Fuzzy regression

Financial markets exhibit high volatility driven by economic indicators, global events, and investor sentiment, making accurate price prediction crucial for portfolio management and risk assessment. This paper presents a comprehensive framework for equity price prediction using Long Short-Term Memory (LSTM) networks integrated with a Django-based web application. The system incorporates historical market data extraction via APIs, advanced preprocessing techniques including normalization and feature engineering, and a bidirectional LSTM architecture for temporal pattern recognition. Performance evaluation on S&P 500 data demonstrates significant improvements over traditional ARIMA models, achieving 23.7% reduction in RMSE and 19.2% reduction in MAE. The web interface enables real-time prediction, comparative analysis, and risk assessment tools for both institutional and retail investors. This integrated approach bridges the gap between academic research and practical financial technology deployment.

No Child Left Behind (NCLB) implementation and results have stimulated vigorous debates about the benefits and harm of accountability policies. Despite robust criticisms, some form of accountability for publicly-funded education to safeguard school and teaching quality and equitable treatment of students is important for serving the public interest. The Race to the Top initiative and pending re-authorization of the Elementary and Secondary Education Act (ESEA) raise questions about alternative models of accountability that might be more effective in generating these valued outcomes. The U.S. test-based accountability model holds schools and teachers accountable for student outcomes with little attention to school improvement processes. Many other countries enact more school-centered accountability efforts, such as school self-evaluation followed by inspection (SSE/I) to examine school quality, as in similar systems in England, Wales, Northern Ireland, and the Netherlands. SSE/I is a complex policy instrument with mixed consequences and many research questions still to be answered. Moreover, accountability models from other countries cannot be naively imported to the U.S. given the vital distinctions in sociopolitical contexts. That being said, a look at some of the purposes or principles behind SSE/I-especially its emphasis on quality improvement-can nevertheless inform efforts to redesign and improve the U.S. accountability model. The purpose of this brief is to take just such a look at this model. Complexities of adapting an SSE/I model include questions about: appropriate purpose and scope; credentials of external inspectors; conceptions of and criteria for school quality; engagement of all stakeholders in design efforts; and adequate funding. In relation to these concerns, we recommend that policymakers consider the following as starting points for incorporating SSE/I notions in the U.S. context: 1. Instead of sanctions-based inspections for making summative judgments about schools, employ external reviews that focus on providing guidance and support for school development and improvement. Proportionate reviews targeting struggling schools might provide external guidance and support where they are needed most, and they might also allow for the most efficient resource allocation. ii of ii 2. Employ as external reviewers qualified experts who meet a prescribed standard for qualifications and required experience. Robust training should initially be compulsory and then required on an on-going basis. 3. Incorporate a broad set of school quality criteria that goes beyond standardized test scores to adequately represent other valued aspects of quality teaching and learning. In particular, we recommend teaching quality be defined in relationship to a specific set of criteria. 4. Include the perspectives of multiple stakeholders (administrators, teachers, students, parents, community leaders, and researchers) in design efforts, allowing all key stakeholder groups to participate directly. 5. Recalibrate and revitalize existing state resources (e.g., regional offices of education) to support external review initiatives.

This paper presents a Neural Network (NN) identification of icing parameters in an A340 aircraft and a reconfiguration technique to keep the A/C performance close to the performance prior to icing. Five aircraft parameters are assumed to be considerably affected by icing. The off-line training for identifying the clear and iced dynamics is based on the Levenberg-Marquard Backpropagation algorithm. The icing parameters are located in the system matrix. The physical locations of the icing are assumed at the right and left wings. The reconfiguration is based on the technique known as the control mixer approach or pseudo inverse technique. This technique generates the new control input vector such that the A/C dynamics is not much affected by icing. In the simulations, the longitudinal and lateral dynamics of an Airbus A340 aircraft model are considered, and the stability derivatives affected by icing are identified. The simulation results show the successful NN identification of the ic...

In this paper, we compare the efficiency of two binary classifiers. The first one uses the Weighted Ordered Weighted Averaging (WOWA) aggregation function whose coefficients are learned thanks to a genetic algorithm. The second is based on an artificial neural network trained by a backpropagation algorithm. They are trained to be used in a multi-criteria decision system. These kind of multi-criteria system are more and more common in the cyber-defence field. In this work, we compare the performance of these two classifiers by using two criteria: Area Under the Curve of a Receiver Operating Characteristics (ROC) curve and the Area Under the Curve of a Precision-Recall (P-R) curve. This second criterion is more adapted for imbalanced dataset what is often the case in the cyber-security field. We perform a complete parameter study of these classifiers to optimize their performance. The dataset used for this work is a pool of Hypertext Preprocessor (PHP) files analyzed by a multiagent PHP webshell detector. We obtain different good results, especially for neural networks and highlights the advantage of the genetic algorithm method that allows a physical interpretation of the result.

