maintenance operators to work in shifts monitoring and inspecting complex systems and different equipment in the situation of mechanical breakdown. Augmented reality (AR) is an emerging technology that embeds data into the environment for situation awareness to help maintenance operators make decisions and solve problems. An application was designed to identify the problem of steam generators and inspection centrifugal pumps. The objective of this research was to find the best medium of AR and type of problem solving strategies among analogy, focal object method and mean-ends analysis. Two scenarios of inspecting leakage were temperature and vibration. Two experiments were used in usability evaluation and future innovation, which included decision-making process and problem-solving strategy. This study found that maintenance operators prefer build-in magnifier to zoom the components (55.6%), 3D exploded view to track the problem parts (50%), and line chart to find the alter data or information (61.1%). There is a significant difference in the use of analogy (44.4%), focal objects (38.9%) and mean-ends strategy (16.7%). The marked differences between maintainers and operators are of the application of a problem solving strategy. However, future work should explore multimedia information retrieval which supports maintenance operators for decision-making.

Keywords: augmented reality, situation awareness, decision-making, problem-solving

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Authors: Rui Wu

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In the volatile modern manufacturing environment, new orders randomly occur at any time, while the pre-emptive methods are infeasible. This leads to a real-time scheduling method that can produce a reasonably good schedule quickly. The dynamic Flexible Job Shop problem is an NP-hard scheduling problem that hybrid the dynamic Job Shop problem with the Parallel Machine problem. A Flexible Job Shop contains different work centres. Each work centre contains parallel machines that can process certain operations. Many algorithms, such as genetic algorithms or simulated annealing, have been proposed to solve the static Flexible Job Shop problems. However, the time efficiency of these methods is low, and these methods are not feasible in a dynamic scheduling problem. Therefore, a dynamic rule selection scheduling system based on the reinforcement learning method is proposed in this research, in which the dynamic Flexible Job Shop problem is divided into several parallel machine problems to decrease the complexity of the dynamic Flexible Job Shop problem. Firstly, the features of jobs, machines, work centres, and flexible job shops are selected to describe the status of the dynamic Flexible Job Shop problem at each decision point in each work centre. Secondly, a framework of reinforcement learning algorithm using a double-layer deep Q-learning network is applied to select proper composite dispatching rules based on the status of each work centre. Then, based on the selected composite dispatching rule, an available operation is selected from the waiting buffer and assigned to an available machine in each work centre. Finally, the proposed algorithm will be compared with well-known dispatching rules on objectives of mean tardiness, mean flow time, mean waiting time, or mean percentage of waiting time in the real-time Flexible Job Shop problem. The result of the simulations proved that the proposed framework has reasonable performance and time efficiency.

Keywords: dynamic scheduling problem, flexible job shop, dispatching rules, deep reinforcement learning

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Authors: S. Som-Am, B. Grechuk

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Moser’s worm problem is the unsolved problem in geometry which asks for the minimal area of a convex region on the plane which can cover all curves of unit length, assuming that curves may be rotated and translated to fit inside the region. We study a version of this problem asking for a minimal convex cover for closed unit curves. By combining geometric methods with numerical box’s search algorithm, we show that any such cover should have an area at least 0.0975. This improves the best previous lower bound of 0.096694. In fact, we show that the minimal area of convex hull of circle, equilateral triangle, and rectangle of perimeter 1 is between 0.0975 and 0.09763.

Keywords: Moser’s worm problem, closed arcs, convex cover, minimal-area cover

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Authors: N. H. D. P. Fonseka, I. H. Rajapakse, A. S. Dissanayake

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Background: Problem drinking, namely alcohol dependence (AD) and alcohol abuse (AA) are associated with major medical, social and economic adverse consequences. Problem drinking behavior is noted among those admitted to hospitals due to alcohol-related medical/surgical complaints as well as those with unrelated complaints. Literature shows an association between alcohol consumption and depression. Aims of this study were to determine the frequency of problem drinking and depression among males with a history of alcohol consumption tertiary care setting in Southern Sri Lanka. Method: Two-hundred male patients who consumed alcohol, receiving care in medical and surgical wards in Teaching Hospital Galle, were assessed. A validated J12 questionnaire of the Mini International Neuropsychiatric Interview was administered to determine frequency AA and AD. A validated PHQ 9 questionnaire to determine the prevalence and severity of depression. Results: Sixty-three participants (31%) had problem drinking. Of them, 61% had AD, and 39% had AA. Depression was noted in 39 (19%) subjects. In those who reported alcohol consumption not amounting to problem drinking, depression was noted in 23 (16%) participants. Mild depression was seen in 17, moderate in five and moderately severe in one. Among those who had problem drinking, 16 (25%) had depression. Mild depression was seen in four, moderate in seven, moderately severe in three and severe in two. Conclusions: A high proportion alcohol users had problem drinking. Adverse consequences associated with problem drinking places a major strain on the health system especially in a low resource setting where healthcare spending is limited and alcohol cessation support services are not well organised. Thus alcohol consumption and problem drinking behaviour need to be inquired into all medical consultations. Community prevalence of depression in Sri Lanka is approximately 10%. Depression among those consuming alcohol was two times higher compared to the general population. The rates of depression among those with problem drinking were especially high being 2.5 times more common than in the general population. A substantial proportion of these patients with depression had moderately severe or severe depression. When depression coexists with problem drinking, it may increase the tendency to consume alcohol as well as act as a barrier to the success of alcohol cessation interventions. Thus screening all patients who consume alcohol for depression, especially those who are problem drinkers becomes an important step in their clinical evaluation. In addition, in view of the high prevalence of problem drinking and coexistent depression, the need to organize a structured alcohol cessation support service in Sri Lanka as well as the need for increasing access to psychological evaluation and treatment of those with problem drinking are highlighted.

Keywords: alcohol abuse, alcohol, depression, problem drinking

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Authors: Beruk Berhanu Desalegn, Kebede Awgechew, Addisalem Mesfin

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Introduction: This study aimed to investigate and compare the energy and selected nutrient intakes of sport science and non-sport science University students of Southern Ethiopia. Method: Multiple-day dietary data were collected from 166 university students (76 sport science and 90 non-sport sciences). Average daily energy and nutrient intake, and inadequate intakes were calculated using NutriSurvey (NS). Results: There were significant differences (p < 0.05) in the median intakes of energy, total carbohydrate, and vitamin B1 between female students from the sport science and non-sport science groups, but only the median intake of iron was significantly different (p < 0.05) between the male sport and non-sport science students’ group. The prevalence of inadequate intake of vitamin B1 were significantly (p<0.05) higher in the male and female from the non-sport science groups compared to the male and female students’ groups in the sport science, respectively. Whereas, the prevalence of inadequate iron intake by the male sport science students’ group was significantly (p<0.05) higher compared to their counterparts. Similarly, the prevalence of inadequate energy among the females from the sport science group was significantly (p<0.05) higher compared to the female students from the non-sport science department group. The prevalence of inadequate intakes of dietary energy, and the majority of the nutrients (protein, fat, vitamin A, B1, B2, and magnesium) were high (>50%) in selected University students. Conclusion: The energy and majority of nutrient intakes by the students in the selected universities of southern Ethiopia were sub-optimal. Therefore, activities that will improve the dietary intake of University students should include weekly meal plan revision considering their average recommended nutrient intake (RNI).

Keywords: dietary intake, sport science, University students, Ethiopia

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