Fuzzy Maximum Satisfiability

In this paper, we extend the Maximum Satisfiability (MaxSAT) problem to {\L}ukasiewicz logic. The MaxSAT problem for a set of formulae {\Phi} is the problem of finding an assignment to the variables in {\Phi} that satisfies the maximum number of formulae. Three possible solutions (encodings) are proposed to the new problem: (1) Disjunctive Linear Relations (DLRs), (2) Mixed Integer Linear Programming (MILP) and (3) Weighted Constraint Satisfaction Problem (WCSP). Like its Boolean counterpart, the extended fuzzy MaxSAT will have numerous applications in optimization problems that involve vagueness.Comment: 10 page

Effects of dried sugar beet root based concentrates level on wholesale cuts and eye muscle characteristics in Nubian goat male kids

    High meat demand and prices in the Sudan highlighted the needs to improve goat exploitation due to high population and meat high nutritive value and health attributes. However, goats are mainly raised in traditional systems with low inputs and outputs. Nubian is the main goat dairy breed and culled males are used for meat production. Nutrition is among the main constraints for goat production and cconcentrates are not commonly fed. Sugar beet is introduced into the Gezira State and is a valuable feed. There is no information on the effects of dried sugar beet roots (DSBR) based concentrates level on Nubian goat male kids performance and carcass characteristics. Twelve Nubian  goat male kids at 6 month old were housed individually, divided into 3 groups and allocated at random to feeds in 2016. They were fed upgraded Seewa (UPS) ad lib. at 8 am and 4 pm. They were fed DSBP based concentrates (70% DSBP,15% groundnut cakes and 15% sunflower cakes) at 0 (control), 250 g and 500 g in two meals before UPS. They were fed for 8 weeks in addition to a two week preliminary period. They were slaughtered and the left side was divided into wholesale cuts, weighed and dissected. The rib section (10th – 12th) was removed and characteristics and meat composition were determined. All wholesale cuts weight increased with concentrates level. Supplementing upgraded Seewa improved Nubian male kids performance and carcass characteristics. Eye muscle characteristics were affected with concentrates level, but not significantly different.  Concentrates level significantly (P<0.05) affected meat DM, CP and ash. Animals fed 500 g had the highest DM, EE and ash. Animals fed 250 g concentrates had the highest CP. It was concluded that DSBP based concentrates level had improved wholesale cuts weight and meat composition. It was recommended to use DSBR based concentrates and upgraded Seewa in fattening Nubian goat  male kids.                 تمثل الماعز النوبي سلالة الألبان الرئيسة وتستخدم الذكور المستبعدة من القطيع  لإنتاج اللحوم. تعتبر التغذية معوقا رئيسيا لانتاج الماعز ولا تستخدم عادة علائقا مركزة . تم مؤخرا إدخال زراعة  بنجرالسكر في ولاية الجزيرة وهو مصدر علفي قيم. ولا تتوفر معلومات عن استخدام عليقة ترتكز على جذور بنجر السكر المجففة على الأداء وصفات الذبيحة في جديان  ذكور للماعز النوبي. وضع 12 ذكرا من الماعز النوبي بعمر سته أشهر في حظائر مفردة ووزعت لثلاثة مجموعات ووزعت المجموعات لثلاثة أعلاف بصورة عشوائية كاملة في عام 2016م. غذيت الحيوانات على مخلفات قناديل الذرة المحسنة  حسب الرغبة عند الساعه الثامنة صباحا  والرابعة مساءا. كما غذيت الحيوانات على عليقة مركزة ترتكز على جذور  بنجر السكر المجفف ( 70% جذور بنجر السكر المجففة,15% أمباز الفول السوداني و15% أمباز بذرة زهرة الشمس) عند صفر           ( الشاهد) 250 جرام و500 جرام في وجبتين قبل مخلفات قناديل الذرة  المحسنة. غذيت الحيوانات لمدة ثمانية أسابيع مع أسبوعين كفترة تمهيدية. تم ذبح الحيوانات وقسم الجانب الأيسر للقطع الاجماليه ووزنت وشٌرٍحت. اخذ جزء الأضلع ( من العاشرة الى الثانية عشر) وقيست صفات العضلة العينية وتركيب اللحم. جميع القطع الاجماليه  زاد وزنها مع مستوي العليقة المركزة وزادت نسبتهم المئوية مع مستوي العليقة المركزة حتى 250 جراما ثم انخفضت عند500 جرام عليقة مركزة .تأثرت صفات  العضلة العينية بمستوي العليقة المركزة بشكل غيرمعنوي. أثر مستوي العليقة المركزة بشكل معنوي علي المادة الجافة ونسبة البروتين الخام  والرماد  في اللحم. كانت نسب المادة الجافة والمستخلص الأثيري والرماد أعلي في الحيوانات التي غذيت على 500جرام عليقة مركزة. كانت نسبة البروتين الخام أعلي في الحيوانات التي غذيت على 250جرام من العليقة المركزة.كانت الخلاصة من الدراسة ان استخدام مستويات مختلفة من عليقة مركزة ترتكز على جذور بنجر السكر المجففة حسن وزن القطع الاجمالية للذبيحة وتركيب اللحوم. لذلك يوصي بإستخدام جذور بنجر السكر المجفف بمستويات مختلفه مع قناديل الذرة  المحسنة في تسمين ذكور الماعز النوبي .                                                          &nbsp