In this paper, we compare the efficiency of two binary classifiers. The first one uses the Weighted Ordered Weighted Averaging (WOWA) aggregation function whose coefficients are learned thanks to a genetic algorithm. The second is based on an artificial neural network trained by a backpropagation algorithm. They are trained to be used in a multi-criteria decision system. These kind of multi-criteria system are more and more common in the cyber-defence field. In this work, we compare the performance of these two classifiers by using two criteria: Area Under the Curve of a Receiver Operating Characteristics (ROC) curve and the Area Under the Curve of a PrecisionRecall (P-R) curve. This second criterion is more adapted for imbalanced dataset what is often the case in the cyber-security field. We perform a complete parameter study of these classifiers to optimize their performance. The dataset used for this work is a pool of Hypertext Preprocessor (PHP) files analyzed by a multiagent PH...

In this paper, a novel hybrid method based on fuzzy neural network for approximate fuzzy coefficients (parameters) of fuzzy linear and nonlinear regression models with fuzzy output and crisp inputs, is presented. Here a neural network is considered as a part of a large field called neural computing or soft computing. Moreover, in order to find the approximate parameters, a simple algorithm from the cost function of the fuzzy neural network is proposed. Finally, we illustrate our approach by some numerical examples.

Sektor industri kecil sebagai salah satu alternatif penciptaan lapangan kerja yang banyak menyerap tenaga kerja yang sangat dibutuhkan seperti industri sandal sepatu di Kecamatan Waru. Jumlah pengrajin yang ada di Kecamatan Waru diharapkan mampu banyak menyerap tenaga kerja bagi penduduk di sekitar lokasi industri sehingga mampu membantu mengurangi jumlah pengangguran. Penelitian ini bertujuan untuk : (1) mengetahui karakteristik pengrajin industri sandal sepatu di Kecamatan Waru, (2) mengetahui peranan industri sandal sepatu terhadap penyerapan tenaga kerja di Kecamatan Waru, (3) mengetahui pemasaran dari industri sandal sepatu di Kecamatan Waru. Jenis penelitian ini termasuk penelitian survey. Subyek penelitian ini adalah semua pengrajin industri sandal sepatu yang ada di Kecamatan Waru sebanyak 58 pengrajin. Teknik pengumpulan data menggunakan kuisioner dengan metode wawancara, pengamatan, dan dokumentasi. Teknik analisis data menggunakan deskriptif kuantitatif dengan prosentase. Hasil penelitian menyatakan bahwa karakteristik pengrajin industri sandal sepatu di Kecamatan Waru Kabupaten Sidoarjo memiliki umur paling banyak yaitu 45-49 tahun, jenis kelaminnya dari 58 orang pengrajin terdapat enam orang perempuan, tingkat pendidikan pengrajin 74,2% adalah SMA, status kawin, pendapatan, banyaknya jam kerja, jumlah tanggungan keluarga, dan jumlah tenaga kerja yang dipekerjakan tidak lebih dari 19 orang. Peranan industri sandal sepatu dari 6 desa ini mampu menyerap tenaga kerja sebesar 2,54% (593 orang) dari jumlah keseluruhan tenaga kerja yang bekerja di sektor industri. Asal wilayah sebaran tenaga kerja pada industri ini yang masih dalam satu desa dimana industri itu berdiri ada 80,6% tenaga kerja, dalam satu Kecamatan Waru lain desa ada 14,7%, luar Kabupaten Sidoarjo 2,9% tenaga kerja. Pemasaran hasil produksi dari industri sandal sepatu di Kecamatan Waru hampir ke kota-kota besar di seluruh Indonesia. Jumlah produk yang dipasarkan sebanyak 11.401 kodi per bulan dengan nilai produk sebesar Rp. 4.743.085.000,-dan dipasarkan ke 9 kota di luar Pulau Jawa dan 18 kota yang ada di Pulau Jawa.

Sadovski, A. (2019). Metod for determination of planting and harvesting dates by fuzzy regression. Bulgarin Journal of Soil Science Agrochemisty and Ecology, 53(3-4), 10-16 In this paper we investigate planting and harvesting dates of maize, potatoes and sugarbeets grown on the territory of selected USA states, which have similar homoclimates with Bulgaria. Such data are very important in agricultural practice and particularly in scheduling irrigation of agricultural crops. Fuzzy set theory provides a strict mathematical framework in which vague conceptual phenomena can be precisely studied and described. A simple solution approach was applied to solve a general fuzzy system of linear equations with crisp explanatory variables and fuzzy unknown variable vectors.

One of the important activities which directly affect the supply chain performance is the demand forecasting. But selection of the appropriate forecasting model that best fits the demand pattern is not an easy decision. This paper analyze the effects of fuzzy linear regression, fuzzy time series and fuzzy grey GM (1,1) forecasting models on supply chain performance quantifying the demand variability through the stages.

Penelitian ini dibertujuan untuk: 1) Menganalisis pengaruh strategi produksi terhadap peningkatan kinerja IKM/UKM Penyamakan Kulit. 2) Menganalisis pengaruh teknologi yang digunakan oleh strategi produksi terhadap peningkatan kinerja IKM/UKM Penyamakan Kulit. 3) Menganalisis pengaruh strategi distribusi terhadap peningkatan kinerja IKM/UKM Penyamakan Kulit. 4) Menganalisis pengaruh teknologi yang digunakan oleh strategi distribusi terhadap peningkatan kinerja IKM/UKM Penyamakan Kulit. 5) Menganalisis pengaruh strategi pemasaran langsung terhadap peningkatan kinerja IKM/UKM Penyamakan Kulit. Menganalisis pengaruh teknologi yang digunakan oleh strategi pemasaran langsung terhadap peningkatan kinerja IKM/UKM Penyamakan Kulit. 7) Menganalisis pengaruh langsung strategi teknologi terhadap peningkatan

South Africa and Ukraine share similar challenges for staff in the healthcare sector. Health care workers in South
Africa have borne the brunt of the COVID-19 pandemic whereas in Ukraine health care workers, amidst the war have
had to show valour and a tough spirit in caring for their patients under very trying circumstances. Arising from the
above tragedies, health care workers have shown incredible bravery both in Ukraine and in South Africa, however
they display extreme burn out. In Ukraine, nurses are working in the conflict zone and have to manage complex
patient mental and physical health issues. Some have even been subjected to violence from traumatized patients.
This article assesses the healthcare situation both in Ukraine and South Africa and provides a descriptive report
utilizing The Swanson’s theory of caring. The elements of Swanson’s theory consisting of maintaining belief,
knowing, being with, doing for, and enabling can be linked to characteristics such as supporting patients and colleagues,
being sensitive, affectionate and empathetic while feeling a sense of responsibility towards the department
and patients. The study, based at selected South African public central hospitals in two provinces, adopted a descriptive
exploratory paradigm. Qualitative techniques were used to administer an interview schedule to 322 frontline
participants. The results revealed that despite high commitment levels, the participants still faced challenges
that impact their daily work life.
The study conducted in South Africa on Quality of Work life (QWL) experiences of frontline healthcare workers
leaves recommendations for the Ukrainian health care sector.

THE ISRAEL-PALESTINE DISPUTE IN THE CONTEXT OF INTERNATIONAL LAW, THE ROLE OF THE UNITED NATIONS AND THE INTERNATIONAL COMMUNITY

Abstract 

The Israeli-Palestinian conflict presents a complex challenge in the realm of international law and the role of the international community. This article examines the conflict from an international legal perspective and assesses the contributions of the United Nations (UN) and other global actors towards resolving it. Since the establishment of the State of Israel in 1948, the dispute has extended beyond regional borders, sparking significant debates over international legal norms and human rights principles. The UN has attempted to address the conflict through various security resolutions and peace processes, yet these efforts have generally achieved limited success. The article evaluates the role of the UN and the international community in this context, discussing the implementation challenges of international legal norms and offering potential solutions. It analyzes the effectiveness of current peace processes and international interventions and provides recommendations for guiding future peace efforts. Ultimately, the role of international law and global actors is crucial for achieving a lasting resolution to the Israeli-Palestinian conflict.

Fuzzy regression models has been traditionally considered as a problem of linear programming. The use of quadratic programming allows to overcome the limitations of linear programming as well as to obtain highly adaptable regression approaches. However, we verify the existence of multicollinearity in fuzzy regression and we propose a model based on Ridge regression in order to address this problem.

In this research, the asymmetric effects of the government's fiscal instruments on the total factor productivity in Iran has been analyzed. So, at first, the total factor productivity index is calculated using the Solow balance method. Then, in order to investigate and empirically analyze the effect of government fiscal instruments on the total factor productivity, the linear (symmetric) and non-linear (asymmetric) autoregressive distributed lag method has been used. The findings in a linear (symmetrical) model show that the government size and the tax burden have a negative effect on the productivity. The non-linear (asymmetric) estimate also shows the asymmetric and negative effect of government size and tax burden on the productivity. In such a way that the negative effect of increases in the government size on the productivity is more than three times the negative effect of decreases in the government size. The tax burden is also associated with an asymmetric effect and its negative effect size during reductions on productivity is almost twice as much as its negative effect during increases. Inflation in a linear form is not associated with a significant effect, but in a non-linear form, it has an inverse and asymmetric effect on the productivity. In such a way that the favorable effect of reductions in inflation on the total productivity is more than the unfavorable effect of increases in inflation. The degree of openness in both symmetric and asymmetric models has a direct effect with the productivity as expected, and according to the estimate, the asymmetry of the effect was also confirmed for this factor. In such a way that the favorable effect of increases in the degree of openness on the productivity is more than four times the unfavorable effect of decreases in the degree of openness. Based on the results, it is suggested that the policy makers should pay attention to the asymmetry of the aforementioned factors in influencing the productivity while adopting appropriate policies in order to improve the productivity of the production factors.