PROTEIN-ENERGY MALNUTRITION IN CENTRAL SUDAN: STUDY OF PREVALENCE AND SOCIO- ECONOMIC BACKGROUND

There is no abstrac

Generalization of Fuzzy C-Means Based on Neutrosophic Logic

This article presents a New Neutrosophic C-Means (NNCMs) method for clustering. It uses the neutrosophic logic (NL), to generalize the Fuzzy C-Means (FCM) clustering system. The NNCMs system assigns objects to clusters using three degrees of membership: a degree of truth, a degree of indeterminacy, and a degree of falsity, rather than only the truth degree used in the FCM. The indeterminacy degree, in the NL, helps in categorizing objects laying in the intersection and the boundary areas. Therefore, the NNCMs reaches more accurate results in clustering. These degrees are initialized randomly without any constraints. That is followed by calculating the clusters’ centers

Neutrosophic rule-based prediction system for toxicity effects assessment of biotransformed hepatic drugs

Measuring toxicity is an important step in drug development. However, the current experimental meth- ods which are used to estimate the drug toxicity are expensive and need high computational efforts. Therefore, these methods are not suitable for large-scale evaluation of drug toxicity. As a consequence, there is a high demand to implement computational models that can predict drug toxicity risks. In this paper, we used a dataset that consists of 553 drugs that biotransformed in the liver

New Entropy-Based Similarity Measure between Interval-Valued Intuitionstic Fuzzy Sets

In this paper we propose a new approach to construct similarity measures using the entropy measure for Interval-Valued Intuitionistic Fuzzy Sets. In addition, we provide several illustrative examples to demonstrate the practicality and effectiveness of the proposed formula. Finally, we use the new proposed similarity measure to develop new approach for solving problems of pattern recognition and multi-criteria fuzzy decision making

The Application of Unsupervised Clustering Methods to Alzheimer’s Disease

Clustering is a powerful machine learning tool for detecting structures in datasets. In the medical field, clustering has been proven to be a powerful tool for discovering patterns and structure in labeled and unlabeled datasets. Unlike supervised methods, clustering is an unsupervised method that works on datasets in which there is no outcome (target) variable nor is anything known about the relationship between the observations, that is, unlabeled data. In this paper, we focus on studying and reviewing clustering methods that have been applied to datasets of neurological diseases, especially Alzheimer’s disease (AD). The aim is to provide insights into which clustering technique is more suitable for partitioning patients of AD based on their similarity. This is important as clustering algorithms can find patterns across patients that are difficult for medical practitioners to find. We further discuss the implications of the use of clustering algorithms in the treatment of AD. We found that clustering analysis can point to several features that underlie the conversion from early-stage AD to advanced AD. Furthermore, future work can apply semi-clustering algorithms on AD datasets, which will enhance clusters by including additional information