Industri mebel rotan merupakan salah satu andalan sektor industri di Indonesia dimana sentra pengolahan rotan terbesar adalah di Kabupaten Cirebon, Jawa Barat. Namun, terdapat beberapa kendala dalam industri mebel rotan di Cirebon ini diantaranya semakin ketatnya persaingan antar produsen dunia dan kebijakan pemerintah memperbolehkan ekspor rotan yang menyebabkan keuntungan di pihak negara pesaing Oleh karena itu, dibutuhkan suatu strategi untuk meningkatkan daya saing produk rotan di pasar dunia. Strategi ini dapat diperoleh dengan melakukan analisis value chain. Tujuan dari penelitian ini adalah untuk menganalisis rantai nilai produk mebel rotan dan mendapatkan strategi kompetitif yang tepat untuk diterapkan oleh setiap pelaku rantai nilai. Metode yang dilakukan adalah analisis finansial, analisis SWOT, analisis Competitiveness Diamond, dan analisis Critical Success Factor (CSF). Objek penelitian adalah perusahaan-perusahaan yang merupakan anggota dari Asosiasi Pengusaha Mebel Indonesia (ASMINDO) Cirebon yang memproduksi mebel rotan single chair. Dari hasil pengolahan data dan analisis diperoleh hasil bahwa strategi yang dapat diterapkan di pihak supplier dalam hal ini pengumpul adalah mendirikan anak perusahaan di tempat tersedia bahan baku dan melakukan merger dengan perusahaan. Strategi yang dapat diterapkan di pihak perusahaan adalah menerapkan upah tenaga kerja per unit produk yang dihasilkan, pengalokasian dana untuk promosi, memprioritaskan buyer langganan, sharing informasi dan inovasi dengan buyer, memiliki fleksibilitas yang tinggi dalam hal kualitas dan harga, bekerjasama dengan asosiasi dan pemerintah dalam kegiatan pameran, dan melakukan merger dengan perusahaan lain ataupun dengan supplier. Sedangkan strategi yang dapat diterapkan di pihak buyer dalam hal ini wholeseller adalah menurunkan harga produk, memaksimalkan promosi dan menjaga hubungan baik dengan perusahaan yang sudah menjadi kepercayaan.

In the present work, a tree-based model that combines aspects of CART (Classification and Regression Trees) and STR (Smooth Transition Regression) is proposed. The main idea relies on specifying a parametric nonlinear model through a tree-growing procedure. The resulting model can be analysed either as a fuzzy regression or as a smooth transition regression with multiple regimes. Decisions about splits are entirely based on statistical tests of hypotheses and confidence intervals are constructed for the parameters within the ...

Bobbie Mills, Senior Researcher, School System and Performance. Bobbie has four years of experience of research, evaluation and data analysis in the education policy sector. Since joining EPI she has authored 'Boys studying modern foreign languages at GCSE in schools in England: Schools that are beating the odds' and co-authored 'Free schools in England: 2019 report' and 'General election 2019: An analysis of manifesto plans for education'.

Bobbie Mills, Senior Researcher, School System and Performance. Bobbie has four years of experience of research, evaluation and data analysis in the education policy sector. Since joining EPI she has authored 'Boys studying modern foreign languages at GCSE in schools in England: Schools that are beating the odds' and co-authored 'Free schools in England: 2019 report' and 'General election 2019: An analysis of manifesto plans for education'.

By applying the new approach to both the concept of soft belonging which is called soft element and the concept of distinct soft elements, we succeeded in introducing and studying the concepts of soft open sets, soft interior sets, soft neighborhood system and closure operator in fuzzifying soft topological spaces. Moreover the concept of a fuzzifying soft continuity was defined and studied.

Measurement of quality is an important task in the evaluation of agricultural products. A higher quality of raw input material produces a higher quantity and quality of end products. Therefore, in the palm oil production, the quality inspection process of fruits needs to be conducted properly to ensure that high-quality fruit bunches are selected. Additionally, human subjective judgments during the evaluation make the fruit grading inexact. Thus, the objectives of this paper is to build a fuzzy multi-criteria evaluation model that characterises the criteria of oil palm fruits to decide the fuzzy weights of these criteria based on a fuzzy regression model. A numerical example is included to illustrate the computational process of the proposed model.

Water quantity and quality are considered to be the main driving forces the reservoir operation. Barra Bonita reservoir, located in the southeast region of Brazil, is chosen as the case study for the application of the proposed methodology. Herein, optimization and artificial intelligence (AI) techniques are applied in the simulation and operation of the reservoir. A fuzzy stochastic dynamic programming model (FSDP) is developed for calculating the optimal operation procedures. Optimization is applied to achieve multiple fuzzy objectives. Markov chain technique is applied to handle the stochastic characteristics of river flow. Water quality analysis is carried out using an artificial neural network model. Organic matter and nutrient loads are modeled as a function of river discharge through the application of a fuzzy regression model based on fuzzy performance functions. The obtained results show that the proposed methodology provides an effective and useful tool for reservoir operation.

Our research’s main aim is to study two viewpoints: First, we define partial interval-valued
soft Ti(j)-spaces (i = 0, 1, 2, 3, 4; j = i, ii), study some of their properties and some of relationships
among them, and give some examples. Second, we introduce the notions of partial total intervalvalued
soft Tj(i)-spaces (i = 0, 1, 2, 3, 4; j = i, ii) and discuss some of their properties. We present some
relationships among them and give some examples.

In this paper predictions of the normalized difference vegetation index (NDVI) are discussed. Time series of Earth observation based estimates of vegetation inform about changes in vegetation. NDVI is an important parameter for vegetation forecasting and management of various problems, such as climate change monitoring, energy usage monitoring, managing the consumption of natural resources, agricultural productivity monitoring, drought monitoring and forest fire detection. Artificial Neural Networks (ANN's) are computational models and universal approximators, which are widely used for nonlinear, non-stationary and dynamical process modeling and forecasting. A layer recurrent neural network (LRN) is used in this paper to make one-step-ahead prediction of the NDVI time series.

Robot task representation typically involves a sequential set of steps. This methodology does not generalize to complex real-world tasks. Real-world tasks involve multiple paths of execution, where intra-task dependencies allow for different methods to complete the same task. Representing such complex tasks compactly poses a challenge as enumerating all possible paths results in combinatorial growth. As well, complex tasks benefit from the shared work of multiple agents. Tasks representations should provide a mechanism for multiple agents to communicate and self-organize as a team. We propose a control architecture to address these issues. The architecture 1) provides an efficient an compact encoding of complex tasks, 2) enables robots to infer what the other teammates are doing, 3) allows robots to dynamically decide which execution path to follow using an activation spreading mechanism.

A novel approach to the problem of regression modeling for fuzzy input-output data is introduced. In order to estimate the parameters of the model, a distance on the space of interval-valued quantities is employed. By minimizing the sum of squared errors, a class of regression models is derived based on the interval-valued data obtained from the α-level sets of fuzzy inputoutput data. Then, by integrating the obtained parameters of the intervalvalued regression models, the optimal values of parameters for the main fuzzy regression model are estimated. Numerical examples and comparison studies are given to clarify the proposed procedure, and to show the performance of the proposed procedure with respect to some common methods.

The goal of this paper is to handle the large variation issues in fuzzy data by constructing a variable spread multivariate adaptive regression splines (MARS) fuzzy regression model with crisp parameters estimation and fuzzy error terms. It deals with imprecise measurement of response variable and crisp measurement of explanatory variables. The proposed method is a two-phase procedure which applies the MARS technique at phase one and an optimization problem at phase two to estimate the center and fuzziness of the response variable. The proposed method, therefore, handles two problems simultaneously: the problem of large variation issue and the problem of variation spreads in fuzzy observations. A realistic application of the proposed method is also presented, by which the suspended load is modeled using discharge in a hydrology engineering problem. Empirical results demonstrate that the proposed approach is more efficient and more realistic than some well-known least-squares fuzzy regression models.

A novel approach to the problem of regression modeling for fuzzy input-output data is introduced.In order to estimate the parameters of the model, a distance on the space of interval-valued quantities is employed.By minimizing the sum of squared errors, a class of regression models is derived based on the interval-valued data obtained from the $alpha$-level sets of fuzzy input-output data.Then, by integrating the obtained parameters of the interval-valued regression models, the optimal values of parameters for the main fuzzy regression model are estimated.Numerical examples and comparison studies are given to clarify the proposed procedure, and to show the performance of the proposed procedure with respect to some common methods.

Development of financial markets and financial instruments is one of the pillars of economic growth and capital accumulation in any countries especially in the developing ones. Capital market works as a substantial tool for development and financing which attracts many investors for purchasing and selling capital. Hence they are seeking for forecasting events and situations of future till can invest with a lower uncertainty. On the other hand total index of stock exchanges accounted for a precursor one in economics which we expect following improvement in index of capital market, the economic growth will improve and we face condition of recession after its decrease. Thus the importance of exact prediction of this index is redoubled. In this paper we forecast the index by applying ARIMA and Neural Network and then we achieve the minimum and maximum of total index by using FARIMA. Indeed the main aim of this research is to imply this point that these three methods are complementary to...

Kegiatan di komoditas pertembakauan saat ini masih menghadapi berbagai masalah didalam beberapa aspek. Tidak konsistennya jumlah dan mutu produk yang dihasilkan, produktivitas yang rendah, pasar yang belum terorganisasi dengan baik, pasar yang tidak transparan, dimana semua ini menyebabkan rendahnya perolehan harga dan rendahnya pendapatan petani serta lemahnya daya saing produk tembakau. PTPN X sebagai penghasil tembakau Na-Oogst terbesar di Indonesia harus dapat mengoptimalisasi dan meningkatkan fungsi dan peran lembaga pertembakauan, meskipun berbagai isu yang terkait dengan komoditas tembakau mendapatkan sorotan yang negatif terhadap produk tersebut. Meskipun demikian pangsa pasar produk-produk berbasis tembakau masih cukup menjanjikan sehingga perlu untuk dicarikan strategi yang tepat untuk menjaga eksistensi dan daya saingnya. Tujuan penelitian ini dibagi tiga, (1) Mengindentifikasi aktivitas Value Chain perusahaan tembakau cerutu milik SBU tembakau PTPN X; (2) Mengidentifikas...

The formulated mathematical model needs predetermined and precise model parametersto find a solution. However, the model parameters such as coefficient value are usually not precisely known. Coefficient plays a pivotal role sincethe coefficientcouldprovide important information in relationship between algebraic and linguistic expression. Existing method which is commonly used to generate the precise parametric valuesis unable to handle the coexistence of fuzzy information. Moreover, selecting real numbers for coefficients in random process increases the complexity inprogramming process. Hence, we proposed a fuzzy random regression method in this paper to estimate the precise coefficient values which contains fuzzy random information. An illustrative numerical example is provided to deduce coefficient values from different data representation which included the fuzziness and randomness.The coefficients were treated based on the property of fuzzy random regression. The approach results show that we have the significant capabilities to estimate the coefficient value and improve the model which retain the simultaneous uncertainties and set up in production planning problem.

Fuzzy relation equations (FRE) are associated with the composition of binary fuzzy relations. In the present work FRE are used as a tool for studying the process of learning a new subject matter by a student class. A classroom application and other suitable examples connected to the student learning of the derivative are also presented illustrating our results and useful conclusions are obtained.

Hypoglycemia or low blood glucose is dangerous and can result in unconsciousness, seizures and even death for Type 1 diabetes mellitus (T1DM) patients. Based on the T1DM patients' physiological parameters, corrected QT interval of the electrocardiogram (ECG) signal, change of heart rate, and the change of corrected QT interval, we have developed a neural network based rule discovery system with hybridizing the approaches of neural networks and genetic algorithm to identify the presences of hypoglycemic episodes for TIDM patients. The proposed neural network based rule discovery system is built and is validated by using the real T1DM patients' data sets collected from Department of Health, Government of Western Australia. Experimental results show that the proposed neural network based rule discovery system can achieve more accurate results on both trained and unseen T1DM patients' data sets compared with those developed based on the commonly used classification methods for medical diagnosis, statistical regression, fuzzy regression and genetic programming. Apart from the achievement of these better results, the proposed neural network based rule discovery system can provide explicit information in the form of production rules which compensate for the deficiency of traditional neural network method which do not provide a clear understanding of how they work in prediction as they are in an implicit black-box structure. This explicit information provided by the product rules can convince medical doctors to use the neural networks to perform diagnosis of hypoglycemia on T1DM patients.

The change of the intensive precipitation with a threshold above 10 mm has been investigated. This is done directly by determining the proportion of such rainfall from the future to the reference period. The Monte Carlo method has been used to test the sustainability of trends by identifying areas where rainfall is most commonly observed in all developments of the model's internal variability for the integration period. The climate change signal indicates an increase in precipitation where it prevails so far. The least affected area is Eastern Bulgaria, except Strandja Mountain. The most affected are West and Northwestern Bulgaria.

The present study is intended to develop an intelligent model for the prediction of color strength of cotton knitted fabrics using fuzzy knowledge based expert system (FKBES). The factors chosen for developing the prediction model are dye concentration, dyeing time and process temperature. Besides, such factors are nonlinear and have mutual interactions among them; so it is not easy to create an exact correlation between the inputs variables and color strength using mathematical or statistical methods. In contrast, artificial neural network and neural-fuzzy models require massive amounts of experimental data for model parameters optimization which are challenging to collect from the dyeing industries. In this context, fuzzy knowledge based expert system is the most efficient modeling tool which performs exceptionally well in a non-linear complex domain with lowest amount of trial data like human experts. In this study, laboratory scale experiments were conducted for three types of c...

Salah satu pendukung sektor ekonomi di Indonesia adalah sektor industri yang berfokus pada industri pengolahan. Provinsi Banten dengan Kota Cilegon yang merupakan salah satu kota industrinya. Kota Cilegon memiliki potensi industri hulu petrokimia yang besar tetapi tidak banyak memiliki industri hilir atau turunannya. Penelitian ini bertujuan untuk merancang sentra industri hilir petrokimia dengan menggunakan tahapan DMAIC (define-measure-analyze-improve-control). Tahap define mendefinisikan bentuk dan jenis industri hilir petrokimia yang dikembangkan yaitu industri hilir safety gloves, dengan bentuk industri kecil dan menengah (IKM). Pada tahap measure dihasilkan cluster map, diagram SIPOC, dan rancangan rantai pasokan untuk sentra IKM. PT XYZ, PT PQR, dan pemasok packaging sebagai supplier; sentra IKM sebagai manufacturer; jasa distribusi dan transportasi sebagai distributor; toko penjual eceran sebagai retailer; dan customer akhir. Pada tahap analyze terdiri dari value chain analysis dan analisa SWOT (strength-weakness-opportunity-threats). Pada tahap improve disusun matriks IFAS (internal factor analysis summary) dan EFAS (external factor analysis summary). Hasil Grand Strategy Matrix menunjukkan total skor faktor internal adalah 1,4, dan total skor faktor eksternal adalah 2,0. Oleh karena itu, didapatkan titik koordinat (1,4 ; 2,0) yang berada di kuadran pertumbuhan (growth). Strategi yang dilakukan adalah strategi SO (strength-opportunity): 1) melakukan promosi melalui platform media sosial serta marketplace; 2) melakukan kerjasama dengan pemerintah untuk distribusi di luar Provinsi Banten; 3) melakukan pembangunan IKM di salah satu kelurahan di Kecamatan Citangkil; 4) melakukan sosialisasi terkait profesi yang ada pada IKM kepada warga sekitar; dan 5) melakukan pelatihan bagi tenaga kerja dari penduduk sekitar.

Purpose – The purpose of this paper is to test the impact of the internal audit function (IAF), an increasingly common internal governance mechanism, on a firm's financial reporting quality. Specifically, this paper investigates the association between the quality of the IAF and abnormal accruals (as a proxy for financial reporting quality) and whether the board of directors play a role in moderating the relationship. Design/methodology/approach – This paper uses a unique dataset of survey responses and archival data. Regression analysis was used to test their hypotheses. Findings – Although their initial findings show an unexpected positive relationship between internal audit quality and abnormal accruals, this relationship is contingent on whether firms outsource their internal audit activities and/or whether they are politically linked. In estimations excluding outsourcing and political connections observations, this paper shows that the association between internal audit qua...

ABSTRACT. The concept of right (left) quotient (or residual) of an ideal η by an ideal ν of an L-subring µ of a ring R is introduced. The right (left) quotients are shown to be ideals of µ. It is proved that the right quotient]: [ νη r of an ideal η by an ideal ν of an L-subring µ is the largest ideal of µ such that ηννη ⊆]: [ r. Most of the results pertaining to the notion of quotients (or residual) of an ideal of ordinary rings are extended to L-ideal theory of L-subrings.

In the crisp regression models, the differences between observed values and calculates ones are suspected to be caused by random distributed errors, although these are due to observation errors and an unappropriate model structure. So, the fuzzy character of model prevails. The Fuzzy linear regression models (FLRM) are, roughly speaking, of two kinds: Fuzzy linear programming (FLP) based methods and Fuzzy least squares (FLS) methods. The FLP methods have been initiated by H.Tanaka (1982) and developed by H. Ishibuchi et al. The classical FLR model, Y=A0+A1X1+...+AkXk, has a explained Fuzzy triangular variable, Y, Fuzzy triangular coefficients {Aj} and crisp explanatory variables {Xj}: the parameters {Aj} of the model are estimated by minimizing the total indetermination of the model, so each data point lies within the limits of the response variable. In a large number of situations the prediction interval of the FLR model were much less than the interval obtained applying classical ...

The greater mouse-eared bat (Myotis myotis) is a flagship species for the protection of hibernation and summer maternity roosts in the Western Palearctic region. A range of pathogenic agents is known to put pressure on populations, including the white-nose syndrome fungus, for which the species shows the highest prevalence and infection intensity of all European bat species. Here, we perform analysis of blood parameters characteristic for the species during its natural annual life cycle in order to establish reference values. Despite sexual dimorphism and some univariate differences, the overall multivariate pattern suggests low seasonal variation with homeostatic mechanisms effectively regulating haematology and blood biochemistry ranges. Overall, the species displayed a high haematocrit and haemoglobin content and high concentration of urea, while blood glucose levels in swarming and hibernating bats ranged from hypo-to normoglycaemic. Unlike blood pH, concentrations of electrolytes were wide ranging. To conclude, baseline data for blood physiology are a useful tool for providing suitable medical care in rescue centres, for studying population health in bats adapting to environmental change, and for understanding bat responses to stressors of conservation and/or zoonotic importance.

White-nose syndrome (WNS) is a fungal disease caused by Pseudogymnoascus destructans that is devastating to Nearctic bat populations but tolerated by Palearctic bats. Temperature is a factor known to be important for fungal growth and bat choice of hibernation. Here we investigated the effect of temperature on the pathogenic fungal growth in the wild across the Palearctic. We modelled body surface temperature of bats with respect to fungal infection intensity and disease severity and were able to relate this to the mean annual surface temperature at the site. Bats that hibernated at lower temperatures had less fungal growth and fewer skin lesions on their wings. Contrary to expectation derived from laboratory P. destructans culture experiments, natural infection intensity peaked between 5 and 6°C and decreased at warmer hibernating temperature. We made predictive maps based on bat species distributions, temperature and infection intensity and disease severity data to determine not only where P. destructans will be found but also where the infection will be invasive to bats across the Palearctic. Together these data highlight the mechanistic model of the interplay between environmental and biological factors, which determine progression in a wildlife disease.

Background: Hibernation allows animals to survive periods of resource scarcity by reducing their energy expenditure through decreased metabolism. However, hibernators become susceptible to psychrophilic pathogens if they cannot mount an efficient immune response to infection. While Nearctic bats infected with white-nose syndrome (WNS) suffer high mortality, related Palearctic taxa are better able to survive the disease than their Nearctic counterparts. We hypothesised that WNS exerted historical selective pressure in Palearctic bats, resulting in genomic changes that promote infection tolerance. Results: We investigated partial sequences of 23 genes related to water metabolism and skin structure function in nine Palearctic and Nearctic hibernating bat species and one non-hibernating species for phylogenetic signals of natural selection. Using maximum likelihood analysis, we found that eight genes were under positive selection and we successfully identified amino acid sites under selection in five encoded proteins. Branch site models revealed positive selection in three genes. Hibernating bats exhibit signals for positive selection in genes ensuring tissue regeneration, wound healing and modulation of the immune response. Conclusion: Our results highlight the importance of skin barrier integrity and healing capacity in hibernating bats. The protective role of skin integrity against both pathophysiology and WNS progression, in synergy with downregulation of the immune reaction in response to the Pseudogymnoascus destructans infection, improves host survival. Our data also suggest that hibernating bat species have evolved into tolerant hosts by reducing the negative impact of skin infection through a set of adaptations, including those at the genomic level.

We examine residential relocation and opting out of the public school system in response to school choice lottery outcomes. We show that rising kindergartners and sixth graders who lose a school choice lottery are 6 percentage points more likely to exit the district or change neighborhood schools (20% to 30% increase) and make up 0.14 to 0.35 standard deviations in average school test scores between lottery assignment and attendance the following year. Using hedonic-based estimates of land prices, we estimate that lottery losers pay a 9% to 11% housing price premium for access to a school with a 1 standard deviation higher mean test score.

Ecological understanding of host-pathogen dynamics is the basis for managing wildlife diseases. Since 2008, federal, state, and provincial agencies and tribal and private organizations have collaborated on bat and white-nose syndrome (WNS) surveillance and monitoring, research, and management programs. Accordingly, scientists and managers have learned a lot about the hosts, pathogen, and dynam-† Work was done while serving as a visiting scientist with the United States Geological Survey.

Industri mebel rotan merupakan salah satu andalan sektor industri di Indonesia dimana sentra pengolahan rotan terbesar adalah di Kabupaten Cirebon, Jawa Barat. Namun, terdapat beberapa kendala dalam industri mebel rotan di Cirebon ini diantaranya semakin ketatnya persaingan antar produsen dunia dan kebijakan pemerintah memperbolehkan ekspor rotan yang menyebabkan keuntungan di pihak negara pesaing Oleh karena itu, dibutuhkan suatu strategi untuk meningkatkan daya saing produk rotan di pasar dunia. Strategi ini dapat diperoleh dengan melakukan analisis value chain. Tujuan dari penelitian ini adalah untuk menganalisis rantai nilai produk mebel rotan dan mendapatkan strategi kompetitif yang tepat untuk diterapkan oleh setiap pelaku rantai nilai. Metode yang dilakukan adalah analisis finansial, analisis SWOT, analisis Competitiveness Diamond, dan analisis Critical Success Factor (CSF). Objek penelitian adalah perusahaan-perusahaan yang merupakan anggota dari Asosiasi Pengusaha Mebel Indonesia (ASMINDO) Cirebon yang memproduksi mebel rotan single chair. Dari hasil pengolahan data dan analisis diperoleh hasil bahwa strategi yang dapat diterapkan di pihak supplier dalam hal ini pengumpul adalah mendirikan anak perusahaan di tempat tersedia bahan baku dan melakukan merger dengan perusahaan. Strategi yang dapat diterapkan di pihak perusahaan adalah menerapkan upah tenaga kerja per unit produk yang dihasilkan, pengalokasian dana untuk promosi, memprioritaskan buyer langganan, sharing informasi dan inovasi dengan buyer, memiliki fleksibilitas yang tinggi dalam hal kualitas dan harga, bekerjasama dengan asosiasi dan pemerintah dalam kegiatan pameran, dan melakukan merger dengan perusahaan lain ataupun dengan supplier. Sedangkan strategi yang dapat diterapkan di pihak buyer dalam hal ini wholeseller adalah menurunkan harga produk, memaksimalkan promosi dan menjaga hubungan baik dengan perusahaan yang sudah menjadi kepercayaan.